problems to solve with technology

14 Major Tech Issues — and the Innovations That Will Resolve Them

The past year has seen unprecedented challenges to public-health systems and the global economy. Many facets of daily life and work have moved into the digital realm, and the shift has highlighted some underlying business technology issues that are getting in the way of productivity, communication and security.

As successful business leaders, the members of the  Young Entrepreneur Council understand how important it is to have functional, up-to-date technology. That ’ s why we asked a panel of them to share what they view as the biggest business tech problem of the past year. Here are the issues they ’ re concerned about and the innovations they believe will help solve them.

Current Major Technology Issues

• Need For Strong Digital Conference Platforms
• Remote Internet Speed and Connections
• Phishing and Data Privacy Issues
• Deepfake Content
• Too Much Focus on Automation
• Data Mixups Due to AI Implementation
• Poor User Experience

1. Employee Productivity Measurement

As most companies switched to 100 percent remote almost overnight, many realized that they lacked an efficient way to measure employee productivity. Technology with “ user productivity reports ”  has become invaluable. Without being able to “ see ”  an employee in the workplace, companies must find technology that helps them to track and report how productive employees are at home. — Bill Mulholland , ARC Relocation

2. Digital Industry Conference Platforms

Nothing beats in-person communication when it comes to business development. In the past, industry conferences were king. Today, though, the move to remote conferences really leaves a lot to be desired and transforms the largely intangible value derived from attending into something that is purely informational. A new form or platform for industry conferences is sorely needed. — Nick Reese , Elder Guide

3. Remote Internet Speed and Equipment

With a sudden shift to most employees working remotely, corporations need to boost at-home internet speed and capacity for employees that didn ’ t previously have the requirements to produce work adequately. Companies need to invest in new technologies like 5G and ensure they are supported at home. — Matthew Podolsky , Florida Law Advisers, P.A.

4. Too Much Focus on Automation

Yes, automation and multi-platform management might be ideal for big-name brands and companies, but for small site owners and businesses, it ’ s just overkill. Way too many people are overcomplicating things. Stick to your business model and what works without trying to overload the process. — Zac Johnson , Blogger

5. Phishing Sites

There are many examples of phishing site victims. Last year, I realized the importance of good pop-up blockers for your laptop and mobile devices. It is so scary to be directed to a website that you don ’ t know or to even pay to get to sites that actually don ’t  exist. Come up with better pop-up blockers if possible. — Daisy Jing , Banish

6. Data Privacy

I think data privacy is still one of the biggest business tech issues around. Blockchain technology can solve this problem. We need more and more businesses to understand that blockchains don’t just serve digital currencies, they also protect people’s privacy. We also need Amazon, Facebook, Google, etc. to understand that personal data belongs in the hands of the individual. — Amine Rahal , IronMonk Solutions

7. Mobile Security

Mobile security is a big issue because we rely so much on mobile internet access today. We need to be more aware of how these networks can be compromised and how to protect them. Whether it ’ s the IoT devices helping deliver data wirelessly to companies or people using apps on their smartphones, we need to become more aware of our mobile cybersecurity and how to protect our data. — Josh Kohlbach , Wholesale Suite

8. Deepfake Content

More and more people are embracing deepfake content, which is content created to look real but isn ’ t. Using AI, people can edit videos to look like someone did something they didn ’ t do and vice versa, which hurts authenticity and makes people question what ’ s real. Lawmakers need to take this issue seriously and create ways to stop people from doing this. — Jared Atchison , WPForms

9. Poor User Experience

I ’ ve noticed some brands struggling with building a seamless user experience. There are so many themes, plugins and changes people can make to their site that it can be overwhelming. As a result, the business owner eventually builds something they like, but sacrifices UX in the process. I suspect that we will see more businesses using customer feedback to make design changes. — John Brackett , Smash Balloon LLC

10. Cybersecurity Threats

Cybersecurity threats are more prevalent than ever before with increased digital activities. This has drawn many hackers, who are becoming more sophisticated and are targeting many more businesses. Vital Information, such as trade secrets, price-sensitive information, HR records, and many others are more vulnerable. Strengthening cybersecurity laws can maintain equilibrium. — Vikas Agrawal , Infobrandz

11. Data Backup and Recovery

As a company, you ’ ll store and keep lots of data crucial to keeping business moving forward. A huge tech issue that businesses face is their backup recovery process when their system goes down. If anything happens, you need access to your information. Backing up your data is crucial to ensure your brand isn ’ t at a standstill. Your IT department should have a backup plan in case anything happens. — Stephanie Wells , Formidable Forms

12. Multiple Ad and Marketing Platforms

A major issue that marketers are dealing with is having to use multiple advertising and marketing platforms, with each one handling a different activity. It can overload a website and is quite expensive. We ’ re already seeing AdTech and MarTech coming together as MAdTech. Businesses need to keep an eye on this convergence of technologies and adopt new platforms that support it. — Syed Balkhi , WPBeginner

13. Location-Based Innovation

The concentration of tech companies in places like Seattle and San Francisco has led to a quick rise in living costs in these cities. Income isn ’ t catching up, and there ’ s stress on public infrastructure. Poor internet services in rural areas also exacerbate this issue. Innovation should be decentralized. — Samuel Thimothy , OneIMS

14. Artificial Intelligence Implementation

Businesses, especially those in the tech industry, are having trouble implementing AI. If you ’ ve used and improved upon your AI over the years, you ’ re likely having an easier time adjusting. But new online businesses test multiple AI programs at once and it ’ s causing communication and data mix-ups. As businesses settle with specific programs and learn what works for them, we will see improvements. — Chris Christoff , MonsterInsights

Built In’s expert contributor network publishes thoughtful, solutions-oriented stories written by innovative tech professionals. It is the tech industry’s definitive destination for sharing compelling, first-person accounts of problem-solving on the road to innovation.

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How to solve 10 common problems with technology

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Technology might cause some of your problems, but it can also solve them. 

I use technology to help with my problems on a daily basis, and I've identified some that most other people have, too.

Whether your work environment is noisy or messy, or you're looking to save a little money, you can find the solutions to your problem on this list.

The problem: not enough outlets

Apartment dwellers are generally worse off when it comes to usable outlets, but even homeowners might find that they're quickly running out of places to plug in their new gadgets. 

You can solve this problem a few different ways depending on its root cause. 

If you're clustering a lot of electronics together (think a home theater system), you should buy a surge protector . I've used one from Belkin for years, and it has helped me stay organized and keeps my gadgets safe. 

If the problem is that too many of our outlets are taken up by single-use power adapters for phones and tablets, you have options. You could go the DIY route and replace the outlets themselves with new ones that have USB ports built into them . Or, you could buy one of Anker's multi-port adapters , which let you charge up to five devices while only taking up a single outlet. 

Regardless of which option you pick, your life will be easier knowing there's a place to plug in the next cool thing you bring home.

Anker PowerPort 5 Multi-Port USB Charger, $23.99, available at Amazon

Topgreener usb charger outlet, $19.99, available at amazon, belkin 8-outlet commercial power strip surge protector, $14.88, available at amazon  , the problem: bad wi-fi.

I've heard people say that having bad Wi-Fi is  worse than having no Wi-Fi, and I agree.

If you live in a place with spotty Wi-Fi you have two options: extend your current network, or create a stronger one. 

I've tried TP-Link's Wi-Fi range extender , and given its budget-friendly price it's what I recommend people try first. It's easy to set up and does a really good job, providing adequate coverage in places that have none. 

If you live in a bigger home, it might be worthwhile to invest in a multi-router Wi-Fi setup, in which case I recommend Eero . Instead of extending your Wi-Fi, Eero's routers create a strong Wi-Fi net to blanket an area in complete coverage. Each router has the same strength and range, so installing them strategically around your house should provide high-speed coverage everywhere.

TP-Link AC750 Wi-Fi Range Extender, $24.99, available at Amazon

Eero home wi-fi system (2-pack), $259.99, available at amazon, the problem: dirty floors.

Most people would  like a robot vacuum, but it can be a pretty significant expense. 

I recently tried a more budget-friendly option in this category, and I'm still impressed at how well it works. With six modes and a 90-minute battery life, Eufy's vacuum should be a good fit for any apartment and single-floor homes. 

The vacuum's sensors are good enough that it's able to accurately clean a room after a very quick survey. Although I'm pretty meticulous when I clean, I can honestly say that since I started trying the Eufy my floors have never been tidier.

Eufy RoboVac 11, $219.99, available at Amazon

The problem: shoddy battery life.

If your phone's battery just isn't cutting it, there are to ways to help it get through a night out or weekend camping trip. 

Those who don't mind adding a little bulk to their phone can invest in one of Mophie's charging cases. Yes, they're bigger than your average case, but they also extend your phone's battery life significantly. During my tests, I was able to get over 30 hours of battery life with my iPhone 7 Plus.

If bulky cases are a no-go, you can pick up one of Anker's external battery packs instead. The one I'm recommending can recharge most phones once or twice, and is still small enough to fit in a pocket, purse, or backpack.

mophie juice pack wireless for the iPhone 7, $71.98, available at Amazon

Mophie juice pack wireless for the iphone 7 plus, $74, available at amazon  , anker powercore 10000 portable battery pack, $25.99, available at amazon, the problem: wanting multi-room audio.

I love Bluetooth speakers, but if you live in a large place and want multi-room audio, things get a little complicated. 

I've had a chance to try Libratone's TOO speaker , which I still think is a great solution to this problem  if you value portability. You can link pairs of these speakers together into "zones," and you can play the same audio from both at the same time.

If you'd prefer to link up multiple speakers and don't care about portability, your best option is Sonos . The whole idea behind the well-known speaker brand is to slowly amass a collection of speakers in every room of your house. Sonos offers greater flexibility than Libratone's solution, but again, you give up portability.

Libratone TOO Portable Bluetooth Speaker, $149, available at Amazon

Sonos play:1 wireless smart speaker, $199, available at amazon, the problem: a high cable bill.

If you cable bill continues to creep up, it might be the right time to consider cutting out your TV package.

I haven't had cable in years, and while I don't  miss live TV, I understand the utility in having it during important events, which is why I bought an HDTV antenna. 

How useful this antenna is will depend on your location, but with a 50-mile range you're likely to pick up the big four networks: ABC, CBS, NBC, and Fox. You should check how good the over-the-air cover coverage is in your area before making the investment, but in my experience, it's worth it. 

1byone 50 Miles Amplified HDTV Antenna, $29.99, available at Amazon

The problem: too many wires on your desk.

A messy work environment can make it difficult to get things done. 

I realized that the quickest way for  me to clear it off was by investing in some wireless tech, namely a wireless keyboard and mouse. 

I've settled on a Bluetooth mouse from Logitech and Bluetooth keyboard from Anker , and despite their reasonable price tags, I've never had to search further. Both paired to my computer instantly and have worked well together for years. 

My preference for Bluetooth gear over traditional wireless gear is the lack of wireless receivers. Instead of taking up a USB port with a small adapter you might lose, these accessories are  totally wireless.

Logitech M557 Bluetooth Mouse, $19.95, available at Amazon

Anker bluetooth ultra-slim keyboard, $17.99, available at amazon, the problem: overcooked or undercooked food.

Whether you're cooking inside, outside, for yourself, or for family, nothing is worse than overcooking or undercooking food.

With grilling season nearly here, Weber has just released the iGrill 3 , its latest wireless thermometer. Stick it into the center of your meat and you'll never have to worry about the steak or chicken being too pink in the middle.

Indoor chefs might want to try sous vide cooking, a technique that heats meat or vegetables up to the perfect temperature by bagging them up and submerging them in water. It might come across as strange at first, but it's a technique that's been used to cook food in high-end restaurants for years. Anova is the biggest name in consumer-grade sous vide cooking, and their option can be paired with your phone via Bluetooth to let you know when your meal is done.

Weber iGrill 3 Bluetooth Thermometer, $98, available at Amazon

Anova culinary bluetooth sous vide, $149, available at amazon, the problem: a boring commute.

Commutes, even when they're relatively short, can be tedious. 

If you prefer to occupy your mind with games rather than a book or music, I have two recommendations that got me through months of train trips.

Minimize is a minimalist puzzle game that requires you to pair similarly colored tiles together. It starts out simple but has a nice difficulty curve. The last few levels required enough concentration that I almost missed my stop. 

Arguably the most well-known puzzle game on the planet, Tetris is easy to play, but tough to master. Like Minimize, the difficulty curve is gentle, but when blocks start falling at a rapid pace it's easy to lose track of time.

Minimize, $2.99

Tetris, $1.99, the problem: working or living in a noisy environment.

If you're like me, you need silence or pleasant sounds to get anything done. 

Unfortunately, it's difficult to get peace and quiet everywhere, which is why it's a good idea to invest in some noise-cancelling headphones. I've recommended Sony's H.ear headphones for the past few months, and everyone who's tried them has come away impressed. 

They're comfortable, sound good, have the only worthwhile on-ear cup controls I've found on headphones, and their noise cancelling is excellent. If you're looking for a way to put a barrier between you and the outside world, these headphones are a great way to do it.

Sony H.ear on Wireless Noise Cancelling Headphone, $219, available at Amazon

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Read our research on: Israel | Internet & Technology | Family & Relationships

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5. tech causes more problems than it solves.

A number of respondents to this canvassing about the likely future of social and civic innovation shared concerns. Some said that technology causes more problems than it solves. Some said it is likely that emerging worries over the impact of digital life will be at least somewhat mitigated as humans adapt. Some said it is possible that any remedies may create a new set of challenges. Others said humans’ uses and abuses of digital technologies are causing societal harms that are not likely to be overcome.

The following comments were selected from among all responses, regardless of an expert’s answer to this canvassing’s main question about the impact of people’s uses of technology. Some of these remarks of concern happen to also include comments about innovations that may emerge. Concerns are organized under four subthemes: Something is rotten in the state of technology; technology use often disconnects or hollows out a community; society needs to catch up and better address the threats and opportunities of tech; and despite current trends, there is reason to hope for better days.

The chapter begins with some overview insights:

Larry Masinter , internet pioneer, formerly with Adobe, AT&T Labs and Xerox PARC, who helped create internet and web standards with IETF and W3C, said, “Technology and social innovation intended to overcome the negatives of the digital age will likely cause additional negative consequences. Examples include: the decentralized web, end-to-end encryption, AI and machine learning, social media.”

James Mickens , associate professor of computer science at Harvard University, formerly with Microsoft, commented, “Technology will obviously result in ‘civic innovation.’ The real question is whether the ‘innovation’ will result in better societal outcomes. For example, the gig economy is enabled by technology; technology finds buyers for workers and their services. However, given the choice between an economy with many gig workers and an economy with an equivalent number of traditional middle-class jobs, I think that most people would prefer the latter.”

Michael Aisenberg , chair, ABA Information Security Committee, wrote, “Misappreciation of limits and genesis of, e.g., AI/machine learning will produce widely disparate results in deployment of tech innovations. Some will be dramatically beneficial; some may enable abuse of law enforcement, economic systems and other fundamental civic institutions and lead to exacerbation of gaps between tech controllers/users and underserved/under- or mis-skilled populations (‘digital divide’) in what may be a significant (embed limitations on career/economic advancement) or even life-threatening (de facto health care or health procedure rationing) manner.”

The problem is that we are becoming more and more dependent on machines and hence more susceptible to bugs and system failures. Yaakov J. Stein

Peter Lunenfeld , a professor of design, media arts and digital humanities at the University of California, Los Angeles, and author of “Tales of the Computer as Culture Machine,” predicted, “We will use technology to solve the problems the use of technology creates, but the new fixes will bring new issues. Every design solution creates a new design problem, and so it is with the ways we have built our global networks. Highly technological societies have to be iterative if they hope to compete, and I think that societies that have experienced democracy will move to curb the slide to authoritarianism that social media has accelerated. Those curbs will bring about their own unintended consequences, however, which will start the cycle anew.”

Yaakov J. Stein , chief technology officer of RAD Data Communications, based in Israel, responded, “The problem with AI and machine learning is not the sci-fi scenario of AI taking over the world and not needing inferior humans. The problem is that we are becoming more and more dependent on machines and hence more susceptible to bugs and system failures. This is hardly a new phenomenon – once a major part of schooling was devoted to, e.g., penmanship and mental arithmetic, which have been superseded by technical means. But with the tremendous growth in the amount of information, education is more focused on how to retrieve required information rather than remembering things, resulting not only in less actual storage but less depth of knowledge and the lack of ability to make connections between disparate bits of information, which is the basis of creativity. However, in the past humankind has always developed a more-advanced technology to overcome limitations of whatever technology was current, and there is no reason to believe that it will be different this time.”

A vice president for research and economic development wrote, “The problems we see now are caused by technology, and any new technological fixes we create will inevitably cause NEW social and political problems. Attempts to police the web will cause freedom of speech conflicts, for example.”

Something is rotten in the state of technology

A large share of these experts say among the leading concerns about today’s technology platforms are the ways in which they are exploited by bad actors who spread misinformation; and the privacy issues arising out of the business model behind the systems.

Misinformation – pervasive, potent, problematic

Numerous experts described misinformation and fake news as a serious issue in digital spaces. They expressed concern over how users will sort through fact and fiction in the coming decade.

Stephanie Fierman , partner, Futureproof Strategies, said, “I believe technology will meaningfully accelerate social and civic innovation. It’s cheap, fast and able to reach huge audiences. But as long as false information is enabled by very large websites, such social and civic innovators will be shadow boxing with people, governments, organizations purposely countering truthful content with lies.”

Sam Lehman-Wilzig , a professor of communications at Bar-Ilan University specializing in Israeli politics and the impact of technological evolution, wrote, “The biggest advance will be the use of artificial intelligence to fight disinformation, deepfakes and the like. There will be an AI ‘arms race’ between those spreading disinformation and those fighting/preventing it. Overall, I see the latter gaining the upper hand.”

Greg Shatan , a lawyer with Moses & Singer LLP and self-described “internet governance wonk,” predicted, “I see success, enabled by technology, as likely. I think it will take technology to make technology more useful and more meaningful. Many of us pride ourselves on having a ‘BS-meter,’ where we believe we can tell honestly delivered information from fake news and disinformation. The instinctual BS-meter is not enough. The next version of the ‘BS-meter’ will need to be technologically based. The tricks of misinformation have far outstripped the ability of people to reliably tell whether they are receiving BS or not – not to mention that it requires a constant state of vigilance that’s exhausting to maintain. I think that the ability and usefulness of the web to enable positive grassroots civic communication will be harnessed, moving beyond mailing lists and fairly static one-way websites. Could there be ‘Slack for Community Self-Governance?’ If not that platform, perhaps something new and aimed specifically at these tasks and needs.”

Oscar Gandy , a professor emeritus of communication at the University of Pennsylvania, said, “Corporate actors will make use of technology to weaken the possibility for improvements in social and civic relationships. I am particularly concerned about the use of technology in the communications realm in order to increase the power of strategic or manipulative communications to shape the engagement of members of the public with key actors within a variety of governance relationships.”

An expert in the ethics of autonomous systems based in Europe responded, “Fake news is more and more used to manipulate a person’s opinion. This war of information is becoming so important that it can influence democracy and the opinion of people before the vote in an election for instance. Some AI tools can be developed to automatically recognize fake news, but such tools can be used in turn in the same manner to enhance the belief in some false information.”

A research leader for a U.S. federal agency wrote, “At this point in time, I don’t know how we will reduce the spread of misinformation (unknowing/individual-level) and disinformation (nefarious/group-level), but I hope that we can.”

A retired information science professional commented, “Dream on, if you think that you can equate positive change with everybody yelling and those with the most clout (i.e., power and money) using their power to see their agendas succeed. Minority views will always be that, a minority. At present and in the near future the elites manipulate and control.”

A research scientist for a major technology company whose expertise is technology design said, “We have already begun to see increased protections around personal privacy. At present, it is less clear how we might avoid the deliberate misuse of news or news-like content to manipulate political opinions or outcomes, but this does not seem impossible. The trick will be avoiding government censorship and maintaining a rich, vigorous exchange of opinions.”

Privacy issues will continue to be a hot button topic

Multiple experts see a growing need for privacy to be addressed in online spaces.

Ayden Férdeline , technology policy fellow at the Mozilla Foundation, responded, “Imagine if everyone on our planet was naked, without any clear options for obtaining privacy technology (clothing). It would not make sense to ask people what they’d pay or trade to get this technology. This is a ‘build it and they will come’ kind of scenario. We’re now on the verge, as a society, of appropriately recognizing the need to respect privacy in our Web 2.0 world, and we are designing tools and rules accordingly. Back in 1992, had you asked people if they’d want a free and open internet, or a graphical browser with a walled garden of content, most would have said they prefer AOL. What society needed was not AOL but something different. We are in a similar situation now with privacy; we’re finally starting to grasp its necessity and importance.”

We’re now on the verge, as a society, of appropriately recognizing the need to respect privacy in our Web 2.0 world, and we are designing tools and rules accordingly. Ayden Férdeline

Graham Norris , a business psychologist with expertise in the future of work, said, “Privacy no longer exists, and yet the concept of privacy still dominates social-policy debates. The real issue is autonomy of the individual. I should own my digital identity, the online expression of myself, not the corporations and governments that collect my interactions in order to channel my behaviour. Approaches to questions of ownership of digital identity cannot shift until the realization occurs that autonomy is the central question, not privacy. Nothing currently visible suggests that shift will take place.”

Eduardo Villanueva-Mansilla , an associate professor of communications at Pontificia Universidad Catolica, Peru, and editor of the Journal of Community Informatics, wrote, “I’m trying to be optimistic, by leaving some room to innovative initiatives from civic society actors. However, I don’t see this as necessarily happening; the pressure from global firms will probably too much to deal with.”

An international policy adviser on the internet and development based in Africa commented, “Technology is creating and will continue to evolve and increase the impact of social and civic innovation. With technology we will see new accountability tools and platforms to raise voices to counter societal ills, be it in leadership, business and other faculties. We must however be careful so that these innovations themselves are not used to negatively impact end users, such issues like privacy and use of data must be taken on in a way that users are protected and not exposed to cybercrime and data breaches that so often occur now.”

Jamie Grady , a business leader, wrote, “As technology companies become more scrutinized by the media and government, changes – particularly in privacy rights – will change. People will learn of these changes through social media as they do now.”

Technology use often disconnects or hollows out community

Some respondents commented on rising problems with a loss of community and the need for more-organic, in-person, human-to-human connection and the impact of digital distancing.

Jonathan Grudin , principal researcher at Microsoft, commented, “Social and civic activity will continue to change in response to technology use, but will it change its trajectory? Realignments following the Industrial Revolution resulted from the formation of new face-to-face communities, including union chapters, community service groups such as Rotary Club and League of Women Voters, church groups, bridge clubs, bowling leagues and so on. Our species is designed to thrive in modest-sized collocated communities, where everyone plays a valued part. Most primates become vulnerable and anxious when not surrounded by their band or troop. Digital media are eroding a sense of community everywhere we look. Can our fundamental human need for close community be restored or will we become more isolated, anxious and susceptible to manipulation?”

Rebecca Theobald , an assistant research professor at the University of Colorado, Colorado Springs, said, “Technology seems to be driving people apart, which would lead to fewer connections in society.”

The program director of a university-based informatics institute said, “There is still a widening gap between rural and urban as well as digital ‘haves’ and ‘have nots.’ As well, the ability to interact in a forum in which all members of society have a voice is diminishing as those with technology move faster in the digital forums than the non-tech segment of the population that use non-digital discourse (interpersonal). The idea of social fabric in a neighborhood and neighborly interactions is diminishing. Most people want innovation – it is the speed of change that creates divisions.”

An infrastructure architect and internet pioneer wrote, “The kind of social innovation required to resolve the problems caused by our current technologies relies on a movement back toward individual responsibility and a specific willingness to engage in community. As both of these work against the aims of the corporate and political elite as they exist today, there is little likelihood these kinds of social innovations are going to take place. The family and church, for instance, which must be the core institutions in any rebuilding of a culture that can teach the kind of personal responsibility required, were both hollowed out in the last few decades. The remaining outward structures are being destroyed. There is little hope either families or churches will recover without a major societal event of some sort, and it will likely take at least one generation for them to rebuild. The church could take on the task of helping rebuild families, but it is too captured in attempts to grow ever larger, and consume or ape our strongly individualistic culture, rather than standing against it.”

Angela Campbell , a professor of law and co-director of the Institute for Public Representation at Georgetown University, responded, “I think there will be efforts to address the social and civic impacts of technology but they may not be sufficient. In particular, I am concerned about the impact of overuse or over-reliance on technology with respect to children and teens. I am concerned about the safety of children online, not just from predators but from peers (bullying). Overuse may also contribute to physical maladies such as obesity, bad posture, eye problems, ADHD, insufficient sleep and even addiction. While technology can help to educate older children (not preschoolers who need to interact with humans and objects), it needs to be selected [and] used carefully and should not subject children to commercialism or invade their privacy. My other major concerns are job loss and discrimination. It seems inevitable that many jobs will be eliminated by technology, and while technologies may generate new jobs, I suspect there will be fewer jobs, and those that remain will require certain skills. It will be important, and difficult, to ensure that everyone is able to have employment and to make enough to live at a reasonable level. As competition for jobs increases, I am also worried about how big data allows hidden discrimination in education, health and employment.”

A researcher based in North America predicted a reining in of the digital in favor of the personal: “Between email and phones, I think we’re close to peak screen time, a waste of time, and it’s ruining our eyes. Just as we have forsaken our landlines, stopped writing letters, don’t answer our cellphones, a concept of an average daily digital budget will develop, just as we have a concept of average daily caloric intake. We’ll have warning labels that rate content against recommended daily allowances of different types of content that have been tested to be good for our mental health and socialization, moderately good, bad, and awful – the bacon of digital media. And people who engage too much will be in rehab, denied child custody and unemployable. Communities, residences and vacation areas will promote digital-free, mindfulness zones – just as they have quiet cars on the train.”

Society needs to catch up and better address the threats and opportunities of tech

Some of these experts said that the accelerating technological change of the digital age is making it difficult for humans to keep up and respond to emerging challenges.

A chair of political science based in the American South commented, “Technology always creates two new problems for every one it solves. At some point, humans’ cognitive and cooperative capacities – largely hard-wired into their brains by millennia of evolution – can’t keep up. Human technology probably overran human coping mechanisms sometime in the later 19th century. The rest is history.”

There is a gap between the rate at which technology develops and the rate at which society develops. We need to take care not to fall into that gap. Louisa Heinrich

Larry Rosen , a professor emeritus of psychology at California State University, Dominguez Hills, known as an international expert on the psychology of technology, wrote, “I would like to believe that we, as citizens, will aid in innovation. Smart people are already working on many social issues, but the problem is that while society is slow to move, tech moves at lightning speed. I worry that solutions will come after the tech has either been integrated or rejected.”

Louisa Heinrich , a futurist and consultant expert in data and the Internet of Things, said, “There is a gap between the rate at which technology develops and the rate at which society develops. We need to take care not to fall into that gap. I hope we will see a shift in governance toward framework-based regulation, which will help mitigate the gap between the pace of change in technology and that in government. At the very least, we need to understand the ways in which technology can extend or undermine the rules and guidelines we set for our businesses, workplaces, public spaces and interactions. To name just one common example, recruitment professionals routinely turn to Facebook as a source of information on prospective employees. This arguably violates a number of regulations designed to protect people from being denied work based on personal details not relevant to that work. How do we unravel this conundrum, bearing in mind that there will always be another social network, another digital source to mine for information about people? Taken from another angle, there is a significant gap between what users understand about certain bits of technology and the risks they take using them. How can we educate people about these risks in a way that encourages participation and co-creation, rather than passivity? As the so-called Gen Z comes of age, we will see a whole generation of young adults who are politically engaged at a level not seen in several generations, who are also native users of technology tools. This could bring about a positive revolution in the way technology is used to facilitate civic engagement and mutually empower and assist citizens and government. Technology provides us with powerful tools that can help us advance socially and civically, but these tools need to be thoughtfully and carefully put to use – when we encode barriers and biases into the applications that people need to use in daily life, whether intentionally or no, we may exclude whole segments of society from experiencing positive outcomes. We are living through a time of rapid and radical change – as always, the early stages feel uncomfortable and chaotic. But we can already see the same tools that have been used to mislead citizens being used to educate, organise, motivate and empower them. What’s needed is a collective desire to prioritise and incentivise this. New Zealand is leading the way with the world’s first ‘well-being’ budget.”

Bulbul Gupta , founding adviser at Socos Labs, a think tank designing artificial intelligence to maximize human potential, responded, “Until government policies, regulators, can keep up with the speed of technology and AI, there is an inherent imbalance of power between technology’s potential to contribute to social and civic innovation and its execution in being used this way. If technology and AI can make decisions about people in milliseconds that can prevent their full social or civic engagement, the incentive structures to be used toward mitigating the problems of the digital age cannot then be solved by technology.”

Gene Policinski , a journalist and First Amendment law expert at the Freedom Forum Institute, observed, “We forget how new the ‘tech revolution’ really is. As we move forward in the next decade, the public’s awareness of the possibilities inherent in social and civic innovation, the creativity of the tech world working with the public sector and public acceptance of new methods of participation in democratic processes will begin to drown out and eventually will surpass the initial problems and missteps.”

Gabriel Kahn , former bureau chief for The Wall Street Journal, now a professor of journalism researching innovation economics in emerging media at the University of Southern California, wrote, “We are not facing a ‘Terminator’-like scenario. Nor are we facing a tech-driven social utopia. Humans are catching up and understanding the pernicious impact of technology and how to mitigate it.”

Kathee Brewer , director of content at CANN Media Group, predicted, “Much like society developed solutions to the challenges brought about by the Industrial Revolution, society will find solutions to the challenges of the Digital Revolution. Whether that will happen by 2030 is up for debate. Change occurs much more rapidly in the digital age than it did at the turn of the 20th century, and for society to solve its problems it must catch up to them first. AND people, including self-interested politicians, must be willing to change. Groups like the Mozilla Foundation already are working on solutions to invasions of privacy. That work will continue. The U.S. government probably won’t make any major changes to the digital elections framework until after the 2020 election, but changes will be made. Sadly, those changes probably will result from some nastiness that develops due to voters of all persuasions being unwilling to accept electoral results, whatever the results may be.”

Valerie Bock of VCB Consulting, former Technical Services Lead at Q2 Learning, responded, “I think our cultures are in the process of adapting to the power our technologies wield, and that we will have developed some communal wisdom around how to evaluate new ones. There are some challenges, but because ordinary citizens have become aware that images can be ‘photoshopped’ the awareness that video can be ‘deepfaked’ is more quickly spreading. Cultural norms as well as technologies will continue to evolve to help people to apply more informed critiques to the messages they are given.”

Bach Avezdjanov , a program officer with Columbia University’s Global Freedom of Expression project, said, “Technological development – being driven by the Silicon Valley theory of uncontrolled growth – will continue to outpace civic and social innovation. The latter needs to happen in tandem with technological innovation, but instead plays catch-up. This will not change in the future, unless political will to heavily regulate digital tools is introduced – an unlikely occurrence.”

A computing science professor emeritus from a top U.S. technological university commented, “Social/civic innovation will occur but most likely lag well behind technological innovation. For example, face-recognition technology will spread and be used by businesses at a faster pace than social and legal norms can develop to protect citizens from any negative effects of that technology. This technology will spread quickly, due to its various positives (increased efficiencies, conveniences and generation of profits in the marketplace) while its negatives will most likely not be countered effectively through thoughtful legislation. Past Supreme Court decisions (such as treating corporations as persons, WRT unlimited funding of political candidates, along with excessive privacy of PACs) have already undermined U.S. democracy. Current populist backlashes, against the corruption of the Trump government, may also undermine democracy, such as the proposed Elizabeth Warren tax, being not on profits, but upon passive wealth itself – a tax on non-revenue-producing illiquid assets (whose valuation is highly subjective), as in her statement to ‘tax the jewelry of the rich’ at 2% annually. Illiquid assets include great private libraries, great private collections of art, antiques, coins, etc. – constituting an assault on the private sector, that if successful, will weaken democracy by strengthening the confiscatory power of government. We could swing from current excesses of the right to future excesses of the left.”

Despite current trends, there is reason to hope for better days

Many of the experts in this canvassing see a complicated and difficult road ahead, but express hope for the future.

Cheryl B. Preston , an expert in internet law and professor at Brigham Young University Law School, said, “Innovation will bring risk. Change will bring pain. Learning will bring challenges. Potential profits will bring abuse. But, as was the decision of Eve in the Garden of Eden, we need to leave the comfortable to learn and improve. If we can, by more informed voting, reduce the corruption in governmental entities and control corporate abuse, we can overcome difficulties and advance as a society. These advances will ultimately bring improvement to individuals and families.”

John Carr , a leading global expert on young people’s use of digital technologies, a former vice president of MySpace, commented, “I know of no proof for the notion that more people simply knowing more stuff, even stuff that is certifiably factually accurate, will necessarily lead to better outcomes for societies. But I do harbour a hope that if, over time, we can establish the idea that there are places on the internet that are reliable sources of information, it will in the medium to longer term help enough people in enough countries to challenge local demagogues and liars, making it harder for the demagogues and liars to succeed, particularly in times of national crisis or in times when war might be on the visible horizon. I used to think that if the internet had been around another Hitler would be impossible. Recently I have had a wobble on that but my optimism ‘trumps’ that gloomy view.”

Mike Douglass , an independent developer, wrote, “There is a significant realization that a stampede to create connections between anonymous people and devices was a bad idea. It’s up to the technologists and – more importantly – those who want to make money out of technology – to come up with a more measured approach. There’s a reason why gentlemen obtained letter of introduction to other gentlemen – one shouldn’t trust some random individual turning up on your doorstep. We need the equivalent approach. I’ve no idea what new innovations might turn up. But if we don’t get the trust/privacy/security model right we’ll end up with more social media disasters.”

Hume Winzar , an associate professor and director of the business analytics undergraduate program at Macquarie University, Sydney, Australia, predicted, “With more hope than evidence, I’d like to think that reason will eventually overcome the extraordinary propaganda machines that are being built. When the educated upper-middle classes realise that the ‘system’ is no longer serving them, then legal and institutional changes will be necessary. That is, only when the managers who are driving the propaganda machine(s) start to feel that they, personally, are losing privacy, autonomy, money and their children’s future, then they will need to undermine the efforts of corporate owners and government bureaucrats and officials.”

Carolyn Heinrich , a professor of education and public policy at Vanderbilt University, said, “My hope (not belief) is that the ‘techlash’ will help to spur social and civic innovations that can combat the negative effects of our digitization of society. Oftentimes, I think the technology developers create their products with one ideal in mind of how they will be used, overlooking that technology can be adapted and used in unintended and harmful ways. We have found this in our study of educational technology in schools. The developers of digital tools envision them as being used in classrooms in ‘blended’ ways with live instructors who work with the students to help customize instruction to their needs. Unfortunately, more often than not, we have seen the digital tools used as substitutes for higher-quality, live instruction and have observed how that contributes to student disengagement from learning. We have also found some of the content lacking in cultural relevance and responsiveness. If left unchecked, this could be harmful for far larger numbers of students exposed to these digital instructional programs in all 50 states. But if we can spur vendors to improve the content, those improvements can also extend to large numbers of students. We have our work cut out for us!”

In the field I follow, artificial intelligence, the numbers of professionals who take seriously the problems that arise as a consequence of this technology are reassuring. Pamela McCorduck

Heywood Sloane , entrepreneur and banking and securities consultant, wrote, “I’m hopeful the it will be a positive contributor. It has the ability to alter the way we relate to our environment in ways that shrink the distances between people and help us exercise control over our personal and social spaces. We are making substantial progress, and 5G technology will accelerate that. On the flip side, we need to find mechanisms and processes to protect our data and ourselves. They need to be strong, economic and simple to deploy and use. That is going to be a challenge.”

Pamela McCorduck , writer, consultant and author of several books, including “Machines Who Think,” commented, “I am heartened by the number of organizations that have formed to enhance social and civic organization through technology. In the field I follow, artificial intelligence, the numbers of professionals who take seriously the problems that arise as a consequence of this technology are reassuring. Will they all succeed? Of course not. We will not get it right the first time. But eventually, I hope.”

Yoshihiko Nakamura , a professor of mechno-informatics at the University of Tokyo, observed, “The current information and communication technology loses diversity because it is still insufficient to enhance the affectivity or emotion side of societies. In this sense I can see the negative side of current technology to human society. However, I have a hope that we can invent uses of technology to enhance the weaker side and develop tomorrow’s technology. The focus should be on the education of society in the liberal arts.”

Ryan Sweeney , director of analytics at Ignite Social Media, commented, “In order to survive as a functioning society, we need social and civic innovation to match our use of technology. Jobs and job requirements are changing as a result of technology. Automation is increasing across a multitude of industries. Identifying how we protect citizens from these changes and help them adapt will be instrumental in building happiness and well-being.”

Miles Fidelman , founder, Center for Civic Networking and principal Protocol Technologies Group, responded, “We can see clear evidence that the internet is enabling new connections, across traditional boundaries – for the flow of information, culture and commerce. It is strengthening some traditional institutions (e.g., ties between geographically distributed family members) and weakening others (e.g., the press). Perhaps the most notable innovation is that of ad hoc, network-centric organizations – be they global project teams, or crisis response efforts. How much of this innovation will make things better, how much it will hurt us, remains an open question.”

A technology developer active in IETF said, “I hope mechanisms will evolve to exploit the advantages of new tech and mitigate the problems. I want to be optimistic, but I am far from confident.”

A renowned professor of sociology known for her research into online communications and digital literacies observed, “New groups expose the error of false equivalence and continue to challenge humans to evolve into our pre-frontal cortex. I guess I am optimistic because the downside is pretty terrible to imagine. It’s like E.O. Wilson said: ‘The real problem of humanity is the following: We have paleolithic emotions; medieval institutions; and god-like technology. And it is terrifically dangerous, and it is now approaching a point of crisis overall.’”

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Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic

a Department of Information Technology & Decision Sciences, Old Dominion University, Norfolk, VA, 23529, USA

Zuopeng (Justin) Zhang

b Department of Management, Coggin College of Business, University of North Florida, Jacksonville, FL 32224, USA

Various technology innovations and applications have been developed to fight the coronavirus pandemic. The pandemic also has implications for the design, development, and use of technologies. There is an urgent need for a greater understanding of what roles information systems and technology researchers can play in this global pandemic. This paper examines emerging technologies used to mitigate the threats of COVID-19 and relevant challenges related to technology design, development, and use. It also provides insights and suggestions into how information systems and technology scholars can help fight the COVID-19 pandemic. This paper helps promote future research and technology development to produce better solutions for tackling the COVID-19 pandemic and future pandemics.

1. Introduction

The COVID-19 pandemic has caused an immense impact on hospital systems, businesses, schools, and the economy. Telemedicine, telework, and online education become essential to help society slow down the spread of the coronavirus ( Chavez & Kounang, 2020 ; Loh & Fishbane, 2020 ; Young, 2020 ). The pandemic has generated a rapid demand for efforts to use innovative technologies to cope with damage from COVID-19 on our life ( O’Leary, 2020 ).

The pandemic has not only raised opportunities to advance technology-based solutions but also provided a rare opportunity to study the research and practice of technology, including information management, work practices, and design and use of technologies ( Sein, 2020 ). The quick transition to telehealth, telework, and online education in response to the coronavirus threat is a reminder that digital technology brings many benefits and can play an essential role in managing and reducing the risks caused by the lockdown during the pandemic and even after the pandemic ( Richter, 2020 ). It is well known that information systems and information technology (IS/IT) play an important role in healthcare, clinical decision support, emergency/crisis response, and risk management ( Angst & Agarwal, 2009 ; Ben-Assuli & Padman, 2020 ; Chen, Sharman, Chakravarti, Rao, & Upadhyaya, 2008 ; Thompson, Whitaker, Kohli, & Jones, 2019 ). Many IS/IT professionals are working in various ways to help fight the pandemic, including developing products to combat the virus, tracking and predicting its spread, and protecting hospitals from cyberattacks ( Mingis, 2020 ). Information systems and technology scholars should contribute to this global effort to fight the COVID-19 and future pandemics ( Ågerfalk, Conboy, & Myers, 2020 ) by leveraging their previous experience and knowledge on responding to crises, decision making, remote working, managing virtual teams, analyzing large data sets, etc. There is currently a shortage of research contributions in the areas of information systems (IS) to help fight the COVID-19.

The pandemic has implications for the design, development, and use of information systems and technologies ( Sein, 2020 ). Information systems and technology researchers and practitioners can help conduct an analysis of the COVID-19 pandemic data and engage in potential emerging research topics, such as facilitating work while social distancing, contactless commerce, face recognition when wearing masks or in other crises, COVID-19 apps in terms of privacy, crowdsourcing, donating data, and tracking cases, robotics and their impact on organizations, monitoring vulnerable vs. non-vulnerable for their impact on work, changing patterns of supply and demand for fragile supply chains and autonomic systems, virtual communication tools, online education breakthroughs, and separation of work and private life ( O’Leary, 2020 ). Rai (2020) also identified some opportunities for IS research to contribute toward building resilience to pandemics and extreme events including (i) redesigning the public health system from reactive to proactive through the use of real-time surveillance systems and contact tracing tools to stem transmission, (ii) transforming organizations through enhancing crisis-driven agility and reducing crisis-revealed fragility, and (iii) empowering individuals and communities through adapting, coping, and stemming the infodemic. Dwivedi et al. (2020) present an assessment of critical challenges of COVID-19 through an information system and technological perspective and offer insights for research and recommendations studying the impact of COVID-19 on information management research and practice in transforming education, work, and life.

To reduce the overlap with O’Leary (2020) and Rai (2020) , this paper primarily focuses on technology integration from the data, system, and people perspectives to discuss how information systems and technology scholars could contribute knowledge and insights to help fight the pandemic. As information systems and technologies are becoming foundational to society, information systems and technology scholars are in an excellent position to leverage their experience and knowledge with information systems and various technologies to improve existing systems and technology practice and help the society become digitally resilient to future large-scale disruptions.

2. Existing IT solutions

This paper uses the data-people-system framework to examine technology solutions to mitigate the impact of the COVID-19 pandemic. The data-people-system framework by Bardhan, Chen, and Karahanna (2020) demonstrates a multidisciplinary roadmap for controlling and managing chronic diseases by focusing on the following three components: (1) extraction, integration, and delivery of health data; (2) interoperability of systems; and (3) guidelines and interface to guide people’s behavior. It must be noted that the original data-people-system framework was proposed for chronic disease management, which needs further development to be proactive and take account of the pandemic context.

The COVID-19 pandemic has revealed the urgent need to redesign the public health system from reactive to proactive and develop innovations that will provide real-time information for proactive decision-making at the local, state, and national levels of public health systems ( Rai, 2020 ). COVID-19 is different from chronic diseases as it is highly contagious, can pass from people to people, and has a high mortality rate. Additionally, as COVID-19 is a new disease, scientific understanding of the virus that causes it, medical response, and actions by governments and organizations continue to evolve. The impact of COVID-19 on people and society is changing daily in ways that would have been unthinkable. As the current pandemic situation and its consequence continue to remain fluid, combating the COVID-19 pandemic requires strong coordination of various resources.

In response to the threats and risks posed by COVID-19, this paper adopts the data-people-system framework to examine the existing technology solutions for fighting against the COVID-19 pandemic and identify their challenges and potential opportunities for information systems and technology researchers. In particular, we have conducted an extensive search using academic databases and web search engines with a variety of queries related to technology, coronavirus, and COVID-19, synthesizing the related discussions in newspapers, news websites, blogs, white papers, practitioner websites, grey literature or academic literature to help understand the existing information systems and technology solutions and the roles that they could play in this challenging time of the pandemic.

Some new technology applications such as mobile COVID-19 contact tracing apps and chatbots have been recently developed to fight this pandemic. Applying these technologies can help reduce the impact of the coronavirus pandemic on people, organizations, and society. Effective and innovative use of emerging technologies can help identify community spread of the coronavirus, monitor the condition of the infected patients, improve the treatment of COVID-19 infected patients, and help develop medical treatments and vaccines ( Johnstone, 2020 ). This section evaluates these technology applications based on the data-people-system framework by Bardhan et al. (2020) .

Technologies powered by artificial intelligence (AI) including machine learning, image recognition, and deep learning algorithms can be used for early detection and diagnosis of the infection, more rapid drug discovery for developing new treatments ( Brohi, Jhanjhi, Brohi, & Brohi, 2020 ). A few companies also repurposed existing AI systems that were initially designed for other areas to assist in social distancing enforcement and contract tracing ( Sipior, 2020 ).

3D Printing Technology can help make face masks and other Personal Protective Equipment (PPE) for healthcare workers. Markforged has partnered with Neurophotometrics to produce 3D printed rayon wrapped nasopharyngeal (NP) swabs for COVID-19 testing. The swabs take less than three minutes to make, can be much quicker at collecting viral particles ( Markforged, 2020 ).

Big Data Analytics can be used to identify people that need quarantine based on their travel history, predict the COVID-19 curve, speed up the development of antiviral drugs and vaccines, and advance the understanding of the COVID-19 spread across both time and space. In Taiwan, big data analytics has been successfully applied to help identify COVID-19 cases and generate real-time alerts through analyzing clinical visits, travel history, and clinical symptoms ( Wang, Ng, & Brook, 2020 ; Wang, Zha, et al., 2020 ; Watson, Ives, & Piccoli, 2020 ).

HPC infrastructures and supercomputers are needed to address complex scientific problems and process big datasets in shorter time frames in order to develop new drugs and vaccines. The COVID-19 High-Performance Computing Consortium was launched to leverage the computing resources and supercomputers in the US. The consortium includes 16 public and private entities such as the US Department of Energy (DoE), IBM, and other academic and industry leaders ( Woo, 2020 ).

Mobile apps via smartphones and video-conferencing tools can be used to track the movements of individuals, alert people from visiting COVID-19 hotspots, help doctors to diagnose patients through video services and telemedicine/telehealth, support people with online shopping, e-learning, online meetings, and telework ( Marr B., 2020 ). Various phone and network-powered apps have been developed to help healthcare workers and ordinary people in this crisis. For example, the U.S. National Science Foundation funded an award to support researchers at Princeton University in developing a system to deploy a firmware update to mobile phones to provide proximity tracking ability for health officials. To preserve users’ privacy, the key to the proximity data would be stored on the phone itself and could only be unlocked when the phone’s owner voluntarily provided it to health officials. Suppose a person tests positive for a disease such as COVID-19. In that case, health officials could then use the system to automatically identify all other cellphone users who were within a certain distance of the infected person for a certain time. The time and distance could be determined by health officials based on knowledge of the disease. Healthcare departments can contact those potentially infected people, advise them of the exposure, and instruct them to get tested for the disease and self-quarantine as needed ( WHO, 2020 ).

Robots have been applied to fight the coronavirus outbreak. For example, hospitals use robots as support systems to deliver food and medicine, disinfect rooms, and other hotspots without direct human interaction with patients. A CNN news report shows that doctors in Seattle have used a telepresence robot to treat the first confirmed patient who tests positive for coronavirus in the United States ( Chavez & Kounang, 2020 ). Drones also are used to deliver medical supplies, patrol public areas, track non-compliance to quarantine mandates, and so on ( Marr B., 2020 ; Marr N., 2020 ).

The Internet of Things (IoT) can be used for the surveillance of people infected by coronavirus to reduce the spread of the coronavirus ( Kumar, Kumar, & Shah, 2020 ). IoT consists of several functional components: data collection, transfer, analytics, and storage. IoT sensors installed on mobile phones, robots, or health monitors can be used to collect data. Next, sensor data would be sent to the cloud server for processing, analytics, and decision-making. As an example, IoT helps check whether patients follow quarantine requirements. IoT can also be used to take the remote patients’ temperatures and then transmit the data through mobile devices to the doctors to monitor, track, and alert while reducing the chance for coronavirus inflections ( He, 2020 ). Additional roles of IoT technologies include the use of smart wearable devices in response to COVID-19 in early diagnosis, quarantine time, and after recovery ( Nasajpour et al., 2020 ).

Blockchain is a distributed ledger technology that records online transactions. It is regulated through a consensus mechanism and is secured with cryptography ( Chong, Lim, Hua, Zheng, & Tan, 2019 ). As an example, a smartphone app that leverages blockchain technology and AI was developed to help fight the coronavirus pandemic. Blockchain technology enables the app to give each participant a "digital identity" controlled by a private key that brings access to a digital version of paper certificates issued by the government. These allow the confirmed healthy people to leave home to buy food or to work ( Sinclair, 2020 ). Blockchain has also been used to prevent the information from being manipulated by unauthorized parties. During the outbreak, a Chinese payment processor and financial services company used blockchain technology to monitor the process of processing claims and making payouts in a more secure and trustworthy way ( News Staff, 2020 ). Blockchain technology has been applied to resolve the tension and trust issues between maintaining privacy and addressing public health needs, such as tracking infected patients in the fight against COVID-19 ( Khurshid, 2020 ).

All the above technologies require the integration of data, people, and systems. Based on their primary focus and original design intention for use in practice, we broadly classify them into three categories. The data-centric technologies for combating COVID-19 include machine learning/deep learning, big data analytics, and HPC infrastructure. The people-centric technologies include robots and 3D printing technology; they are used to serve patients better and protect healthy people from infections with the support of specific systems. The system-centric technologies include digital contact tracing apps, the Internet of Things, and Blockchain; they are developed based on system concepts to monitor patients and prevent healthy people from contracting coronavirus. Some of these technologies are interrelated and may transcend multiple categories as they are being used in dealing with the pandemic, depending on how creative people are using them in varying contexts. For example, big data analytics that identify people who need quarantine could have system-centric or people-centric aspects depending on the specific purposes and use by different government agencies, health authorities, hospitals, and organizations. Table 1 summarizes the three categories of technologies and their required support from data, people, and systems.

Summary of technology solutions for COVID-19.

3. Challenges

The COVID-19 pandemic has exposed the weaknesses of existing public health systems. The use of technologies to combat the pandemic raises challenges in many aspects. The specific nature of the COVID-19 pandemic requires strong coordination of connected data, people, and systems ( Bardhan et al., 2020 ) to facilitate worldwide collaboration in fighting against it. Traditionally, public health agencies and healthcare stakeholders have not used the same systems, data formats, or standards, hampering the ability to identify trends and develop interventions against the pandemic. Public health researchers, epidemiologists, and government officials need to be connected via integrated systems with connected data to understand the evolving pandemic better and make collective decisions on addressing this crisis. As people play a crucial role in this fight against the COVID-19, it is essential to connect, coordinate, and support various stakeholders through innovative and integrated technologies.

3.1. Connecting systems to integrate technologies

Emerging technologies including the IoT, big-data analytics, AI, and blockchain can be integrated to develop smart strategies for addressing immediate challenges caused by the coronavirus. For example, Facebook has used artificial intelligence and big data technologies to tap into satellite imagery and census data to generate maps that display population density, demographics, and travel patterns in order to help decide where to send supplies or how to reduce the spread ( Holt, 2020 ). Big data analysis of geographic information systems (GIS) and IoT sensor data collected from infected patients can assist epidemiologists to trace patient zero and help identify close contacts of the infected patients ( He, 2020 ). The U.S. National Science Foundation recently funded a RAPID award that explores the capabilities and potential of integrating social media big data, geospatial data, and AI technologies to enable and transform spatial epidemiology research and risk communication. The emerging convergence of blockchain, the IoT, and AI holds great promise for addressing the issues of trust and security in public health ( Gurgu, Andronie, Andronie, & Dijmarescu, 2019 ; Singh, Rathore, & Park, 2020 ). For example, medical device data and non-personal sensor data collected by IoT can be stored and shared on the blockchains. Patients’ personal data can still be stored in the hospitals’ enterprise systems due to privacy regulations such as the GDPR ( Agbo, Mahmoud, & Eklund, 2019 ; Onik, Aich, Yang, Kim, & Kim, 2019 ). AI and big data technologies can be leveraged to analyze and visualize both on-chain and off-chain data and provide near real-time analytics and recommendations to relevant stakeholders through customized dashboards.

Currently, most systems and apps that have been used to deal with the pandemic are poorly inter-connected since they are developed by different government agencies, health authorities, and organizations. There is a lack of systematic frameworks and tools to accomplish systematic integration across various technologies in the global response against pandemic challenges.

To integrate these different technologies, guidelines and systematic efforts are required to coordinate the collection of large amounts of quality data related to coronavirus cases. The design of effective big data analytics and AI algorithms requires public health departments and hospitals to provide a large amount of reliable and high-quality data. Due to a lack of standards, the integration of multiple data sources for promoting interoperability is challenging. Some data sources may be well structured, while others are not ( Pham, Nguyen, Huynh-The, Hwang, & Pathirana, 2020 ). There is also a need to generate standardized protocols to facilitate communication across systems without compromising data security. Governments, leading tech firms, health organizations, and other relevant stakeholders need to collaborate efficiently and effectively to define the standard, protocols, data formats and types, etc.

Information systems and technology scholars have been examining system integration in enterprise or organizational environments over the past several decades ( Henningsson, Yetton, & Wynne, 2018 ; Ravichandran & Rai, 2000 ; Xu, 2011 ). Information systems and technology scholars also studied the role of information systems in crisis, disaster, and emergency response ( Chen et al., 2008 ; Pan, Pan, & Leidner, 2012 ; Valecha, Rao, Upadhyaya, & Sharman, 2019 ). Information systems and technology researchers should take the opportunity to offer their expertise in system integration and experience with emergency or crisis response systems to provide recommendations and strategies to help developers with various systems and technology integration efforts.

3.2. Connecting data to share best practices

As the World Health Organization (2020) suggests, new collaboration and knowledge sharing are needed to deliver targeted solutions through a coordinated effort to support countries facing stages of this epidemic in different ways and at different times. Faced with a global pandemic, countries need to work together to share data, information, resources, effective practices, and strategies to combat the coronavirus. In addition, global collaboration among relevant stakeholders between organizations and governments will be crucial to coordinating the sharing and use of data and knowledge to solve the problems we encountered during this pandemic. For example, China took extraordinary measures for the shutdown of Wuhan, a large city with millions of people, to control the spread of the coronavirus ( Lin et al., 2020 ). Useful experience and lessons related to its efficacy as a containment measure could be valuable for other countries who are considering similar measures. Data integration and knowledge management (KM) technologies such as web portals, knowledge repositories, and online communities of practice can be used to empower data connections to leverage resources more effectively and efficiently at a lower cost ( Bardhan et al., 2020 ; Pan, Cui, & Qian, 2020 ).

Knowledge-based systems such as expert systems and intelligent decision technologies have been used to support health workers in detecting and diagnosing patients, and providing decision-making support for relevant healthcare stakeholders and decision-makers in a pandemic crisis ( O’Leary, 2020 ; Rehfuess et al., 2019 ). Data mining and visualization technologies have been used to discover and visualize knowledge evolution across time and locations as the coronavirus outbreak continues to evolve. Online health communities have been established to help healthcare workers, patients, and other stakeholders learn about COVID-19, symptoms, and the effectiveness of treatments ( Yan & Tan, 2014 ; Ziebland et al., 2004 ). However, these systems often operate in a silo, and the data, information, and knowledge stored in their systems are not widely shared. To allow various systems and stakeholders in different communities of practice to share knowledge within and across their individual areas, we need to create an environment to encourage people across countries to share knowledge instead of keeping or holding the knowledge. In the context of a coronavirus outbreak, strategies could be developed to assess the quality of the knowledge and help systems break down silos that hinder communication and sharing data more efficiently.

Besides, behavioral issues need to be addressed to facilitate the sharing of data and best practices among stakeholders. Over the years, there have been a number of calls for information systems and technology researchers to consider the unintended or negative consequences of technologies ( Chiasson, Davidson, & Winter, 2018 ). IT professionals have been rushing to build apps, services, and systems for contact tracing, tracking, and quarantine monitoring. Some of these technologies are lightweight for short-term use, while others are pervasive and invasive ( O’Neill, Ryan-Mosley, & Johnson, 2020 ). For example, many researchers have advocated the use of digital contact tracing and health code apps ( Oxford Analytica, 2020 ) to reduce the spread of the disease. Some people are concerned that short-term fixes such as monitoring of infected people via an app could lead to a permanent state of surveillance by the government ( Lin & Martin, 2020 ). Digital contact tracing can be effective but is controversial because it could have disastrous consequences if not implemented with proper privacy checks and encryption ( Huang, Sun, & Sui, 2020 ). For example, some experts are questioning how anonymous the data is and whether it can be easily de-anonymized to identify or infer the personal identity of infected persons ( Lee & Roberts, 2020 ). Healthy authorities may misuse or abuse the data they collected from digital tracing mobile apps for long-term and other purposes. Many people are concerned about whether these coronavirus-fighting apps are secure to use, how these apps will preserve privacy, and what policies are needed to prevent the abuse ( O’Neill et al., 2020 ). These concerns are likely to undermine public trust and affect people’s adoption of emerging technologies. There is also a need for further research to investigate security, privacy, and ethics issues related to technologies developed for fighting this pandemic.

Knowing about coronavirus exposures is important for containing the spread of COVID-19. Governments around the world are introducing technologies such as mobile apps to help health officials trace contacts of people newly infected with the coronavirus. These mobile apps work by recording whom a person comes close to—then alerting those people if a person contracts COVID-19. Out of precaution to protect people’s privacy and reduce people’s concern on increased surveillance, Australia made it illegal for non-health officials to access data collected on smartphone software to trace the spread of the coronavirus. The European Data Protection Board (EDPB) has published guidance for the use of location data and contact tracing tools in order to mitigate privacy and security concerns. Apple and Google disclosed a series of changes including stronger privacy protections and accuracy to their COVID-19 contact tracing initiative.

On the other hand, some researchers think that it is justified to temporarily relax privacy measures for such technologies in the hopes of possibly saving lives, serving the public good, and protecting public health under pandemic circumstances. Many people have been engaged in self-disclosure on social media to share personal information such as health status and preventive behaviors (e.g., wearing masks and buying sanitizing products) because sharing such information contributes to the public good ( Nabity-Grover, Cheung, & Thatcher, 2020 ). Some researchers hold that privacy concerns should not decrease the usefulness of technology to protect public health ( Cho, Ippolito, & Yu, 2020 ). They do not think such technologies were designed to make a permanent change to society ( Ferretti et al., 2020 ). The lack of a consensus on privacy protection in technologies against COVID-19 indicates a strong need for establishing best practice guidelines to reassure citizens on data collection ( Fahey & Hino, 2020 ).

Public trust and confidence are necessary to people’s adoption of various technologies including sharing their data to address the challenges caused by this pandemic ( Ferretti et al., 2020 ). Currently, the adoption of digital contact tracing apps is voluntary in western countries. It has been recognized that these issues cause more controversy in Western countries with a culture of individualism such as Europe and the U.S. than in countries with a culture of collectivism. However, at least 60 percent of people with smartphones would need to opt-in for such apps to be effective ( Scott, 2020 ). How to incentivize mass user adoption of these apps is a challenge. In the context of this coronavirus pandemic with a lot of loss of life, information systems and technology scholars can help evaluate the use of digital data and technologies including AI-related algorithms in a responsible manner, provide oversight for user-related data, develop ways to incentivize users to share relevant data as needed, help develop mechanisms to ensure that technology design and use are guided by ethical principles in order to ensure transparency, equity, and security and increase public trust and confidence ( Ienca & Vayena, 2020 ; Lee & Roberts, 2020 ). Information systems and technology scholars can also help identify best practices to implement responsible data-collection and data-processing, and achieve a balance between privacy and utility of the proposed technologies.

3.3. Connecting people with enhanced collaborative tools and IT infrastructures

The COVID-19 outbreak is rapidly changing the workplace. Millions of people are moving their workspaces to their homes through teleworking. Many industries benefit as knowledge workers learn to operate virtually, work from home, and use cloud services to process and store files. We are witnessing wider acceptance of online services by people and diverse types of industries during this pandemic. The importance of IT infrastructure in enabling teleworking, online learning, e-government, e-commerce, and other online activities has been widely recognized. The pandemic is forcing a record number of employees to work remotely for an extended duration, which results in heavy traffic on remote connectivity networks. There are vital needs for society to continue investing in IT infrastructure and accelerate digital transformation efforts to deal with the impact of COVID-19 and future public health crises ( Watson, Ives, et al., 2020 ). Companies need to enhance their investments in tools such as video conferencing and group decision-making support systems ( Xu, Du, & Chen, 2015 ) to enable personnel and distributed teams to work remotely and collaborate virtually. On the other hand, costs for IT infrastructure are exploding as employees practice teleworking and students take online classes in light of the COVID-19 outbreak. It is necessary to understand the rise in hard costs of IT infrastructure associated with meeting spiking demand. As the pandemic continues to evolve, IT infrastructures need to be enhanced for workers to perform their duties safely and healthily ( CISA, 2020 ). Some critical tasks may not be executable from home, and workarounds need to be identified. It is particularly necessary to identify the factors that drive the cost of serving the increased demand due to teleworking, such as cloud server costs, video conferencing costs, additional licenses for support products. Cloud services should be further leveraged through existing infrastructures such as Google Cloud, Azure, AWS, or Salesforce. Strategies need to be developed to keep essential functions and services up and running. CIOs need to think about retrofitting the present for the new needs or creating new systems for new situations ( Watson, Ives, et al., 2020 ). Finally, digital infrastructure readiness and resilience are also important areas to explore ( Papagiannidis, Harris, & Morton, 2020 ).

Group decision-making is often needed for complicated situations involving much uncertainty and time constraints. Information systems and technology scholars can share their experience with group decision support systems to support collective decision making regarding the evolving pandemic, help connect stakeholders at different levels to build consensus, and support governments, health authorities, organizations, and the public to make culturally appropriate and sensitive decisions regarding the infection detection, infection prediction, and infection avoidance and when to reopen the economy. Information systems and technology scholars can also help build collaborative information systems, community-based information systems, talent, and volunteer networks to leverage the expertise and time of various stakeholders. As an example, an innovative application is a wastewater COVID-19 early warning detection system. Wastewater detection of COVID-19 could act not only as a supplement to medical testing but as an early warning system for community monitoring and prevention. Continued wastewater-based monitoring could alert public health officials whether the coronavirus is still circulating in a community ( Chakradhar, 2020 ). A lot of volunteers are needed to make the wastewater COVID-19 early warning detection system successful. Information systems and technology scholars can contribute by providing expertise to help the government, authorities, and local communities to design and develop a volunteer network to engage and organize a large number of volunteers, and help build a collaborative information system to deliver a national program in this area ( Thomas & Bertsch, 2020 ). As Rai (2020) points out, swift deployment of grassroots innovation could develop rapid solutions to meet urgent needs.

3.4. Studying human behavior with technologies and digital divide

It is important to study human behavior when designing, building, and using technologies as more COVID-19 related technologies are being developed, integrated, and used by governments, organizations, and people. Lots of efforts to combat the pandemic incorporate new technological advances and approaches in integrating various systems and innovations. However, we need to acknowledge that people’s misbehavior with technologies may reduce the eff ;ectiveness of the technology-related interventions or countermeasures on containing the coronavirus break. Information systems and technology scholars can contribute by incorporating their understanding of human behavior into the technology design and development process, leading to more effective technology ( Pfleeger & Caputo, 2012 ). A large number of theories and models such as the technology acceptance model, innovation diffusion theory, the theory of reasoned action, health belief models and theory of planned behavior, social cognitive theory, and motivation theory can be used to explore the acceptance and use of COVID-19 related technologies such as telehealth technologies, study the strategic role of various technologies in dealing with the COVID-19 pandemic, and also examine unintended consequences of using technologies. For example, information systems and technology scholars can examine online users’ information sharing behavior, study how online patient communities should be engaged and incentivized to share information and support COVID-19 patients and caregivers, and how to analyze data to reveal new insights to support policy-making for health departments and medical knowledge discovery ( Bardhan et al., 2020 ).

We have also witnessed a digital divide during the pandemic. The digital divide broadly refers to the uneven access to digital content and connection because of some people who do not own or have easy access to technology. People's ability to use technologies effectively remains inequitable ( Newman, Browne‐Yung, Raghavendra, Wood, & Grace, 2017 ). As emerging technologies such as mobile apps, AI, IoT, and big data analytics are increasingly used to fight the pandemic, existing disparities, inequality, and biases are further reinforced ( Park & Humphry, 2019 ). As people spent more time working, learning, socializing, and shopping online at home, this pandemic provides a chance to assess the issues and challenges faced by the rapid digital transformation of organizations and how the digital divide impacts people (e.g., underprivileged populations, women, workers in healthcare, elderly and those at-risk) ( Venkatesh, 2020 ). Therefore, information systems and technology scholars need to help develop strategies and approaches to addressing digital inequality and disparity, especially when the governments need to flatten the curve of infection.

Information systems and technology can play a significant role in improving the visibility of digital inequality and disparity at organizations and communities ( Bardhan et al., 2020 ). Data shows Black and Hispanic populations face higher exposure to coronavirus and more significant hurdles for medical treatment and level of care ( Nemo, 2020 ). People of color communities tend to have relatively lower public health literacy and less experience in finding and evaluating healthcare information. Information systems and technology scholars can investigate to what extent the marginalized, women, elderly, and people of color are engaged, included, and impacted by these COVID-19 technology-related applications and systems, including health information seeking tools, mobile contact tracing, and tracking apps, COVID-19 self-checking chatbots, quarantine monitors, and telemedicine in a sustainable manner. It would be valuable to understand the short, medium, and long-term impacts of the digital divide during the COVID-19 pandemic response on marginalized groups, women, the elderly, people of color and people in rural settings. Information systems and technology scholars can do their part to improve technology design and processes to promote digital inclusion, assist with efficient development and sustainable implementation of the proposed technology, particularly in underserved populations. For example, Goh, Gao, and Agarwal (2016)) showed that technology-mediated online health communities could share information and alleviate rural-urban health disparities. Online health communities can also support the most vulnerable family caregivers ( Friedman, Trail, Vaughan, & Tanielian, 2018 ). Information systems and technology scholars can explore factors affecting underserved populations and communities to adopt and effectively use emerging technologies, encourage information sharing behavior during this crisis, and identify strategies to incentivize the mass adoption of relevant coronavirus-fighting technologies by underserved populations. Understanding the underserved population's unique perspectives in this coronavirus outbreak can provide guidelines for future IT systems and applications design, development, and potentially improve the adoption and use of novel IT systems.

4. Conclusion

The COVID-19 pandemic has produced significant impacts on people, businesses, and society. The pandemic also has implications for the design, development, and use of technologies ( Sein, 2020 ). Technologies can be useful for reducing the severity of the coronavirus pandemic’s impact on people, organizations, and society. However, the use of technologies to combat the pandemic raises challenges such as security, privacy, biases, ethics, and the digital divide. This paper evaluates the technology applications based on the data-people-system framework and suggests that the specific nature of the COVID-19 pandemic requires strong coordination for connected data, people, and systems to facilitate worldwide collaboration.

Future pandemics are likely to come. While information systems and technology scholars might not be able to help with the scientific aspect of developing vaccination and treatment directly, we can contribute knowledge, experiences, and time to help society better prepare for future pandemics. To mitigate future pandemics’ costs and improve data sharing during global public health crises, Chin and Chin (2020) called for establishing a global common data space for highly infectious diseases. While it is very challenging to establish a global common data space for public health data sharing due to various reasons such as technical, geopolitical, and ethical barriers, we support this call for its promising benefits and broader social good. At this stage, information systems and technology scholars can at least help advocate and build a national common data space or health information systems for public health data sharing.

Solving grand challenges facing society requires significant financial and human resources. To increase the importance and relevance of information systems and technology research, we encourage scholars to actively apply for various government and industry grants, including various COVID-19 funding opportunities, to get financial support to put some of their research ideas into practice. For example, the U.S. National Science Foundation and National Institutes of Health have grants programs that support technology-related research to develop solutions to addressing challenges caused by the coronavirus. Information systems and technology scholars should get involved by leading or joining an interdisciplinary team to write grant proposals and get funding to directly work on some of these research ideas. Furthermore, many students including undergraduate and graduate students in information systems and technology are looking for internship opportunities. Since many small businesses in industries such as tourism, food service, and retail are being hit hardest by the pandemic, information systems and technology faculty could collect student resumes, put them on a Google drive or a website, and share the resumes with interested small business owners. This would help match information systems and technology students with interested small businesses or non-profit organizations to solve the technology and other issues they may have during the pandemic. We are glad that some of the information systems and technology faculty are doing this and mentoring small business owners on deploying digital technologies to deal with the challenges of business continuity ( Papadopoulos, Baltas, & Balta, 2020 ). Some professors were involved in digital solution development projects (e.g., tackling misinformation) and helped to organize events such as online hackathons to gather people with diverse skills to work on solutions to help society fight COVID-19 ( Bacq, Geoghegan, Josefy, Stevenson, & Williams, 2020 ; Pan & Zhang, 2020 ). We hope to see more information systems and technology scholars involved in building and expanding technology volunteer networks and mobilizing community resources and services to fight COVID-19. At last, some of the developed technologies and application for this pandemic may cease to be useful after the pandemic ends, but many will likely be retained, enhanced, or repurposed for other uses ( Oxford Analytica, 2020 ), in which information systems and technology scholars can continue to play a role after the pandemic. For example, will data collected from mobile contact tracing be destroyed after this pandemic? What data management policies are needed to prevent the abuse of the user data and guide the improved design, development, and use of future mobile contact tracing and tracking tools?

CRediT authorship contribution statement

Wu He: Conceptualization, Investigation, Writing - original draft, Writing - review & editing. Zuopeng (Justin) Zhang: Writing - original draft, Writing - review & editing. Wenzhuo Li: Writing - original draft, Writing - review & editing.

• Agbo C.C., Mahmoud Q.H., Eklund J.M. Healthcare (Vol. 7, No. 2, p. 56) Multidisciplinary Digital Publishing Institute; 2019. Blockchain technology in healthcare: A systematic review. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ågerfalk P., Conboy K., Myers M. 2020. The european journal of information systems call for papers: Special communications on information systems in the age of pandemics. https://techjournals.wixsite.com/techjournals/ejis-is-pandemics Available at. [ Google Scholar ]
• Angst C.M., Agarwal R. Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly. 2009; 33 (2):339–370. [ Google Scholar ]
• Bacq S., Geoghegan W., Josefy M., Stevenson R., Williams T.A. The COVID-19 Virtual Idea Blitz: Marshaling social entrepreneurship to rapidly respond to urgent grand challenges. Business Horizons. 2020; 63 (6):705–723. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bansal A., Garg C., Padappayil R.P. Optimizing the Implementation of COVID-19 “Immunity Certificates” Using Blockchain. Journal of Medical Systems. 2020; 44 (9):1–2. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bardhan I., Chen H., Karahanna E. Connecting systems, data, and people: A multidisciplinary research roadmap for chronic disease management. Management Information Systems Quarterly. 2020; 44 (1):185–200. [ Google Scholar ]
• Ben-Assuli O., Padman R. Trajectories of repeated readmissions of chronic disease patients: Risk stratification, profiling, and prediction. MIS Quarterly. 2020; 44 (1):201–226. [ Google Scholar ]
• Brohi S.N., Jhanjhi N.Z., Brohi N.N., Brohi M.N. 2020. Key applications of state-of-the-Art technologies to mitigate and eliminate COVID-19. https://www.techrxiv.org/articles/Key_Applications_of_State-of-the-Art_Technologies_to_Mitigate_and_Eliminate_COVID-19_pdf/12115596 Available at. [ Google Scholar ]
• Budd J., Miller B.S., Manning E.M., Lampos V., Zhuang M., Edelstein M. Digital technologies in the public-health response to COVID-19. Nature Medicine. 2020:1–10. [ PubMed ] [ Google Scholar ]
• Chakradhar S. 2020. New research examines wastewater to detect community spread of COVID-19. https://www.boston.com/news/health/2020/04/10/new-research-examines-wastewater-to-detect-community-spread-of-covid-19 Available at. [ Google Scholar ]
• Chavez N., Kounang N. 2020. A man diagnosed with Wuhan coronavirus near Seattle is being treated largely by a robot. https://www.cnn.com/2020/01/23/health/us-wuhan-coronavirus-doctor-interview/index.html Available at. [ Google Scholar ]
• Chen C.M., Jyan H.W., Chien S.C., Jen H.H., Hsu C.Y., Lee P.C. Containing COVID-19 among 627,386 persons in contact with the diamond princess cruise ship passengers who disembarked in Taiwan: big data analytics. Journal of Medical Internet Research. 2020; 22 (5) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Chen R., Sharman R., Chakravarti N., Rao H.R., Upadhyaya S.J. Emergency response information system interoperability: Development of chemical incident response data model. Journal of the Association for Information Systems. 2008; 9 (3):200–230. [ Google Scholar ]
• Chiasson M., Davidson E., Winter J. Philosophical foundations for informing the future (S) through IS research. European Journal of Information Systems. 2018; 27 (3):367–379. [ Google Scholar ]
• Chin S., Chin C. 2020. To mitigate the costs of future pandemics, establish a common data space. https://www.brookings.edu/blog/techtank/2020/11/02/to-mitigate-the-costs-of-future-pandemics-establish-a-common-data-space/ Available at. [ Google Scholar ]
• Cho H., Ippolito D., Yu Y.W. Contact tracing mobile apps for COVID-19: Privacy considerations and related trade-offs. arXiv preprint arXiv. 2020 2003.11511. [ Google Scholar ]
• Chong A.Y.L., Lim E.T., Hua X., Zheng S., Tan C.W. Business on chain: A comparative case study of five blockchain-inspired business models. Journal of the Association for Information Systems. 2019; 20 (9):9. [ Google Scholar ]
• Choong Y.Y.C., Tan H.W., Patel D.C., Choong W.T.N., Chen C.H., Low H.Y. The global rise of 3D printing during the COVID-19 pandemic. Nature Reviews Materials. 2020:1–3. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• CISA . 2020. CISA releases version 3.0 of guidance on essential critical infrastructure workers during covid-19. https://www.cisa.gov/news/2020/04/17/cisa-releases-version-30-guidance-essential-critical-infrastructure-workers-during Available at. [ Google Scholar ]
• Dwivedi Y.K., Hughes D.L., Coombs C., Constantiou I., Duan Y., Edwards J.S. Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management. 2020; 55 [ Google Scholar ]
• Fahey R.A., Hino A. COVID-19, digital privacy, and the social limits on data-focused public health responses. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ferretti L., Wymant C., Kendall M., Zhao L., Nurtay A., Abeler-Dörner L. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science. 2020 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Friedman E.M., Trail T.E., Vaughan C.A., Tanielian T. Online Peer Support Groups for Family Caregivers: Are They Reaching the Caregivers with the Greatest Needs? Journal of the American Medical Informatics Association. 2018; 25 (9):1130–1136. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Goh J.M., Gao G., Agarwal R. The Creation of Social Value: Can an Online Health Community Reduce Rural– Urban Health Disparities? MIS Quarterly. 2016; 40 (1):247–263. [ Google Scholar ]
• Gurgu E., Andronie M., Andronie M., Dijmarescu I. International conference on economic sciences and business administration (Vol. 5, No. 1. Spiru Haret University.; 2019. Does the convergence of the blockchain, the internet of things and artificial intelligence changing our lives, education and the known world of the internet?! Some changes and perspectives for the International economy; pp. 69–88. [ Google Scholar ]
• He S. 2020. Using the internet of things to fight virus outbreaks. https://www.technologynetworks.com/immunology/articles/using-the-internet-of-things-to-fight-virus-outbreaks-331992 Available at. [ Google Scholar ]
• Henningsson S., Yetton P.W., Wynne P.J. A review of information system integration in mergers and acquisitions. Journal of Information Technology. 2018; 33 (4):255–303. [ Google Scholar ]
• Holt K. 2020. Facebook used its AI smarts to build detailed disease prevention maps. https://www.engadget.com/2019-05-20-facebook-ai-disease-prevention-maps-demographics-movement-network-coverage.html Available at. [ Google Scholar ]
• Huang Y., Sun M., Sui Y. 2020. How digital contact tracing slowed Covid-19 in East Asia. https://hbr.org/2020/04/how-digital-contact-tracing-slowed-covid-19-in-east-asia Available at. [ Google Scholar ]
• Ienca M., Vayena E. On the responsible use of digital data to tackle the COVID-19 pandemic. Nature Medicine. 2020; 26 (4):463–464. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Johnstone S. University of Hong Kong Faculty of Law Research Paper, (2020/005); 2020. A viral warning for change. COVID-19 versus the Red Cross: Better Solutions Via Blockchain and Artificial Intelligence (February 3, 2020) [ Google Scholar ]
• Khurshid A. Applying blockchain technology to address the crisis of trust during the COVID-19 pandemic. JMIR Medical Informatics. 2020; 8 (9) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kumar K., Kumar N., Shah R. Role of IoT to avoid spreading of COVID-19. International Journal of Intelligent Networks. 2020; 1 :32–35. [ Google Scholar ]
• Lee N.T., Roberts J. Managing health privacy and bias in COVID-19 public surveillance. Brookings. 2020 https://www.brookings.edu/blog/techtank/2020/04/21/managing-health-privacy-and-bias-in-covid-19-public-surveillance/?utm_campaign=Center%20for%20Technology%20Innovation&utm_source=hs_email&utm_medium=email&utm_content=87437298 Available at. [ Google Scholar ]
• Liang W., Yao J., Chen A., Lv Q., Zanin M., Liu J. Early triage of critically ill COVID-19 patients using deep learning. Nature Communications. 2020; 11 (1):1–7. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lin L., Martin T. 2020. How coronavirus is eroding privacy. https://www.wsj.com/articles/coronavirus-paves-way-for-new-age-of-digital-surveillance-11586963028 Available at. [ Google Scholar ]
• Lin Q., Zhao S., Gao D., Lou Y., Yang S., Musa S.S. A conceptual model for the outbreak of Coronavirus disease 2019 (COVID-19) in Wuhan, China with individual reaction and governmental action. International Journal of Infectious Diseases. 2020; 93 :211–216. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Liu J. 2020. Deployment of health IT in China’s fight against the COVID-19 pandemic. https://www.itnonline.com/article/deployment-health-it-china%E2%80%99s-fight-against-covid-19-pandemic Available at: [ Google Scholar ]
• Loh T., Fishbane L. 2020. COVID-19 makes the benefits of telework obvious. https://www.brookings.edu/blog/the-avenue/2020/03/17/covid-19-makes-the-benefits-of-telework-obvious/ Available at. [ Google Scholar ]
• Markforged . 2020. Fiberflex: 3D printed nasal swabs for Covid-19 testing. https://markforged.com/covid-19/#swabs Available at. [ Google Scholar ]
• Marr B. 2020. Coronavirus: How artificial intelligence, data science and technology is used to fight the pandemic. https://www.forbes.com/sites/bernardmarr/2020/03/13/coronavirus-how-artificial-intelligence-data-science-and-technology-is-used-to-fight-the-pandemic/#34645abe5f5f Available at. [ Google Scholar ]
• Marr N. 2020. How the COVID-19 pandemic is fast-tracking digital transformation in companies. https://www.forbes.com/sites/bernardmarr/2020/03/17/how-the-covid-19-pandemic-is-fast-tracking-digital-transformation-in-companies/#60fc18caa8ee Available at. [ Google Scholar ]
• Mingis K. 2020. Tech pitches in to fight COVID-19 pandemic. https://www.computerworld.com/article/3534478/tech-pitches-in-to-fight-covid-19-pandemic.html Available at. [ Google Scholar ]
• Nabity-Grover T., Cheung C.M., Thatcher J.B. Inside out and outside in: How the COVID-19 pandemic affects self-disclosure on social media. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Nasajpour M., Pouriyeh S., Parizi R.M., Dorodchi M., Valero M., Arabnia H.R. Internet of Things for current COVID-19 and future pandemics: An exploratory study. Journal of Healthcare Informatics Research. 2020:1–40. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Nemo L. 2020. Why people of color are disproportionately hit by COVID-19. https://www.discovermagazine.com/health/why-people-of-color-are-disproportionately-hit-by-covid-19 Available at. [ Google Scholar ]
• Newman L., Browne‐Yung K., Raghavendra P., Wood D., Grace E. Applying a critical approach to investigate barriers to digital inclusion and online social networking among young people with disabilities. Information Systems Journal. 2017; 27 (5):559–588. [ Google Scholar ]
• News Staff . 2020. Blockchain emerges as useful tool in fight against coronavirus. https://www.govtech.com/products/Blockchain-Emerges-as-Useful-Tool-in-Fight-Against-Coronavirus.html Available at. [ Google Scholar ]
• O’Leary D.E. Evolving information systems and technology research issues for COVID-19 and other pandemics. Journal of Organizational Computing and Electronic Commerce. 2020 doi: 10.1080/10919392.2020.1755790. Available at. [ CrossRef ] [ Google Scholar ]
• O’Neill P.H., Ryan-Mosley T., Johnson B. 2020. A flood of coronavirus apps are tracking us. Now it’s time to keep track of them. https://www.technologyreview.com/2020/05/07/1000961/launching-mittr-covid-tracing-tracker/ Available at. [ Google Scholar ]
• Onik M.M.H., Aich S., Yang J., Kim C.S., Kim H.C. Big data analytics for intelligent healthcare management. Academic Press; 2019. Blockchain in healthcare: Challenges and solutions; pp. 197–226. [ Google Scholar ]
• Oxford Analytica . Emerald expert briefings. 2020. COVID-19 tech will expand surveillance state in China. Available at. [ CrossRef ] [ Google Scholar ]
• Ozturk T., Talo M., Yildirim E.A., Baloglu U.B., Yildirim O., Acharya U.R. Automated detection of COVID-19 cases using deep neural networks with X-ray images. Computers in Biology and Medicine. 2020 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pan S.L., Cui M., Qian J. Information resource orchestration during the COVID-19 pandemic: A study of community lockdowns in China. International Journal of Information Management. 2020; 54 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pan S.L., Pan G., Leidner D.E. Crisis response information networks. Journal of the Association for Information Systems. 2012; 13 (1):518–555. [ Google Scholar ]
• Pan S.L., Zhang S. From fighting COVID-19 pandemic to tackling sustainable development goals: An opportunity for responsible information systems research. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Papadopoulos T., Baltas K.N., Balta M.E. The use of digital technologies by small and medium enterprises during COVID-19: Implications for theory and practice. International Journal of Information Management. 2020; 55 doi: 10.1016/j.ijinfomgt.2020.102192. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Papagiannidis S., Harris J., Morton D. WHO led the digital transformation of your company? A reflection of IT related challenges during the pandemic. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Park S., Humphry J. Exclusion by design: Intersections of social, digital and data exclusion. Information, Communication and Society. 2019; 22 (7):934–953. [ Google Scholar ]
• Pfleeger S.L., Caputo D.D. Leveraging behavioral science to mitigate cyber security risk. Computers & Security. 2012; 31 (4):597–611. [ Google Scholar ]
• Pham Q., Nguyen D.C., Huynh-The T., Hwang W., Pathirana P.N. Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts. Preprints. 2020; 2020 doi: 10.20944/preprints202004.0383.v1). [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Punn N.S., Sonbhadra S.K., Agarwal S. COVID-19 epidemic analysis using machine learning and deep learning algorithms. medRxiv. 2020 [ Google Scholar ]
• Rahman M.S., Peeri N.C., Shrestha N., Zaki R., Haque U., Ab Hamid S.H. Defending against the Novel Coronavirus (COVID-19) Outbreak: How Can the Internet of Things (IoT) help to save the World? Health Policy and Technology. 2020; 9 (2):136–138. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rai A. The COVID-19 pandemic: Building resilience with IS research. MIS Quarterly. 2020; 44 (2):02. [ Google Scholar ]
• Ravichandran T., Rai A. Quality management in systems development: An organizational system perspective. MIS Quarterly. 2000:381–415. [ Google Scholar ]
• Rehfuess E.A., Stratil J.M., Scheel I.B., Portela A., Norris S.L., Baltussen R. The WHO-INTEGRATE evidence to decision framework version 1.0: Integrating WHO norms and values and a complexity perspective. BMJ Global Health. 2019; 4 (Suppl 1) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Richter A. Locked-down digital work. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Scott D. 2020. What good digital contact tracing might look like. https://www.vox.com/2020/4/22/21231443/coronavirus-contact-tracing-app-states Available at. [ Google Scholar ]
• Sein M.K. The serendipitous impact of COVID-19 pandemic: A rare opportunity for research and practice. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sinclair S. 2020. Researchers in Spain are racing to develop a smartphone app that leverages blockchain technology and artificial intelligence to help stem the coronavirus pandemic. https://www.coindesk.com/spanish-researchers-working-to-curb-coronavirus-spread-with-blockchain-app Available at. [ Google Scholar ]
• Singh S.K., Rathore S., Park J.H. Blockiotintelligence: A blockchain-enabled intelligent IoT architecture with artificial intelligence. Future Generation Computer Systems. 2020; 110 :721–743. [ Google Scholar ]
• Sipior J.C. Considerations for development and use of AI in response to COVID-19. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Thomas K., Bertsch P. 2020. Australian researchers trace sewage for early warning COVID-19 spread. https://www.uq.edu.au/news/article/2020/04/australian-researchers-trace-sewage-early-warning-covid-19-spread Available at. [ Google Scholar ]
• Thompson S., Whitaker J., Kohli R., Jones C. Chronic disease management: How IT and analytics create healthcare value through the temporal displacement of care. MIS Quarterly. 2019; 44 (1):227–256. [ Google Scholar ]
• Ting D.S.W., Carin L., Dzau V., Wong T.Y. Digital technology and COVID-19. Nature Medicine. 2020; 26 (4):459–461. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Valecha R., Rao R., Upadhyaya S., Sharman R. An activity theory approach to modeling dispatch-mediated emergency response. Journal of the Association for Information Systems. 2019; 20 (1):33–57. [ Google Scholar ]
• Venkatesh V. Impacts of COVID-19: A research agenda to support people in their fight. International Journal of Information Management. 2020; 55 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wang J. Fast identification of possible drug treatment of coronavirus disease-19 (COVID-19) through computational drug repurposing study. Journal of Chemical Information and Modeling. 2020; 60 (6):3277–3286. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wang C.J., Ng C.Y., Brook R.H. Response to COVID-19 in Taiwan: Big data analytics, new technology, and proactive testing. Jama. 2020 [ PubMed ] [ Google Scholar ]
• Wang S., Zha Y., Li W., Wu Q., Li X., Niu M. A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis. The European Respiratory Journal. 2020 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Watson R., Ives B., Piccoli G. Guest editorial: Practice-oriented research contributions in the Covid-19 forged new normal. MIS Quarterly Executive. 2020; 19 (2):2. [ Google Scholar ]
• Woo T. Cloud players and research groups join the fight against COVID-19 with high-performance computing. Forrest. 2020 https://go.forrester.com/blogs/cloud-players-and-research-groups-join-the-fight-against-covid-19-with-high-performance-computing/ Available at. [ Google Scholar ]
• World Health Organization . 2020. Digital technology for COVID-19 response. https://www.who.int/news-room/detail/03-04-2020-digital-technology-for-covid-19-response Available at. [ Google Scholar ]
• Xu L. Enterprise systems: State-of-the-art and future trends. IEEE Transactions on Industrial Informatics. 2011; 7 (4):630–640. [ Google Scholar ]
• Xu X.H., Du Z.J., Chen X.H. Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions. Decision Support Systems. 2015; 79 :150–160. [ Google Scholar ]
• Yan L., Tan Y. Feeling blue? Go online: An empirical study of social support among patients. Information Systems Research. 2014; 25 (4):690–709. [ Google Scholar ]
• Yang G.Z., Nelson B.J., Murphy R.R., Choset H., Christensen H., Collins S.H. 2020. Combating COVID-19—The role of robotics in managing public health and infectious diseases. [ PubMed ] [ Google Scholar ]
• Young J. 2020. Scenes from college classes forced online by COVID-19. https://www.edsurge.com/news/2020-03-26-scenes-from-college-classes-forced-online-by-COVID-19 Available at. [ Google Scholar ]
• Ziebland S., Chapple A., Dumelow C., Evans J., Prinjha S., Rozmovits L. How the internet affects patients’ experience of Cancer: A qualitative study. BMJ. 2004; 328 :7439. [ PMC free article ] [ PubMed ] [ Google Scholar ]

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Technology is all about solving big thorny problems. Yet one of the hardest things about solving hard problems is knowing where to focus our efforts. There are so many urgent issues facing the world. Where should we even begin? So we asked dozens of people to identify what problem at the intersection of technology and society that they think we should focus more of our energy on. We queried scientists, journalists, politicians, entrepreneurs, activists, and CEOs.

Some broad themes emerged: the climate crisis, global health, creating a just and equitable society, and AI all came up frequently. There were plenty of outliers, too, ranging from regulating social media to fighting corruption.

Reporting: MIT Technology Review Staff Editing: Allison Arieff, Rachel Courtland, Mat Honan, Amy Nordrum Copy editing: Linda Lowenthal Fact checking: Matt Mahoney Art direction: Stephanie Arnett

10 biggest tech problems that should have been solved by now

The annoying bugbears that have tech innovators stumped

• Ten big tech problems: 1 - 5
• Tech problems: 6 - 10

There's a famous Louis CK sketch in which the red-headed social commentator points out what a bunch of ungrateful so-and-sos (he uses a different word) this generation is for daring to complain about smartphones .

"We have this beautiful thing and we hate it. Even the s***tiest cellphone, is a miracle," he says. "Why are you so mad at it?"

As we often catch ourselves violently stabbing the touchscreen of our super-powerful, handheld telephone, internet device, games console, media player and navigation tool for responding more than a millisecond after our sweet caress, it's hard to argue with the popular comedian's assessment.

Tech has brought us such a long way, and we give thanks to the silicon gods every day.

Louis is right, we should smell the roses. But, come on, is there really any excuse for these infuriating tech-related problems to still exist?

1. Tangled headphone cables

How about just once, we could pull a pair of cans or buds out of our bags without spending half an hour unravelling the cables? It's a problem that several audio manufactures have attempted to resolve, but most just gave up and by-passed the cables completely thanks to a little Bluetooth magic.

The budget Zipbuds, do the trick by literally zipping them up, but make the experience cumbersome. The a-JAYS One+ earphones employ springy flat cables to 'resist' tangles, but no one has found a real way to ease the frustration.

Don't get us started on those Apple EarPods either.

2. Changing email addresses

As funny as it sounded at the time, the email address [email protected] looks bad on a CV. The trouble is, it's easier to actually move house than it is to change email addresses and maintain all of your correspondences.

Updating every online account you have takes forever, as does safeguarding all of your files and making sure everyone who emails you has access to the new address. The reality is, you're never free of an old email address. There's always the temptation to login every couple of months just to ensure you've not missed something important, like a message from a long-lost friend, or bank telling you you've been defrauded. How else do you think Hotmail was able to keep going for so long?

3. Proper all-day smartphone battery life

In trying to solve the conundrum regarding iOS 7 and crippled iPhone 5 battery efficiency we stumbled across a really helpful online feature. "Just try using it less," it advised. Geniuses! Why didn't we think of that?

However, even without a new OS to sap the cell, the full HD 5-inch screens, quad-core processors, console-quality games and turn-by-turn GPS mean most well-used handsets are begging for a refill after a tough 8-hour shift. Is it really that hard to make them better? We've still got a Nokia 3210 in the office that's been switched on since 1999.

4. Pick 'n' Mix television

Isn't ludicrous that with omnipresent streaming portals and on-demand options that simply obtaining our favorite TV channels necessitates paying for about 500 that we don't want?

"Need Sky Sports, Sir? Here's the Bio channel too! Here you can watch Real Housewives of Atlanta re-runs all day." Thanks! Sadly, this isn't technology's problem, but that of an antiquated subscription model that current technology will eventually crush to smithereens. However, we won't get there until an entire generation of Rupert Murdochs shuffle off this mortal coil.

5. A-zombie Flash

We think we've figure out the best halloween costume and it's a cracker! We're going as Adobe Flash, because no matter how hard the world tries, it just won't die.

The Michael Myers of web technology was savaged by Steve Jobs, banned from iOS and hell, even Adobe doesn't like it that much anymore. The real reason flash still hangs around crashing our computers, gobbling up our RAM and forcing us into updates at every turn and inhibiting our mobile experiences is because of HMTL5 has failed to assume the throne. We're not angry, we're just disappointed.

Current page: Ten big tech problems: 1 - 5

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A technology journalist, writer and videographer of many magazines and websites including T3, Gadget Magazine and TechRadar.com. He specializes in applications for smartphones, tablets and handheld devices, with bylines also at The Guardian, WIRED, Trusted Reviews and Wareable. Chris is also the podcast host for The Liverpool Way. As well as tech and football, Chris is a pop-punk fan and enjoys the art of wrasslin'.

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The 12 biggest issues IT faces today

Economic uncertainty, the need to continually drive business value, and shifting ways of working and leveraging IT continue to reshape the CIO agenda as priorities shift mid-year.

The list of expectations on CIOs continues to lengthen, as they face pressure to seize on new technologies and drive the organization forward while simultaneously improving efficiency, dealing with staffing challenges, and facing a tech skills gap.

Granted, each CIO will have a unique list of priorities and challenges based on enterprise objectives and its industry vertical. But the following 12 issues are ones that CIOs commonly find themselves contending with today.

1. Hardening cybersecurity

Most CIOs not only see cybersecurity as one of their top issues today, a majority name it as their No. 1 concern.

Consider the findings from the 2023 Insight Intelligent Technology Report, an IDC InfoBrief. The survey found that cybersecurity is one of the top challenges facing organizations, with 56% of respondents saying so.

Meanwhile, Lenovo’s Global Study of CIOs showed that 66% of CIOs listed cybersecurity/ransomware and 66% listed data privacy/security as top challenges.

“As technology evolves, hackers adjust their methods to new norms, making security threats a constant concern that requires IT leaders and their teams to be vigilant around the clock,” says Jeremy Rafuse, vice president of IT and head of digital workplace at software company GoTo.

2. Operationalizing artificial intelligence

Harnessing the power of AI — and particularly generative AI — is also dominating the CIO’s agenda, according to multiple sources.

“The No. 1 question these days is, ‘How do we leverage generative AI?’” says Thomas Phelps, vice president of corporate strategy and CIO of Laserfiche. “It’s being brought up by the executive staff, the board, at trade shows, and in the media; you can’t walk anywhere without hearing about generative AI.”

Phelps and other tech execs say they’re focusing on how to use AI throughout their organizations to not only be more effective and efficient but to be more innovative and transformative, too. But they’re additionally tasked with doing so in a secure and ethical manner , necessitating the development of new strategies, practices, and governance policies that for many are still very much in the works.

3. Coping with economic pressures, uncertainty

Although the majority of CIOs have seen their IT budgets increase, they also say they’re feeling the pinch of inflation because that extra money isn’t covering their higher costs.

For example, the CIO Pulse: 2023 Budgets and Priorities survey from SoftwareOne reports that 93% of the 600 IT leaders it surveyed said their budgets are up, yet 83% also say that they will have to achieve more with less.

That has CIOs looking at how they can drive more efficiencies both in their own IT departments as well as throughout their organizations.

“In this age of economic uncertainty, there are a lot of questions about whether we are as efficient as we can be and whether we really understand our costs,” says Joseph Bruhin, CIO of Breakthru Beverage Group.

Barry Brunsman, a principal at professional services firm KPMG and leader of its Global CIO Center of Excellence, says CIOs are walking a tightrope here: They’re focusing on delivering efficiencies so their organizations are prepared if national economies tip into recession (the subject of ongoing speculation that has yet to happen in most places) but at the same time they don’t want to scale back on initiatives that could better position their organizations if economies stay steady or strengthen.

“There’s kind of a paralysis around what CIOs are going to do,” he says.

4. Modernizing at speed

The ever-increasing pace of technology change also has CIOs’ full attention.

Joel Schwalbe, CIO of biotech company Transnetyx, says he’s focused on continuously reducing technical debt and modernizing his company’s tech stack so his IT team can minimize the resources needed for maintaining the environment and instead maximize the time and energy spent on supporting business objectives.

It’s a constant challenge, Schwalbe says.

“It’s tricky, because as technology continues to evolve, you want to make sure you place your bets in the right area,” he says, adding that the goal is to stay on top of modernization and transformation efforts so “you don’t get to the point where tech debt is a problem.”

Lenovo’s Global Study of CIOs gives some insight into this work. It found that 61% of respondents believe that “their business would feel an impact in no more than a few weeks if they halted spending on digital transformation initiatives.”

Moreover, 57% said they’d replace half or more of their company’s current technology if given the chance to start from scratch and 25% said they’d replace most or all of it.

5. Innovating meaningfully

Of course, as CIOs know, that modernization effort can’t just be for the sake of getting new technologies. It must drive business objectives and ultimately transformation.

That’s why, Phelps says, he and other CIOs continue to build “an ongoing culture of innovation” within their IT departments and their organizations as a whole.

CIOs are well-positioned to take on the task, Phelps says, because they work across all the functional areas of the enterprise and they are among the best equipped to propose and deliver innovative digital services .

“Everything is now digital, and CIOs have to shape that narrative. That has elevated the role of CIO to be one of a digital leader who can plug into innovative initiatives,” Phelps adds.

Research confirms the emphasis on IT as innovator: In the May 2023 Technology Pulse Poll from professional services firm EY, 94% of surveyed tech executives said that “company-wide innovation will help them come out of the current economic downturn a stronger company than before”; 94% said their company plans to increase investments in IT or emerging technologies over the next year; and 81% said their company plans to make an innovation-related acquisition in the next six months.

6. Ensuring IT’s value proposition

Just as innovation must bring tangible returns to the enterprise, so too are CIOs expected to work with their business colleagues to calculate the value proposition of tech initiatives .

As Bruhin explains, CIOs today must have — and instill in their partners who come requesting new technologies — a “benefits realization mentality.”

“There’s a focus on the value it’s going to generate for the organization,” he adds.

7. Driving data insights

Speaking of value, CIOs are also looking at how to maximize all the data-related investments they’ve made in recent years.

CIO’s 2023 State of the CIO survey found that 34% of IT leaders list leveraging data as a major tech initiative, putting it second on the list of priorities — just behind security and risk management.

And EY’s Technology Pulse Poll found that 62% of surveyed tech execs have prioritized big data and analytics investments.

But where past years’ investments focused on building solid data infrastructure, CIOs are now spending on technologies and training to help people throughout their organizations use data.

“We’re seeing a shift in spending to technologies that drive the democratization of data and analytics — and we are expecting that spend will dramatically increase,” Brunsman says, adding that, although many organizations have data specialists generating insights from the vast troves of data they’ve accumulated, they now want to get to a place where everyone in their organization can get value out of data.

8. Transforming to meet regulatory requirements

CIOs are also still working with their executive peers to manage their data, says Ray Velez, global CTO with the digital consultancy Publicis Sapient.

Granted, many CIOs have been working with their chief data officers, chief marketing officers and other C-suite leaders on this topic for years. But, as Velez points out, the rules and regulations around data evolve.

As a result, Velez says he sees “a lot of focus on modernizing the customer data stack” and adopting emerging technologies that allow organizations to meet regulatory requirements such as offering a customer opt-out capability while still enabling organizations to access and use the data needed to deliver personalized customer service and insights to decision-makers.

“CIOs need to be able to supply things like consent management and work with others to create and transform how customer data is used, stored and the communication of the value proposition,” Velez adds.

9. Democratizing tech development

CIOs are not only putting data into the hands of workers throughout their organizations; they’re increasingly putting software development tools there , too.

Research firm IDC expects sales of low-code/no-code platforms to grow at a rapid clip — 13.9% annually — through 2026.

Jamie Smith, CIO at the University of Phoenix, believes enabling non-IT workers to create some of their own capabilities is a “force multiplier” that benefits the entire organization by enabling workers closest to business processes and customers to create the digital experiences they want and need to get their work done.

10. Acquiring and retaining talent

Global business consulting firm Protiviti surveyed 1,304 C-level executives and directors to understand the top risks they face. The top of their list? The ability to attract and retain top talent in a tightening labor market, which they see as limiting their ability to achieve operational targets .

Although many functional leaders experience challenges finding and keeping talent, CIOs are among the most taxed in this regard.

“The global talent shortage has burdened the job market, and researchers expect this issue to worsen, with 85 million jobs forecasted to be unfilled by 2030 due to a lack of skilled workers,” Rafuse says. “With tech advancement accelerating by the day, it’s possible the problem gets worse before it gets better. IT departments need to be able to keep up with constant updates, new operating systems, and emerging threats, or understaffed teams risk falling behind.”

He continues: “With so much competition for top talent and laid-off workers from Big Tech firms, companies need to be creative in how they set themselves apart. CIOs and IT leaders should also constantly explore methods to invest in the internal upskilling of their current staff in order to attract and maintain talent.”

11. Preparing IT teams for the future

CIOs have to think not only about their teams today, but their teams of tomorrow , too.

IT workers must keep pace with evolving technologies to ensure they can deliver and support the tools and capabilities their organizations will need to be successful. Moreover, technologists want to learn new skills, with multiple studies showing that they’ll switch jobs if they feel like they’re stagnating in their current role. (In one recent survey , 47% of responding tech workers said they’re considering leaving their current job to grow their skills.)

“Skilled IT labor is going to continue to be difficult to find in the future, so CIOs more than ever are going to have to look at opportunities for their staff to upskill,” says Matt Deneroff, vice president of technology talent solutions at staffing firm Robert Half.

12. Creating a hybrid work environment that works for everyone

CIOs say they themselves also must learn to work in new ways as the world shifts, particularly when it comes to supporting a hybrid workforce across their organization as well as leading their own teams in this new workplace model.

“Equipping employees with the tools and support they need to do their jobs, no matter where they are, needs to be a top priority for IT teams,” Rafuse says.

But at the same time Rafuse says CIOs, himself included, should consider what that means for IT staffers.

“[The] IT manager must balance this flexibility with a good life/work balance. Just because IT teams can always be on, doesn’t mean they should if you want to keep good talent around for the long term,” he says, noting that “businesses should strive for quality over quantity by streamlining the number of technologies and software they are using thus reducing the burden on IT. This will create a more positive and functional virtual working environment for employees, while reducing cross-department friction and IT team burnout.”

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Technological problem solving: an investigation of differences associated with levels of task success

• Open access
• Published: 02 June 2021
• volume  32 ,  pages 1725–1753 ( 2022 )

You have full access to this open access article

• David Morrison-Love   ORCID: orcid.org/0000-0002-9009-4738 1  

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Cite this article

Research into technological problem solving has shown it to exist in a range of forms and draw upon different processes and knowledge types. This paper adds to this understanding by identifying procedural and epistemic differences in relation to task performance for pupils solving a well-defined technological problem. The study is theoretically grounded in a transformative epistemology of technology education. 50 pupils in small groups worked through a cantilever problem, the most and least successful solutions to which were identified using a Delphi technique. Time-interval photography, verbal interactions, observations and supplementary data formed a composite representation of activity which was analysed with successively less contrasting groups to isolate sustained differences. Analyses revealed key differences in three areas. First, more successful groups used better and more proactive process-management strategies including use of planning, role and task allocation with lower levels of group tension. Second, they made greater use of reflection in which knowledge associated with the technological solution was explicitly verblised. This was defined as ‘analytical reflection’ and reveals aspects of pupils’ qualitative technical knowledge. Third, higher-performing groups exhibited greater levels of tacit-procedural knowledge within their solutions. There was also evidence that less successful groups were less affected by competition and not as comprehensive in translating prior conceptual learning into their tangible technological solutions. Overall findings suggest that proactive management, and making contextual and technical connections, are important for pupils solving well-defined technological problems. This understanding can be used to support classroom pedagogies that help pupils learn to problem solve more effectively.

Avoid common mistakes on your manuscript.

Introduction

Problem solving is an activity, a context and a dominant pedagogical frame for Technology Education. It constitutes a central method and a critical skill through which school pupils learn about and become proficient in technology (Custer et al., 2001 ). Research has, among other things, been able to identify and investigate sets of intellectual and cognitive processes (Buckley et al., 2019 ; Haupt, 2018 ; Johnson, 1997 ; Sung & Kelly, 2019 ) and shown there to be conceptual, procedural, relational and harder-to-get-to forms of ‘technological knowledge’ involved when pupils develop technological solutions (de Vries, 2005 ; McCormick, 1997 , 2004 ; Rauscher, 2011 ). Some authors argue that technological problem solving (and design) is a situated activity (Jackson & Strimel, 2018 ; Murphy & McCormick, 1997 ; Liddament, 1996 ), but with social and context-independent processes also playing an important role (e.g. Jones, 1997 ; Winkelmann & Hacker, 2011 ). Within and across this vista, there has been strong interest in more open-ended, creative and design-based problem-solving (Lewis, 2005 , 2009 ), which Xu et al. ( 2019 ) notes became particularly prominent after 2006. These studies have helped to understand some of the challenges and pedagogies of design (Gómez Puente et al., 2013 ; Lavonen et al., 2002 ; Mioduser & Dagan, 2007 ; Mawson, 2003 ) including those that mitigate effects such as cognitive fixation (e.g. McLellan & Nicholl, 2011 ). Problem solving, it seems, is a pervasive idea in technology education research and policy. Middleton ( 2009 ) notes that problem solving is found in almost all international technology education curricula.

The pace, nature and complexity of contemporary societal challenges make it more critical than ever that technology classrooms prepare people who can think through and respond to technological problems effectively. It requires that we strengthen our understanding in ways that will ultimately be powerful for shaping classroom learning. One way of contributing to this is to learn more about the differences between learners who are more and less successful at technological problem solving. Studies that share a comparative perspective and/or a focus upon task success are relatively few. Doornekamp ( 2001 ) compared pupils (circa 13 years old) who solved technological problems using weakly structured instructional materials with those using strongly structured materials. It was shown that the latter led to statistically significant improvements in the quality of the technical solutions. More recently, Bartholomew & Strimel ( 2018 ) were able to show that, for open-ended problem solving, there was no significant relationship between prior experience and folio creation, but that more in-school school experience of open-ended problem solving corresponded to higher ranked solutions.

This paper contributes to this work by reporting on a study that compares groups of pupils during technological problem solving in order to identify areas of difference and the factors associated with more successful outcomes. Specifically, it addresses the question: ‘In terms of intellectual processes and knowledge, what are the differences in the modi operandi between groups of pupils that produced more and less successful technological solutions to a well-defined problem?’ Theoretically grounded in a transformative epistemology of technology education (Morrison-Love, 2017 ), the study identifies prominent procedural and epistemic differences in pupils’ thinking and technical solutions. Groups of pupils engaged with a structures problem requiring them to develop a cantilever bridge system which would facilitate safe travel across a body of water.

The paper begins by setting out the theoretical basis and conceptual framework for investigation before describing the comparative methodological and analytical approaches that were adopted. Following an analysis and presentation of key findings, conclusion and implications are discussed.

A theoretical basis for the study of technological problem solving

Despite there being no single comprehensive paradigm for technological problem solving, a theoretical grounding and conceptual framework necessary for this study are presented. At the theoretical level, this study is based upon a ‘transformative epistemology’ for technology education (Morrison-Love, 2017 ). From this, a ternary conceptual framework based upon mode, epistemology and process is developed to support study design and initiate data analysis.

A transformative epistemology for technology education (Morrison-Love, ibid) proposes that pupils’ technological knowledge and capability arises from the ontological transformation of their technical solution from ‘perdurant’ (more conceptual, mutable, less well-defined, partial) in the early stages, to ‘endurant’ (comprehensive, tangible, stable over time) upon completion. It proposes that technical outcomes exist in material and tangible forms and that to be technological (rather than, for example, social, cultural or aesthetic) these must somehow enhance human capabilities in their intended systems of use. For this study, the ideas of transformative epistemology support problem solving in which pupils build technological knowledge by iteratively moving from concept to tangible, material solution. Moreover, it means pupils are successful in this when their solutions or prototypes: (1) enhance existing human capabilities in some way, and (2) are sufficiently developed to be stable over time, beyond the problem-solving activity that created it.

A conceptual framework for technological problem solving

A ternary conceptual framework (Fig. 1 ) of mode, process and epistemology was developed from the literature in which the knowledge and cognitive/intellectual processes used by pupils are enacted in the ‘process application block’. This is like the ‘problem space’ described in a model proposed by Mioduser ( 1998 ). Collectively, the goal of creating a physical artefact, the solution itself, the epistemic and procedural dimensions reflect the four dimensions of technology identified by Custer ( 1995 ).

‘A conceptual framework for technological problem solving’

Mode and forms dimension

Although problem solving may be ‘technological’, several classifications of both problem type and problem solving are found in the literature. Ill-defined and well-defined problems build upon the earlier work of information processing and cognitive psychology (see Jonassen, 1997 ). Typically, these two forms reflect different extents to which the outcome is specified to the solver at the outset. Ill-defined problems are strongly associated with design and creativity, and Twyford and Järvinen ( 2000 ) suggest that these more open briefs promote greater social interaction and use by pupils of prior knowledge and experience. Additionally, two forms of troubleshooting were identified in the literature: emergent troubleshooting and discrete troubleshooting. MacPherson ( 1998 ) argues that ‘troubleshooting’ constitutes a particular subset of technological problem solving—something earlier recognised by McCade ( 1990 ), who views it as the identification and overcoming of problems encountered during the production or use of a technical solution. In this study, emergent troubleshooting occurs in the process of developing solutions in response to emergent problems (McCormick, 1994 ). Discrete troubleshooting is a process in which significant technical understanding is applied in a structured way (Schaafstal et al., 2000 ) to resolve something about an existing artefact.

Intellectual and cognitive process dimension

Studies often conceptualise cognitive processes discretely rather than hierarchically, and different studies employ different process sets. Williams ( 2000 ), identifies evaluation, communication, modelling, generating ideas, research and investigation, producing and documenting as important to technological problem solving, while DeLuca ( 1991 ) identifies troubleshooting, the scientific process, the design process, research and development, and project management. There are also studies that employ specific, or more established, coding schemes for sets of intellectual and cognitive processes. A detailed analysis of these is given Grubbs et al. ( 2018 ), although the extent to which a particular process remains discrete or could form a sub-process of another remains problematic. In DeLuca’s ( 1991 ) break down for example, to what extent are research and investigation part of design and does this depend on the scale at which we conceptualise different processes?

Regardless of the processes a study defines, it is typically understood that pupils apply them in iterative or cyclic fashion. This is reflected across several models from Argyle’s ( 1972 ) ‘Motor Skill Process Model’ (perception-translation-motor response) through to those of Miodusre and Kipperman ( 2002 ) and Scrivener et al. ( 2002 ) (evaluation-modification cycles) which pertain specifically to technology education. All these models bridge pupils’ conceptual-internal representations with their practical-external representations as they move towards an ontologically endurant solution and this is captured by the ‘Re-Application/Transformation Loop’ of the conceptual framework. Given that little is known about where differences might lie, the process set identified by Halfin ( 1973 ) was adopted due to its rigour and the breadth of thinking it encompasses. This set was validated for technology classrooms by Hill and Wicklein ( 1999 ) and used successfully by other studies of pupils technological thinking including Hill ( 1997 ), Kelley ( 2008 ) and Strimel ( 2014 ).

Epistemology dimension

The nature and sources of knowledge play a critical role for pupils when solving technological problems, but these remain far from straightforward to conceptualise. McCormick ( 1997 ) observes that the activity of technology education, and its body of content, can be thought of as ‘procedural knowledge’ and ‘conceptual knowledge’ respectively. Vincenti ( 1990 ), in the context of Engineering, makes the case for descriptive knowledge (things as they currently are) and prescriptive knowledge (of that with is required to meet a desired state) but also recognises knowledge can take on implicit, or tacit forms relating to an individual’s skill, judgement, and practice (Polanyi, 1967 ; Schön, 1992 ; Sternberg, 1999 ; Welch, 1998 ). Arguably, moving from concept to physical solution will demand from pupils a certain level of practical skill and judgement, and Morgan ( 2008 ) observes that procedural knowledge which is explicit in the early stages becomes increasingly implicit with mastery. Notably, in addition to conceptual, procedural and tacit forms of knowledge, there is also evidence that knowledge of principles plays a role. Distinct from impoverished notions of technology as ‘applied science’, Rophol ( 1997 ) shows that it is often technological principles, laws and maxims that are applied during problem solving rather than scientific ones. Frey ( 1989 ) makes similar observations and sees this form of knowledge arising largely from practice. In this study, knowledge of principles involves knowledge of a relationship between things. It is not constrained to those that are represented scientifically.

The conceptual framework finally accounts for pupils’ sources of knowledge during problem solving, building principally on a design knowledge framework of media, community and domain presented by Erkip et al. ( 1997 ). In this study, media includes task information, representations and materials; community includes teachers and peers, and domain relates to prior technological knowledge from within technology lessons and prior personal knowledge from out with technology lessons. Finally, the developing solution is itself recognised a source of knowledge that pupils iteratively engage with and reflect upon, even when it appears that limited progress in being made (Hamel & Elshout, 2000 ).

Methodology

The research question in this study is concerned with differences in the knowledge and intellectual processes used by pupils in moving from a perdurant to an endurant technical solution. From an exploratory stance, this elicits a dualistic activity system involving pupils’ subjective constructions of reality as well as the resultant tangible and more objective material solution. The study does not aim to investigate pupils’ own subjective constructions from an emic perspective, but rather seeks to determine the nature and occurrences of any differences during observable real-time problem-solving activity. As such, content rather than thematic analysis was used (Elo & Kyngäs, 2008 ; Vaismoradi et al., 2013 ) with concurrent data collection to build a composite representation of reality (Gall et al., 2003 , p.14). Complementary data provided insights into study effects, the classrooms and contexts within which problem-solving took place.

This study assumes that should differences exist, these will be discernible in the inferred cognitive processes, external material transformations, interactions and verbalisation (even though this tends to diminish as activity becomes more practical). Absolute and objective observation is not possible. This study also accepts that data gathering and analysis are influenced by theory, researcher fallibility and bias which will be explicitly accounted for as far as possible. Finally, while the conceptual framework provides an analytical starting point, it should not preclude the capture of differences that may lie elsewhere in the data including, for example, process that lie out with those identified by Halfin ( 1973 ).

Participants, selection and grouping

To support transferability, a representative spread of pupils from low, medium and high socio-economic backgrounds took part in this study. Purposeful, four-stage criterion sampling was used (Gall et al., 2003 , p.179). Stage one identified six schools at each socio-economic level from all Scottish secondary schools that presented pupils for one or more technology subjects with the Scottish Qualifications Authority. This was done using socio-economic data from the Scottish Area Deprivation Index, the Carstairs Index and pupil eligibility for subsidised meals. Secondary school catchment areas were used to account for pupil demographics as accurately as possible. All eighteen schools were subsequently ranked with one median drawn from low, medium and high bands of socio-economic deprivation (School 1: Low, School 2: Medium, School 3: High).

One class in each school was then selected from the second year of study prior to pupils making specific subject choices to minimise variations in curricular experience. In total, 3 class teachers and 50 pupils (20 female, 30 male) aged between 12 and 13 years old took part in the study. The group rather than the individual was defined as unit of study to centralise verbal interaction.

None of the pupils participating in this study had experience of group approaches such as co-operative learning and it was likely that groups might experience participation effects including inter-group conflict and interaction effects (Harkins, 1987 ; Sherif et al., 1961 ), social loafing (Salomon & Globerson, 1989 ), free-rider (Strong & Anderson, 1990 ) and status differential effects (Rowell, 2002 ). Relevant also to this study is evidence suggesting that gender effects can take place in untrained groups undertaking practical/material manipulation activities. To maximise interaction between group members and the material solution, thirteen single sex groups averaging four pupils were formed in order to: (1) minimise the marginalisation of girls with boys’ tendency to monopolise materials and apparatus in groups (Conwell et al., 1993 ; Whyte, 1984 ); (2) recognise boys’ tendency to respond more readily to other boys (Webb, 1984 ) and, (3) maximise girls’ opportunities to interact which is seen to erode in mixed groups (Parker & Rennie, 2002 ; Rennie & Parker, 1987 ). Hong et al. ( 2012 ) examines such gender differences in detail specifically within the context of technological problem solving. Teacher participation in group allocation minimised inter-group conflict and interaction effects although groups still experienced naturally fluctuating attrition from pupil absences (School 1 = 17.6%; School 2 = 2.5% and School 3 = 8.8%).

Identification of most and least successful solutions

The research question requires differences to be identified in terms of levels of success. The overall trustworthiness of any differences therefore depends upon the credible identification of the most and least successful solutions from the thirteen produced. Wholly objective assessment of the pupils’ solutions is not possible, and material imperfections in different solutions negated reliable physical testing across the three classes. Moreover, because the researcher earlier observed pupils while problem solving, neutrality of researcher judgement in establishing a rank order of group solutions was equally problematic. Everton and Green ( 1986 ) identify this biasing risk between and early and later stages of research as a form of contamination.

To address these limitations, a Delphi technique was design using the work of Gordon ( 1994 ), Rowe and Wright ( 1999 ) and Yousuf ( 2007 ). This was undertaken anonymously prior to any analysis and, in conjunction with the results of physical testing, enabled the four most successful and four least successful solutions to be confidently identified independently of the researcher. A panel of eight secondary school teachers was convened from schools out with the study. All panel members had expertise in teaching structures with no dependent relationships or conflicts of interest. Following Delphi training, and a threshold level of 75%, the four most and four least successful solutions on outcome alone were identified after two rounds. Qualitative content validity checks confirmed that panel judgements fell within the scope of the accessible information. 37/43 reasons given were ‘High’, with six considered ‘Medium’ because the reasoning was partially speculative. When triangulated with additional evidence from physical testing, two cohorts of four groups were identified and paired to form four dyads (Table 1 ).

Study design

As noted, ‘Structures’ was chosen as a topic area and was new to all participants. It was appropriate for setting well-defined problems and allowed pupils to draw upon a sufficiently wide range of processes and knowledge types in developing a tangible, endurant solution. In discussion with the researcher, teachers did not alter their teaching style and adopted pedagogy and formative interactions that would support independent thinking, reasoning and problem solving. This study involved a learning phase, followed by a problem-solving phase.

In the learning phase, groups engaged over three fifty-minute periods with a unit of work on structures which was developed collaboratively with, and delivered by, the three classroom teachers. This allowed pupils to interact with materials and develop a qualitative understanding of key structural concepts including strength, tension and compression, triangulation, and turning moments. During this time, pupils also acclimatised to the presence of the researcher and recording equipment which helped to reduce any potential Hawthorne effect (Gall et al., 2003 ). Structured observations, teacher de-briefs and questionnaires were used in this phase to capture study effects, unit content coverage and environmental consistency between the three classrooms. Content coverage and environmental consistency were shown to be extremely high. Scores from the unit activity sheets that pupils completed were used to gauge group understanding of key concepts.

The problem-solving phase took place over two circa 50-minute periods (range: 40–52 m) in which pupils responded to a well-defined problem brief. This required them to develop a cantilever bridge enabling travel across a body of water. This bridge would enhance people’s ability to traverse terrain (conditions for being ‘technological’) with maximal span rigidity and minimal deflection (conditions for an ontologically ‘endurant’ solution). All groups had access to the same range and number of materials and resources and were issued with a base board showing water and land on which to develop their solutions.

While video capture was explored in depth (Lomax & Casey, 1998 ), challenges in reliably capturing solution detail resulted in group verbalisation being recorded as audio. This was synchronised with time interval photography and supplemented with structured observer-participant observation that focused on a sub-set of observable processes from the conceptual framework (Halfin, 1973 ). The developing technical solutions were viewed as manifestations of the knowledge and intellectual processes used by pupils at different points in time through their cognitive and material interactions. Photographs captured the results of these interactions in group solutions every 3–4 min but did not capture interactions between pupils. The structured observational approach adopted continuous coding similar to that found in the Flanders System of Interaction analysis (Amatari, 2015 ) and was refined through two pilot studies. During each problem-solving session, groups were observed at least twice between photographs and, following each session, pupil questionnaires, teacher de-briefs and solution videos (360° panoramic pivot about the solution) were completed to support future analysis. Reflexive accounts by the researcher also captured critical events, observer and study effects.

Analytical approach

All data were prepared, time-synchronised and analysed in three stages. Core verbal data (apx. 12h) and photographic data (n = 206) were triangulated with observational and other data against time. The problem-solving phase for each class was broken into a series of 3–4 min samples labelled S = 1, S = 2, S = 3…with durations in each recorded in minutes and seconds. Verbal data were analysed using NVivo software using digital waveforms rather than transcribed files to preserve immediacy, accuracy and minimise levels of interpretation (Wainwright & Russell, 2010 ; Zamawe, 2015 ). Photographic data were coded for the physical developments of the solutions (e.g. adding/removing materials in particular places) allowing solution development to be mapped for different groups over time. Triangulation of data also allowed coding to capture whether individual developments enhanced or detracted from the overall function efficacy of the solution.

The first stage of analysis was immersive, beginning with an initial codebook derived from the conceptual framework. In response to the data this iteratively shifted to a more inductive mode. To sensitise the analysis to differences, the most successful and the least successful groups were compared first as is discussed by Strauss 1987 (Miles & Huberman, 1994 , p.58). Three frameworks of differences emerged from this: (1) epistemic differences, (2) process differences, and (3) social and extrinsic differences. These were then applied to dyads of decreasing contrast and successively  refined in response to how these differences were reflected in the wider data set. Seven complete passes allowed non-profitable codes to be omitted and frameworks to be finalised. A final stage summarised differences across all groups.

Analysis and findings

The analysis and findings are presented in two main parts: (1) findings from the learning phase, and (2) findings from the problem-solving phase. Verbal data forms a core data source throughout and coding includes both counts and durations (in minutes and seconds). Direct quotations are used from verbal data, although the pupils involved in the study were from regions of Scotland with differing and often very strong local dialects. Quotations are therefore presented with dialect effects removed:

Example data excerpt reflecting dialect: “See instead-e all-e-us watchin’, we could all be doin’ su-hum instead-o watchin’ Leanne..” Example data excerpt with dialect removed: “See instead of all of us watching, we could all be doing something instead of watching Leanne..”

Part 1: Findings from the Learning Phase

Both teacher and researcher observation confirmed that pupils in all three classes engaged well with the unit of work (50 pupils across 13 groups) with all 40 content indicators covered by each class. Teachers of classes 1 and 3 commented that the lesson pace was slightly faster than pupils were used to. As expected, different teaching styles and examples were between classes, but all pupils completed the same unit activity sheets. The teacher of class 2, for example, used man-made structures and insect wings to explore triangulation; and the teacher in class 3 talked about the improved stability pupils get by standing with their feet apart. The understanding reflected in activity sheets was very good overall and Table 2 illustrates the percentage of correct responses for each class in relation to each of the three core concept areas.

Though unit activity sheets are not standardised tests, the conditions of administration, scoring, standards for interpretation, fairness and concept validity discussed by Gall et al. ( 2003 , p.xx) were maintained as far as possible. Evidence did not show that representational/stylistic variations by teachers had any discernible effect on pupil understanding and was seen to maintain normality from the pupils’ perspective. Class 3 scored consistently highly across all conceptual areas, although the qualitative understanding of turning moments was least secure for all three classes. Non-completion of selected questions in the task sheets partially explains lower numerical attainment for this concept in class 1 and 2, however, it is unknown if omissions resulted from a lack of understanding. The figures in Table 2 are absence corrected to account for fluctuating pupil attendance at sessions: (17.6% pupil absence across sessions for class 1, compared with 8.8% and 2.5% for classes 3 and 3 respectively). Table 3 illustrates the percentage scores for activity sheets completed by groups in the more and less successful cohorts.

Observational and reflexive data highlighted evidence of some researcher and recorder effects. These were typically associated with pupils’ interest in understanding the roles of the researcher and class teacher, and discussion around what they could say while being recorded. These subsided over time for all but two groups in Class 1, but with no substantive effect on pupils’ technological thinking.

In summary, findings from the learning phase show that: (1) Pupils engagement was high, and all classes covered the core structural concepts in the unit; (2) pupil knowledge and understanding, as measured by activity sheet responses, was very good overall but scores for turning moments were comparatively lower, and (3) study effect subsided quite quickly for all but two groups and there was no evidence showing these to be detrimental to technological thinking. These differences are considered epistemic and are captured in the framework of difference in Fig. 5 .

Part 2: findings from the problem-solving phase

Part 2 begins by describing the differences from comparing the material solutions produced by the most and least successful groups (dyad 1). Subsequent sections report upon the three areas in which difference were found: epistemic differences, process differences and social and extrinsic differences. Each of these sections lead with the analysis from the most contrasting groups (dyad 1) before presenting the resultant framework of difference. They conclude by reporting on how the differences in these frameworks are reflected across the wider data set. As with findings across all sections, findings only account for areas of the conceptual framework in which differences were identified. For processes such as measuring and testing, no difference was found and other processes, such as computing, did not feature for any of the groups.

Differences in the solutions produced by the most & least successful groups (dyad 1)

Group 5′s solution was identified as the most successful and Group7′s solution was identified as the least successful. Overall, both of these groups engaged well with the task and produced cantilevers that are shown in Figs. 2 and 3 . The order in which different parts of the solutions were developed is indicated by colour with the lighter parts appearing earlier in problem solving than the darker parts. Figure 4 shows this cumulative physical development of each solution over time. Both groups shared a similar conceptual basis and employed triangulation above and below the road surface. Figure 4 shows that Group 5′s solution evolved through 36 developments, while Group 7 undertook 23 developments and chose to strip down and restart their solution at the beginning of the second problem solving session. Similarly, groups 6, 11 and 13 removed or rebuilt significant sections of their solution. Neither group 5 or 7 undertook any developments under the rear of the road surface, and the greatest percentage of developments applied to the road surface itself (Group 7: 30.6%; Group 5: 47.8%). For Group 5, it was only developments 5 and 6 (Fig. 2 ) which offered little to no functional structural advantage. All other developments contributed to either triangulation, rigidity or strength through configuration and material choice with no evidence of misconception, which was also noted by the Delphi panel. The orientation, configuration and choice of materials by Group 7 share similarities with Group 5 insofar as each reflected knowledge of a cognate concept or principle (e.g. triangulation). Delphi Panel Member 8 described Group 7′s solution as having a good conceptual basis. Key differences, however, lay in the overall structural integrity of the solution and the underdevelopment of the road surface (Fig. 3 , Dev.1 and Dev.5) which mean that Group 5 achieved a more ontologically endurant solution than Group 7 did. Evidence from Group 7′s discussion (S = 3, 3.34–3.37; S = 3, 3.38–3.39; S = 16, 3.26–3.30) suggests this is partly because of misconception and deficits in knowledge about materials and the task/cantilever requirements. This was also reflected in the group’s activity responses during structures unit in the learning phase. Alongside the photographic evidence and reflexive notes of the researcher, this suggest that there was  some difficultly in translating concepts and ideas into a practical form. This constitutes a difference in tacit-procedural knowledge between Group 5 and Group 7.

‘Group 5 solution schematic’

‘Group 7 solution schematic’

‘Cumulative development of tangible solutions’

Epistemic differences during problem solving

As well as the knowledge differences in the learning phase and the physical solutions, analysis of the most and least successful groups revealed epistemic differences in problem solving activity related to ‘task knowledge’ and ‘knowledge of concepts and principles’. The extent to which ‘knowledge’ can be reliably coded for in this context is limited because it rapidly becomes inseparable from process. Skills are processes which, in turn, are forms of enacted knowledge. Consequently, although Halfin ( 1973 ) defines idea generation as a knowledge generating process using all the senses, attempts to code for this were unsuccessful because it was not possible to ascertain with any confidence where one idea ended, and another began. Coding was possible, however, for ‘prior personal knowledge’, ‘task knowledge’ and ‘prior technological knowledge’. The analysis of these is present along with the resulting framework of epistemic difference with prior personal knowledge omitted on the basis that no differences between groups was found. The final section looks at how epistemic differences are reflected in the activity of the remaining groups.

Epistemic differences between the most & least successful groups (dyad 1)

Task knowledge is the knowledge pupils have of the problem statement and includes relatively objective parameters, conditions, and constraints. One key difference was the extent to which groups explicitly used this to support decision making. Group 5 spent considerably more time than Group 7 discussing what they knew and understood of the task prior to construction (1m10s vs. 8 s) but during construction, had more instances where their knowledge of the task appeared uncertain or was questioned (n = 6 for Group 5 vs. n = 2 for Group 7). Differences were also found in the prior technological knowledge used by groups. This knowledge includes core structural concepts and principles explored in the learning phase. As with task knowledge, Group 5 verbalised this category of knowledge to a far greater extent than Group 7, both apart from, and as part of, formative discussions with the class teacher (18:59 s vs. 14:43 s). In only one instance was the prior technological knowledge of Group 5 incorrect or uncertain compared with four instances for Group 7. These included misconceptions about triangulation and strength despite performing well with these in the learning phase. Furthermore, some instances of erroneous knowledge impacted directly upon solution development. In response to a discussion about rigidity and the physical performance of the road surface, one pupil stated: “Yes, but it is supposed to be able to bend in the middle..” (Group 7, S = 3, 3.34–3.37) meaning that the group did not sufficient attend to this point of structural weakness which resulted in a less endurant solution. No such occurrences took place with Group 5. More prominent and accurate use of this type of knowledge supports stronger application of learning into the problem-solving context and appeared to accompany greater solution integrity.

From these findings, and those from the learning phase, the framework of difference shown in Fig. 5 was developed:

‘Framework of epistemic differences from comparative analysis of Group 5 and 7’

Epistemic differences across all groups (dyads 1–4)

As with dyad 1, the more successful groups in dyads 3 and 4 scored higher (+ 14% and + 20.7%, respectively) in the learning phase compared with their less successful partner groups. This, however, was not seen with dyad 2. The less successful group achieved a higher average score of 86.3% compared with 71% and, despite greater fluctuations in pupil attendance, scored 100% for turning moments compared with 58% for the more successful group. Although comparatively minimal across all groups, more successful groups in each dyad tended to explicitly verbalise technological and task knowledge more than less successful groups. Furthermore, it was more often correct or certain for more successful groups. This was particularly true for dyad 2, although there was some uncertainty about the strongest shapes for given materials in, for example, Group 12 which was the more successful group of dyad 3. The greatest similarity in verbalised task knowledge was observed with the least contrasting dyad, although evidence from concept sketching (Figs. 6 , 7 ) illustrated a shared misunderstanding between both groups of the cantilever and task requirements.

‘Group 2 concept sketch’

‘Group 8 concept sketch’

The differences in tacit-procedural knowledge between Group 5 and 7 were reflected quite consistently across other dyads, with more successful groups showing greater accuracy, skill and judgement in solution construction. The more successful groups in dyads 2 and 3 undertook three material developments that offered little to no functional advantage, and each of the developments these groups undertook correctly embodied knowledge of cognate structural concepts and principles. Notably, Group 8 of dyad 4 was able to achieved this with no structural redundancy at all. Less successful groups, however, were not as secure in their grasp of the functional dependencies and interrelationships between different parts of their structural systems. The starkest example of this was with Group 4 of dyad 3, who explicitly used triangulation but their failure to physically connect it with other parts of the structure rendered the triangulation redundant. Group 2 of dyad 4 were the only group not to triangulate the underside of the road surface. Less successful groups tended to focus slightly more of their material developments in areas of the bridge other than the road surface, whereas the opposite tended to be true for the other groups. Significantly, while all groups in the study included developments that offered little to no functional advantage, it was only in the case of less successful groups that these impaired the overall functional performance of solutions in some way. Table 4 summarises the sustained epistemic difference across all four dyads.

Process differences

Analysis of the most contrasting dyad yielded process differences in: (1) managing (Halfin, 1973 ), (2) planning, and (3) reflection. Groups managed role and task allocation differently, as well as engaging in different approaches to planning aspects of solution development. Reflection, as a process of drawing meaning or conclusions from past events, is not explicitly identified by Halfin or the conceptual framework. Two new forms of reflection for well-defined technological problem solving (declarative reflection and analytical reflection) were therefor developed to account for the differences found. The analysis of the process differences is presented with the resulting framework for this dyad. The final section presents sustained process differences across all groups.

Difference in managing—role & task allocation & adoption (dyad 1)

The autonomous creation of roles and allocation of tasks featured heavily in the activity of Group 5. These typically clustered around agreed tasks such as sketching (S = 2, 1.46), and points where group members were not directly engaged in construction. In total, Group 5 allocated or adopted roles or task on 31 occasions during problem solving compared with only 7 for Group 7. Both groups did so to assist other members (Group 5, S = 16, 3.33–3.38; Group 7, S = 3, 0.37–0.41), to take advantage of certain skills that group members were perceived to possess (Group 5, S = 2, 1.47- 1.49; Group 7, S = 2, 2.03–2.06) and, for one instance in Group 7, to prevent one group member from executing something incorrectly (S = 16, 2.11–2.13). There was evidence, however, that Group 5 moved beyond these quite pragmatic drivers. Member often had more of a choice and, as shown in Excerpt 5, allocation and adoption is mediated by sense of ownership and fairness.

Excerpt 5: Idea Ownership (Sketching) Pupil ?: “You can’t draw on them..” Pupil 1: “You draw Chloe, I can’t draw..” Pupil 2: “I know I can’t draw on them, that’s why I doing them; no, because you, you had the ideas… because you had…” Pupil ?: “(unclear)” Pupil 3: “Just draw your own ideas, right, you can share with mine right…. Right, you draw the thread one, I’ll do the straw thing…” (Group 5, S  =  2, 1.46–1.59)

The effective use of role and task allocation appeared to play an important role in realising an effective technical solution, however, negative managerial traits were perhaps more significant.

Difference in managing—negative managerial traits (dyad 1)

Evidence of differences between Group 5 and 7 were found in relation to: (1) group involvement, and (2) fragmentation of group vision, which were found to be highly interrelated. Negative group involvement accounted for traits of dominance and dismissiveness. For Group 7, this was more prevalent earlier in the problem-solving activity where one group member tended to dominate the process. This pupil tabled 9 out of 11 proposals prior to working with physical materials and, at times, readily dismissed suggestions by other group members (See Excerpt 1). Moreover, ideas and proposals within the group were sometimes poorly communicated (Excerpt 2), which led to a growing level of disenfranchisement for some group members and a fragmented group vision for solution development.

Excerpt 1 Pupil 1:“We could do it that way…” (Pupils continue discussion without acknowledgement) Pupil 1:“You could do that..” Pupil 2:“Shut up, how are we going to do that?” Pupil 1:“Well you’re allowed glue, and you’re allowed scissors..” Several group members: “Shut-up!” (Group 7, S = 1, 2.07–2.28) Excerpt 2 “(Loud inhalation) Watch my brilliant idea… I need scissors.. Are you allowed scissors?” (Group 7, S = 1, 1.36–1.41)

The was some evidence of dismissiveness present with Group 5 also (e.g. S = 9, 1.32–1.46), however, group members were able to voice their ideas which appeared to support a better shared understanding among group members. Notably, Group 5 reached a degree of consensus about what they would do prior to constructing anything, whilst Group 7 did not. Even in these early stages, two of the four members of Group 7 made it very clear that they did not know what was happening (Excerpt 3).

Excerpt 3 Pupil 1: “What are you all up to?” Pupil 2: “Move you” Pupil 4: “No idea” Pupil 2: “You’re allowed to say hell are you not?” Pupil ?: “Helli-yeh” Pupil 2: “Hellilouya” (slight laughter) Pupil 3: “Right so were going to..(unclear) and do that..” Pupil 1: “What are you all up to?” Pupil 2: “Just… I know what he’s thinking of..” Pupil 4: “I don’t have a clue what you’re thinking of..” Pupil 3: “Neither do I..” (Group 7, S = 2, 0.15–0.33)

Occurrence like these contributed to a growing sense of fragmentation in the group. Verbal and observational data show this to have been picked up by the class teacher who tried to encourage and support the group to share and discussed ideas more fully. Despite this, the group lost their sense of shared vision about how to approach a solution and, part way through the first session, two group members attempted to begin developing a separate solution of their own (S-3, 2.52).

The final managerial difference between Group 5 and 7 was the way in which efforts were made to increase the efficiency of solution development. Seen as a positive managerial trait, both groups did this, but it was more frequent and more developed with Group 5. There were four examples of this with Group 7 in the form of simple prompts to speed the process up (E.g. S = 5:3.02–3.04; S = 6:2.22–2.23; S = 11: 1.34–1.35) and 25 examples with Group 5 involving prompts and orchestrating parallel rather than successive activity.

Differences in planning (dyad 1)

Differences emerged in how Group 5 and 7 thought about and prepared for future problem-solving activity. While the complexity of the pupils’ problem-solving prevented cause and effect from being attributed to planning decisions, four areas of difference were identified: (1) determining use of/amount of materials/resources, (2) sequencing, ordering or prioritising, (3) identification of global solution requirements, and (4) working through how an idea should be practically executed. Across both problem-solving sessions, Group 5 spent over three times as long as Group 7 did, engaging in these forms of planning (8m17s vs. 2.23 s), but Group 7 planned on almost twice as many occasions (n = 98 vs. n = 56). Both groups considered the availability of materials for, and matching of materials to, given ideas (e.g. Group 5, S = 5:3.38–3.48; Group 7, S = 4:2.20–2.34; S = 12:1.53–2.00) and both identified global solution requirements. At the start, Group 5 engaged in 12 min of planning in which they read task instructions (S = 1, 0.49–1.49), explored, tested, and compared the available materials (S = 1, 1.49–2.10), and agreed on a starting point. As shown in Excerpt 4, these discussions attempted to integrate thinking on materials, joining methods, placement. As the class teacher observed, Group 7 were eager to begin construction after 4m45s and did so without an agreed starting point. Pupils in this group explored materials in a more reactive way in response to construction.

Excerpt 4 “..a tiny bit of cardboard, right, this is the cardboard, right.. (picks up part) put glue on it so that’s on that, right.. (modelling part orientation) then put glue on it there so it sticks down.. something to stick it down, do you know what I mean?” (Group 5, S = 9, 2.10–2.20)

Despite similar types of planning processes, the planning discourse of Group 5 was more proactive, and this may have minimised inefficiencies and avoidable errors. For Group 7, two group members unintentionally drew the same idea (S = 2, 3.19–3.26), parts were taped in the wrong place (S = 17, 1.26–1.40) and others glued in the wrong order (S = 5, 1.28–1.30 and 1.48–1.56). Such occurrences, however, notably reduced after the group re-started their solution in the second session which also mirrored a 73% drop in poor group involvement. Communication played an important role in planning and there was no evidence of avoidable errors with Group 5.

Differences in reflection (dyad 1)

The most prevent differences in this study were found in how Group 5 and Group 7 reflected upon their developing solutions. Analysis revealed two main forms of reflection that were used differently by groups. ‘Declarative reflection’ lies close to observation and is defined by this study as reflection that does not explicitly reveal anything of a pupil’s knowledge of technical relationships within their solution, e.g.: “that’s not going to be strong…” (Group 7, S = 2, 0.49–0.51). This form of reflection was critical for both groups who used it heuristically to quality assure material developments, but it was used slightly more often by Group 7 (n = 164:4m30s vs. n = 145:4m07s). By contrast, ‘analytical reflection’ is defined as that which does reveal something of a pupil’s knowledge of technical relationships between two or more parts of a solution. Examples of this are shown in Excerpts 5 and 6 where pupils are reflecting upon an attempt made to support the underside of the road surface.

Excerpt 5: “It’s not going to work because it’s in compression and straws bend..” (Group 5, S = 9, 2.3–2.35) Excerpt 6: “no, that’ll be… oh, aye, because that would weight it down and it would go into the water.” (Group 5, S = 14, 3.35–3.38)

Looking across verbal and observational data, there was no consistent pattern to the use of declarative reflection but analytical reflection for both groups was almost exclusively anchored around, and promoted by, the practical enactment of an idea and could be associated with predictions about the future performance of their solution. Overall, both Group 5 and 7 reflected a similar number of times (n = 216 and n = 209, respectively) although the total amount of time spent reflecting was 17% longer for Group 5. This difference in time was accounted for by comparatively more analytical reflection in Group 5 (n = 75:3m47s vs. n = 45:2m10s for Group 7), particularly during the first half of problem solving. It was also interesting that Group 7 engaged with no analytical reflection at all prior to construction.

Findings from process management, planning and reflection led to the framework of difference in Fig. 8 . This also accounts for differences in the amount of time each group reflected upon the task detail, but this was extremely limited (Group 5: n = 7, 26 s; Group 7: n = 5, 10 s).

‘Framework of process differences from comparative analysis of Group 5 and 7’

Process differences across all groups (dyads 1–4)

Task reflection, attempts at increasing efficiency and differences of fragmented vision found with the most contrasting dyad were not sustained across remaining groups. The only sufficiently consistent difference in patterns of solution development was that more successful groups, on average, spent 18% longer in planning and discussion before beginning to construct anything.

Overall, the nature and patterns of good and poor group involvement from dyad 1 were reflected more widely, with some instances of deviation. The more successful group in dyad 4 had more significant and numerous examples of poor group involvement than did the less successful group (n = 16 vs. n = 10), although they made more effective use of roles and task allocation and spent longer engaged in planning processes. Dyad 2 deviated also insofar as the less successful group (13) actually had fewer avoidable errors than Group 6 who accidentally cut the incorrect parts (e.g. S = 15, 2.44–2.47), undertook developments that were not required (e.g. S = 6, 2.11–2.16) and integrated the wrong parts into their solution (e.g. S = 7, 1.10–1.13).

Differences in the nature and use of reflection was one of the most consistently sustained findings between the most and least successful cohorts. All four of the more successful groups engaged more heavily in reflective processes and more of this reflection was analytical in nature. This shows that reflection which explicitly integrates knowledge of technical relationships between different aspects of a solution plays an important role in more successful technical outcomes. Whilst declarative reflection remained important for all groups, it was also less prominent for groups in the less successful cohort. Table 5 summarises the sustained process difference across dyads 1, 2, 3 and 4.

Social & extrinsic differences (dyad 1)

Differences reported in this section lie out with the formal conceptual framework of the study but, nonetheless, were shown to play a role in the technological problem-solving activity of dyad 1. Differences between Group 5 and 7 emerged in three areas: (1) group tension, (2) effects of the classroom competitive dynamic, and (3) study effects. Group tension, which relates to aspects of interaction such as argumentative discourse, raised voices and exasperation, were negligible for Group 5 (n = 4, 0m24s) when compared with Group 7 (n = 38, 2m38s) and related exclusively to pupils having their voiced heard. For group 7, tension was evident during both sessions, but was more significant in the first session before re-starting the solution in session 2 and purposeful attempts to work more collaboratively with the support of the teacher (Group 7, S = 10, 0.36–1.29). Observations revealed that tension was typically caused by pupils failing to carry out practical processes to the standard of other group members, or breaking parts such as the thread supporting the road surface in the 36 th minute of Session 2.

Despite collaborative efforts within groups, there was a sense of competitive dynamic which appeared either to positively bias, negatively bias, or to not affect group activity. This competitive dynamic was present in groups comparing themselves to other groups in the class. Group 7 had 3.7 times as many instances of this as Group 5 with 73% of these negatively affecting the group. These included interference from and with other groups (S = 7, 0.07–0.12), attempting to copy other groups (S = 7, 1.14–1.22) and comparing the solutions of other groups to their own (S = 8, 2.55–2.59). In contrast, Group 5 appeared to be far less affected by perceptions of competition. Around a third of instances were coded as neutral, however, Group 7 experienced more instances of positive competitive effects than Group 5 did (n = 5 vs. n = 1).

Study effects were present for both groups often triggered by the arrival of the researcher at their table to observe or take photographs. The biggest difference in study effects was associated with the audio recorder. Recorder effects for Group 7 were three and half times that of Group 5 involving discussion about how it worked (Group 7, S = 10, 3.04–3.17), or about what was caught or not caught on tape (Group 7, S = 14, 1.01–1.45). Although questionnaire data showed that pupils in Group 5 felt that they talked less in the presence of the recorder, this was not supported by observations, verbal data, or the class teacher. From these findings, the framework of social and extrinsic difference in Fig. 9 was developed.

‘Framework of social & extrinsic differences from comparative analysis of Group 5 and 7’

Social & extrinsic differences across all groups (dyads 1–4)

Most of the social and extrinsic differences identified with Groups 5 and 7 were reflected to greater or lesser extents in other dyads. In addition to less successful groups being more susceptible to researcher and recorder effects, two specific points of interest emerged. Firstly, group tension was considerably more prominent for less successful groups than it was for more successful groups. Although no evidence of a direct relationship was established, tension appeared to accompany poor managerial traits and the changing of group composition (e.g. Group 8, Group 13). The most significant differences in tension were found with dyad 3. No occurrences were found for the most successful group and 29 were seen with the least successful group including aggressive and abrupt communication between pupils involving blame for substandard construction (S = 10, 2.28–2.38), through to name calling (S = 12, 0.20–0.22), arguing (S = 6, 1.46–2.10) and threats of physical violence (S = 11, 3.25–3.29).

Secondly, the more successful groups were influenced by the competitive class dynamic more than the less successful groups were. This is the only sustained finding that directly opposes what was found with dyad 1. These took the form of neutral or negative inter-group effects involving comparing and judging other groups (e.g. Group 6), espionage, copying or suspicion thereof (e.g. Group 6, 8 and 12). Table 6 summarises the sustained social and extrinsic differences across the more and less successful cohorts.

Discussion and Conclusions

This study established and applied three frameworks to capture the epistemic, procedural, and social and extrinsic differences between groups of pupils as they developed solutions to a well-defined technological problem. Social & extrinsic findings revealed higher levels of group tension for the less successful cohort, but that more successful groups elicited more negative responses to the competitive class dynamic created by different groups solving the same problem. Major findings about differences in knowledge and process are discussed. Thereafter, a three-part characterisation of thinking for well-defined technological problem solving is presented in support of pedagogy for Design & Technology classrooms.

The most important of those knowledge differences uncovered were found in: (1) the material development of the solution itself, and (2) the reflective processes used by groups during problem solving. The conceptual framework characterises ‘tacit-procedural knowledge’ as the implicit procedural knowledge embodied in technical skill, accuracy and judgement, and this was further refined in the solutions of more successful groups. Linked to this was the fact that several of the material developments for triangulation and strength were improperly realised by less successful groups which negatively impacted on the functional performance of their solutions. Often, this was despite evidence of a good conceptual understanding of triangulation, tension, and compression in the learning phase. An ontologically endurant solution requires stability over time and lesser developed aspects of tacit-procedural knowledge and knowledge application meant that this was not realised as fully as possible for some groups.

This can be partly explained by the challenge of learning transfer, or more accurately, learning application. Several notable studies have explored these difficulties in technology education (Brown, 2001 ; Dixon & Brown, 2012 ; Kelly & Kellam, 2009 ; Wicklein & Schell, 1995 ), but typically at a subject or interdisciplinary level. The findings of this study suggest that, even when the concepts in a learning unit are tightly aligned with a well-defined problem brief, some pupils find difficulty in applying them within a tangible, material context. It could be argued that more successful groups were better at connecting learning between different contexts associated with the problem-solving task and could apply this with more developed skill and judgement.

The second important knowledge difference arose in the various forms of reflection that groups engaged with. Reflection in this study supports pupils in cycling through the re-application/transformation loop in a similar way to the perception/translation/evaluation blocks of the iterative models of problem solving (Argyle, 1972 ; Miodusre & Kipperman, 2002 ; Scrivener et al., 2002 ). Surprisingly few studies explore ‘reflection’ as a process in technological thinking (Kavousi et al., 2020 ; Luppicini, 2003 ; Lousberg et al., 2020 ), and fewer still in the context of school-level technological problem solving. This study found that more successful groups reflected more frequently, and that more of this reflection was analytical insofar as it explicitly revealed knowledge of technical relationships between different variables or parts of their solution. Such instances are likely to have been powerful in shaping the shared understanding of the group. This type of reflection is significant because it takes place at a deeper level than declarative reflection and is amalgamated with pupils’ subject knowledge and qualitative understanding of their technical solution. This allowed pupils to look back and to predict by explicitly making connections between technical aspects of their solution.

The final area in which important differences were found was management of the problem-solving process which is accounted for by Halfin ( 1973 ) in his mental process set. When analysed, the more successful cohort exploited more positive managerial strategies, and fewer negative traits. They made more extensive and effective use of role and task allocation, spent more time planning ahead and longer in the earlier conceptual phase prior to construction. Other studies have also captured aspects of these for technology education. Hennessy and Murphy ( 1999 ) discuss peer interaction, planning, co-operation and conflict, and changing roles and responsibilities as features of collaboration with significant potential for problem solving in technology. Rowell ( 2002 ), in a study of a single pair of technology pupils, demonstrated the significance of roles and participative decisions as enablers and inhibiters of what pupils take away from learning situations. What was interesting about the groups involved in this study, was that the managerial approaches were collectively more proactive in nature for more successful groups. Less successful groups were generally more reactive to emergent successes or problems during solution development.

The problem-solving activity of pupils in this study was exceptionally complex and a fuller understanding of how these complexities interacted would have to be further explored. Yet, key differences in knowledge and process collectively suggest that effectively solving well-defined technological problems involves a combination of proactive rather than reactive process management, and an ability to make two different types of technology-specific connections: contextual connections and technical connections. Proactively managing is generic and involves planning, sequencing, and resourcing developments beyond those that are immediately in play to minimise avoidable errors with reference to problem parameters. It involves group members through agreed roles and task allocation that, where possible, capitalise on their strengths. Contextual connections involve effectively linking and applying technological knowledge, concepts, and principles to the material context that have been learnt form other contexts out with solution development. This is supported by skill and judgement in the material developments that embody this knowledge. Finally, technical connections appear to be important for better functioning solutions. These are links in understanding that pupils make between different parts of the developing solution that reveal and build knowledge of interrelationships, dependencies and how their solution works. In addition to helping pupils developing effective managerial approaches in group work, this suggests that pedagogical approaches should not assume pupils are simply able to make contextual and technical connections during technological problem solving.  Rather, pedagogy should actively seek to help pupils make both forms of connection explicit in their thinking.

This study has determined that proactive management, contextual and technical connections are important characteristics of the modus operandi of pupils who successfully solve well-defined technological problems. This study does not make any claim about the learning that pupils might have taken from the problem-solving experience. It does, however, provide key findings that teachers can use to support questioning, formative assessment and pedagogies that help pupils in solving well-structured technological problems more effectively.

Ethical approval

Ethical approval for this study was granted by the School of Education Ethics Committee at the University of Glasgow and guided by the British Educational Research Association Ethical Code of Conduct. All necessary permissions and informed consents were gained, and participants knew they could withdraw at any time without giving a reason. The author declares no conflicts of interest in carrying out this study.

Argyle, M. (1972). Anlaysis of the behaviour of an interactor. In A. Morrison & D. McIntyre (Eds.), The social psychology of teaching. Cox & Wyman Ltd.

Google Scholar  

Bartholomew, S. R., & Strimel, G. J. (2018). Factors influencing student success on open-ended design problems. International Journal of Technology and Design Education, 28 (3), 753–770. https://doi.org/10.1007/s10798-017-9415-2 .

Article   Google Scholar  

Brown, D. (2001). Cognitive science concepts and technology teacher education. The Journal of Technology Studies, 27 (1), 33–42. https://doi.org/10.21061/jots.v27i1.a.7 .

Buckley, J., Seery, N., & Canty, D. (2019). Investigating the use of spatial reasoning strategies in geometric problem solving. International Journal of Technology and Design Education, 29 (2), 341–362. https://doi.org/10.1007/s10798-018-9446-3 .

Conwell, C. R., Griffin, S., & Algozzine, B. (1993). Gender and racial differences in unstructured learning groups in science. International Journal of Science Education, 15 (1), 107–115. https://doi.org/10.1080/0950069930150109 .

Custer, R. L. (1995). Examining the dimensions of technology. International Journal of Technology and Design Education, 5 (3), 219–244. https://doi.org/10.1007/BF00769905 .

Custer, R. L., Valesey, B. G., & Burke, B. N. (2001). An Assessment model for a design approach to technological problem solving. Journal of Technology Education, 12 (2), 5–20. https://doi.org/10.21061/jte.v12i2.a.1 .

de Vries, M. J. (2005). The nature of technological knowledge: Philosophical reflections and educational consequences. International Journal of Technology and Design Education, 15 (2), 149–154. https://doi.org/10.1007/s10798-005-8276-2 .

DeLuca, V. W. (1991). Implementing technology education problem-solving activities. Journal of Technology Education, 2 (2), 1–10. https://doi.org/10.21061/jte.v2i2.a.2 .

Dixon, R. A., & Brown, R. A. (2012). Transfer of learning: Connecting concepts during problem solving. Journal of Technology Education, 24 (1), 2–17. https://doi.org/10.21061/jte.v24i1.a.1 .

Doornekamp, B. G. (2001). Designing teaching materials for learning problem solving in technology education. Research in Science & Technological Education, 19 (1), 25–38. https://doi.org/10.1080/02635140120046204 .

Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62 (1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x .

Erkip, F., Demirkan, H., & Pultar, M. (1997). Knowledge acquisition for design education. In IDATER 97 Conference, 1997 (pp. 126-132). Loughborough: Loughborough University.

Everton, C. M., & Green, J. L. (1986). Observation as inquiry and method. In M. C. Wittrock (Ed.), Handbook of research on teaching. (3rd ed., pp. 192–213). MacMillan.

Frey, R. E. (1989). A philosophical framework for understanding technology. Journal of Industrial Teacher Education, 27 (1), 23–35.

Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational Research: an introduction . (7th ed.). Allyn and Bacon.

Gómez Puente, S. M., van Eijck, M., & Jochems, W. (2013). A sampled literature review of design-based learning approaches: A search for key characteristics. International Journal of Technology and Design Education, 23 (3), 717–732. https://doi.org/10.1007/s10798-012-9212-x .

Gordon, T. J. (1994). The delphi method. Futures research methodology, 2 (3), 1–30.

Grubbs, M. E., Strimel, G. J., & Kim, E. (2018). Examining design cognition coding schemes for P-12 engineering/technology education. International Journal of Technology and Design Education, 28 (4), 899–920. https://doi.org/10.1007/s10798-017-9427-y .

Halfin, H. H. (1973). Technology: A process approach. Doctoral Thesis, West Virginia University, West Virginia.

Hamel, R., & Elshout, J. J. (2000). On the development of knowledge during problem solving. European Journal of Cognitive Psychology, 12 (3), 289–322.

Harkins, S. G. (1987). Social loafing and social facilitation. Journal of Experimental Social Psychology, 23 (1), 1–18.

Haupt, G. (2018). Hierarchical thinking: A cognitive tool for guiding coherent decision making in design problem solving. International Journal of Technology and Design Education, 28 (1), 207–237. https://doi.org/10.1007/s10798-016-9381-0 .

Hennessy, S., & Murphy, P. (1999). The potential for collaborative problem solving in design and technology. International Journal of Technology and Design Education, 9 (1), 1–36. https://doi.org/10.1023/A:1008855526312 .

Hill, R. B. (1997). The design of an instrument to assess problem solving activities in technology education. Journal of Technology Education , 9 (1), 31–46.

Hill, R. B., & Wicklein, R. C. (1999). A factor analysis of primary mental processes for technological problem solving. Journal of Industrial Teacher Education, 36 (2), 83–100.

Hong, J.-C., Hwang, M.-Y., Wong, W.-T., Lin, H.-C., & Yau, C.-M. (2012). Gender differences in social cognitive learning at a technological project design. International Journal of Technology and Design Education, 22 (4), 451–472. https://doi.org/10.1007/s10798-011-9152-x .

Jackson, A., & Strimel, G. (2018). Toward a matrix of situated design cognition. CTETE Research Monograph Series, 1 (1), 49–65. https://doi.org/10.21061/ctete-rms.v1.c.3 .

Johnson, S. D. (1997). Learning technological concepts and developing intellectual skills. International Journal of Technology and Design Education, 7 (1–2), 161–180.

Jonassen, D. H. (1997). Instructional design models for well-structured and III-structured problem-solving learning outcomes. Educational Technology Research and Development, 45 (1), 65–94. https://doi.org/10.1007/BF02299613 .

Jones, A. (1997). Recent research in learning technological concepts and processes. International Journal of Technology and Design Education, 7 (1–2), 83–96. https://doi.org/10.1023/A:1008813120391 .

Kavousi, S., Miller, P. A., & Alexander, P. A. (2020). Modeling metacognition in design thinking and design making. International Journal of Technology and Design Education, 30 (4), 709–735. https://doi.org/10.1007/s10798-019-09521-9 .

Kelley, T., & Kellam, N. (2009). A theoretical framework to guide the re-engineering of technology education. Journal of Technology Education, 20 (2), 37–49. https://doi.org/10.21061/jte.v20i2.a.3 .

Kelley, T. R. (2008). Cognitive processes of students participating in engineering-focused design instruction. Journal of Technology Education, 19 (2), 15.

Lavonen, J., Meisalo, V., & Lattu, M. (2002). Collaborative problem solving in a control technology learning environment, a pilot study. International Journal of Technology and Design Education, 12 (2), 139–160. https://doi.org/10.1023/A:1015261004362 .

Lewis, T. (2005). Creativity a framework for the design/problem solving discourse in technology education. Journal of Technology Education . https://doi.org/10.21061/jte.v17i1.a.3 .

Lewis, T. (2009). Creativity in technology education: Providing children with glimpses of their inventive potential. International Journal of Technology and Design Education, 19 (3), 255–268. https://doi.org/10.1007/s10798-008-9051-y .

Liddament, T. (1996). Design and Problem-Solving. In IDATER 1996 Conference, 1996 (pp. 1-5). Loughborough: Loughborough University.

Lomax, H., & Casey, N. (1998). Recording social life: Reflexivity and video methodology. Sociological Research Online, 3 (2), 121–146.

Lousberg, L., Rooij, R., van Jansen, S., Dooren, E., & van der Zaag, E. (2020). Reflection in design education. International Journal of Technology and Design Education, 30 (5), 885–897. https://doi.org/10.1007/s10798-019-09532-6 .

Luppicini, R. (2003). Reflective action instructional design (raid): A designer’s aid. International Journal of Technology and Design Education, 13 (1), 75–82. https://doi.org/10.1023/B:ITDE.0000039569.05754.a8 .

MacPherson, R. T. (1998). Factors affecting technological trouble shooting skills. Journal of Industrial Teacher Education, 35 (4), 1–29.

Mawson, B. (2003). Beyond `the design process’: an alternative pedagogy for technology education. International Journal of Technology and Design Education, 13 (2), 117–128. https://doi.org/10.1023/A:1024186814591 .

McCade, J. (1990). Problem solving: Much more than just design. Journal of Technology Education, 2 (1), 1–13. https://doi.org/10.21061/jte.v2i1.a.5 .

McCormick, R. (1994). The problem solving in technology education (PSTE) project. International Journal of Technology and Design Education, 5 (2), 173–175. https://doi.org/10.1007/BF00766816 .

Mccormick, R. (1997). Conceptual and procedural knowledge. International Journal of Technology and Design Education, 7 (1–2), 161–180.

McCormick, R. (2004). Issues of learning and knowledge in technology education. International Journal of Technology and Design Education, 14 (1), 21–44. https://doi.org/10.1023/B:ITDE.0000007359.81781.7c .

McLellan, R., & Nicholl, B. (2011). “If I was going to design a chair, the last thing I would look at is a chair”: Product analysis and the causes of fixation in students’ design work 11–16 years. International Journal of Technology and Design Education, 21 (1), 71–92. https://doi.org/10.1007/s10798-009-9107-7 .

Middleton, H. (2009). Problem-solving in technology education as an approach to education for sustainable development. International Journal of Technology and Design Education, 19 (2), 187–197. https://doi.org/10.1007/s10798-008-9075-3 .

Miles, B. M., & Huberman, A. M. (1994). Qualitative data analysis: An expanded source book (2nd ed.). California: Sage Publications.

Mioduser, D. (1998). Framework for the study of cognitive and curricular issues of technological problem solving. International Journal of Technology and Design Education, 8 (2), 167–184. https://doi.org/10.1023/A:1008824125352 .

Mioduser, D. (2002). Evaluation/Modification cycles in junior high students’ technological problem solving. International Journal of Technology and Design Education, 12 (2), 123–138. https://doi.org/10.1023/A:1015256928387 .

Mioduser, D., & Dagan, O. (2007). The effect of alternative approaches to design instruction (structural or functional) on students’ mental models of technological design processes. International Journal of Technology and Design Education, 17 (2), 135–148. https://doi.org/10.1007/s10798-006-0004-z .

Morgan, K. (2008). Does Polanyi’s Tacit Knowledge Dimension Exist? In Polanyi Society Conference, 2008 . Chicago: Loyola University.

Morrison-Love, D. (2017). Towards a transformative epistemology of technology education: An epistemology of technology education. Journal of Philosophy of Education, 51 (1), 23–37. https://doi.org/10.1111/1467-9752.12226 .

Murphy, P., & McCormick, R. (1997). Problem solving in science and technology education. Research in Science Education, 27 (3), 461–481. https://doi.org/10.1007/BF02461765 .

Odiri Amatari, V. (2015). The instructional process: a review of flanders’ interaction analysis in a classroom setting. International Journal of Secondary Education, 3 (5), 43–49. https://doi.org/10.11648/j.ijsedu.20150305.11 .

Parker, L. H., & Rennie, L. J. (2002). Teachers’ implementation of gender-inclusive instructional strategies in single-sex and mixed-sex science classrooms. International Journal of Science Education, 24 (9), 881–897. https://doi.org/10.1080/09500690110078860 .

Polanyi, M. (1967). The tacit dimension . Routledge and Kegan Paul.

Rauscher, W. (2011). The technological knowledge used by technology education students in capability tasks. International Journal of Technology and Design Education, 21 (3), 291–305. https://doi.org/10.1007/s10798-010-9120-x .

Relations, U. o. O. I. o. G., & Sherif, M. (1961). Intergroup conflict and cooperation: The Robbers Cave experiment (Vol. 10): University Book Exchange Norman, OK.

Rennie, L. J., & Parker, L. H. (1987). Detecting and accounting for gender differences in mixed-sex and single-sex groupings in science lessons. Educational Review, 39 (1), 65–73. https://doi.org/10.1080/0013191870390107 .

Ropohl, N. (1997). Knowledge types in technology. International Journal of Technology and Design Education, 7 (1–2), 56–72.

Rowe, G., & Wright, G. (1999). The delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 15 (4), 353–375. https://doi.org/10.1016/S0169-2070(99)00018-7 .

Rowell, P. M. (2002). Peer interactions in shared technological activity: A study of participation. International Journal of Technology and Design Education, 12 (1), 1–22. https://doi.org/10.1023/A:1013081115540 .

Salomon, G., & Globerson, T. (1989). When teams do not function the way they ought to. International journal of Educational research, 13 (1), 89–99.

Schaafstal, A., Schraagen, J. M., & van Berl, M. (2000). Cognitive task analysis and innovation of training: The case of structured troubleshooting. Human Factors: The Journal of the Human Factors and Ergonomics Society, 42 (1), 75–86. https://doi.org/10.1518/001872000779656570 .

Schön, D. A. (1992). The reflective practitioner: How professionals think in action . Routledge.

Scrivener, S. A. R., Liang, K. C., & Ball, L. J. (2002). Extending the design problem-solving process model: Requirements and outcomes. In: Common Ground: Proceedings of the 2002 International Conference of the Design Research Society. Staffordshire University Press, Stoke-On-Trent.

Sternberg, R. J. (1999). The theory of successful intelligence. Review of General Psychology, 4 (3), 292–316.

Strimel, G. J. (2014). Engineering design: A cognitive process approach. Doctoral Thesis, Old Dominion University, Norfolk, VA.

Strong, J. T., & Anderson, R. E. (1990). Free-riding in group projects: Control mechanisms and preliminary data. Journal of marketing education, 12 (2), 61–67.

Sung, E., & Kelley, T. R. (2019). Identifying design process patterns: a sequential analysis study of design thinking. International Journal of Technology and Design Education, 29 (2), 283–302. https://doi.org/10.1007/s10798-018-9448-1 .

Twyford, J., & Järvinen, E.-M. (2000). The formation of children’s technological concepts: A study of what it means to do technology from a child’s perspective. Journal of Technology Education, 12 (1), 17.

Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study—qualitative descriptive study. Nursing & Health Sciences, 15 (3), 398–405. https://doi.org/10.1111/nhs.12048 .

Vincenti, W. G. (1990). What engineers know and how they know it: Analytical studies from aeronautical history . The Johns Hopkins University Press.

Wainwright, M. (2010). Using NVivo audio-coding: Practical, sensorial and epistemological considerations . (pp. 1–4). Social Research Update.

Webb, N. M. (1984). Stability of small group interaction and achievement over time. Journal of Educational Psychology, 76 (2), 211.

Welch, M. (1998). Students’ use of three-dimensional modelling while designing and making a solution to a technological problem. International Journal of Technology and Design Education, 8 (3), 241–260. https://doi.org/10.1023/A:1008802927817 .

Whyte, J. (1984). Observing sex stereotypes and interactions in the school lab and workshop. Educational Review, 36 (1), 75–86. https://doi.org/10.1080/0013191840360107 .

Wicklein, R. C., & Schell, J. W. (1995). Case studies of multidisciplinary approaches to integrating mathematics, science and technologyeducation. Journal of Technology Education, 6 (2), 18.

Williams, P. J. (2000). Design: The only methodology of technology. Journal of Technology Education . https://doi.org/10.21061/jte.v11i2.a.4 .

Winkelmann, C., & Hacker, W. (2011). Generic non-technical procedures in design problem solving: Is there any benefit to the clarification of task requirements? International Journal of Technology and Design Education, 21 (4), 395–407. https://doi.org/10.1007/s10798-010-9131-7 .

Xu, M., Williams, P. J., Gu, J., & Zhang, H. (2019). Hotspots and trends of technology education in the international journal of technology and design education: 2000–2018. International Journal of Technology and Design Education . https://doi.org/10.1007/s10798-019-09508-6 .

Yousuf, M. I. (2007). Using experts` opinions through delphi technique. Practical Assessment, Research, and Evaluation, 12 (4), 1–8.

Zamawe, F. (2015). The Implication of Using NVivo software in qualitative data analysis: Evidence-based reflections. Malawi Medical Journal, 27 (1), 13. https://doi.org/10.4314/mmj.v27i1.4 .

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I would like to thank Dr Jane V. Magill, Dr. Alastair D. McPhee and Professor Frank Banks for their support in this work as well as the participating teachers and pupils who made this possible.

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10 Real World Problems That Can Be Solved With Technology

Published on april 24, 2017 at 2:39 pm by sneha shah in lists , news, 5. food –  hershey co. (nyse: hsy ).

Technology in the food industry will not only help produce genetically modified food that promises better nutritional value and is pest-resistant, but could also make the overall food system more organized and safer. Drones could be used to monitor entire farms without the need for a farmer to do it manually. The Internet of Things could be used for crop yield monitoring or better irrigation facilities. 3D Printing will gain popularity in restaurants and candy shops, with the likes of Hershey Co. (NYSE:HSY) already using 3D printing for chocolate designs. Even NASA made a pizza using a 3D printer for astronauts. With technology advancements, it could even be possible to grow food using a nutrient-rich water solution without soil.

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Quantum capital of the world: Emerging field that could solve ‘unsolvable’ problems

Posted: November 2, 2023 | Last updated: November 2, 2023

CHICAGO — Think of a corn maze as a problem. Think of the people in the maze as traditional computers trying to solve the problem. They’re limited to attempting one route at a time.

But what if they could try all of the potential routes at the same time?

THE ‘QUANTUM LEAP’

That’s one way of thinking about the difference between our current computers and quantum computers.

The ones we use today process information using binary digits or “bits” that are either in the state of zero or one, handling one input, or one maze route, at a time.

A quantum computer processes more information faster, using quantum bits – or q-bits. The process is so fast and powerful because the data is in multiple states all at once.

“A little bit like spinning a coin on a table,” said Professor David Awschalom, a University of Chicago physicist and the director of Chicago Quantum Exchange. “Is it heads or is it tails? it’s a combination.”

Awschalom said it means instead of the single answer we might get from a classical computer, a quantum computer can try infinite answers to find the right way out of the maze, or the right way to solve any number of problems.

“So, it means you can address problems that are really unsolvable in today’s technology,” Awschalom said.

PRACTICAL APPLICATIONS

Now imagine if we could apply quantum mechanics, quantum technology, and quantum computing power to real-world problems.

We might find solutions to traffic congestion, identity theft, risk in investing, or detecting diseases like cancer in the earliest stages and then creating the pharmaceuticals to treat them.  

There are many more possible applications, according to Awschalom.

“How do you transport energy efficiently across a country?,” he said. “How does a package delivery service know the fastest way to deliver packages across the nation? So many problems that are very complex are reachable with quantum computers.”

PRIORITY FOR PRITZKER

Quantum technology has the potential to shape the future.  That’s why Illinois Gov. JB Pritzker is focused on making Chicago the quantum capital of the world.

PRITZKER: “It’s the next phase of technological development in the world, not just for the United States, this is a worldwide competition.”

WGN: “How is Chicago going to win this competition with the entire world?”

PRITZKER: “In order to make Chicago the hub of quantum development, you had to have the universities and laboratories willing to work together. The collaboration between them is vital and working with Purdue in Indiana, and University of Wisconsin in Madison, bringing all of that together and having Chicago as the center of that is vital for our future. That didn’t happen accidentally.”

WGN: “A phone call from the governor gets all the universities, gets the labs. You’re the guy who can pull it together.”

PRITZKER: “What I knew is that there are federal dollars, there are private dollars, there are foundation dollars that were available to a city, as state a locale that was making real investments and actually making progress in quantum mechanics and quantum computing. So if the state was willing to step forward with a major investment. We invested $200 million back in 2019, if the state was willing to do that, it would bring enormous attention and it would catalyze those other investments coming here.”

PUBLIC, PRIVATE INVESTMENT CREATE ‘QUANTUM ECOSYSTEM’

Illinois receives two of every $5 the federal government spends on quantum technology. It is home to four of the nation’s ten quantum centers, the most of any state.

“We are the chosen location for the United States government to put a significant amount of its dollars toward quantum development right here in Illinois.”

Private investment is also fueling Chicago’s quantum economy, according to Robin Ficke of World Business Chicago.  

FICKE: “If you look at private investment, we’re number two, so we actually really are the epicenter for interest in quantum.”

LOWE: “What are the factors that are making Chicago a quantum technology capital?”

FICKE: “There are three things. First, we have a deep bench of talent coming out of universities. then when people leave the universities, we have a robust ecosystem that they can interact with and finally when they’re ready to launch their quantum sensing products or computing products, we have a robust and diverse industry base that they can interact with.”

One company on the cutting edge of Chicago’s economic present is in a building that symbolizes the city’s economic past – the Chicago Board of Trade.

At the offices of Infleqtion, 20 employees are building the software for quantum computers. Pranav Gokhale, the company’s vice president of quantum software, says he always thought he’d start a quantum tech company in Silicon Valley.

“But a couple of years into grad school I realized that this is where we’d want to build a company, this is where the talent was, this is where technology [was], and where the business development was,” Gokhale said.  

Chicago is the leader in U.S.-based quantum investments. It ranks only behind California for the number of quantum start-up companies.

“Chicago is becoming the center of that industrial revolution for what quantum technology will bring,” Gokhale said.

The Infleqtion team was celebrating the launch of its new software product this fall.

TOP UNIVERSITIES PROVIDE THE QUANTUM WORKFORCE

Technology industry experts have said the key to any region’s success is the available workforce, and that is where Illinois shines, ranking second in the nation for producing Ph.D. graduates in quantum-related fields.  

Swathi Chandrika, is working at a University of Chicago lab three stories underground. She and other doctoral students are fine-tuning experiments and building the devices that will connect to a 124-mile fiber-optic network running from the university’s campus on Chicago’s South Side to two federally funded labs in the suburbs: Argonne National Laboratory and Fermi National Accelerator Laboratory.

“We’ve built one of the first quantum links or quantum networks between this building, where you’re standing right now, downtown Hyde Park, and Argonne National Laboratories,” Awschalom said. “We’re extending it throughout the state right now, and the idea is can we use this as a testbed for companies to come, bring their technology, try it in the real-world network. There is weather in Chicago, there are big temperature changes, we use optical fibers to transmit quantum information and those change with temperature. Change with vibrations on the Eisenhower (Expressway), right? On the tollways? How does quantum information work in the real world? These are things on which we’re working together with industry to explore.”

DUALITY, CHICAGO QUANTUM EXCHANGE, WORLD BUSINESS CHICAGO CONNECT RESEACH TO BUSINESS

Building quantum connections is also a focus of World Business Chicago CEO Michael Fassnacht.

“Quantum will be ultimately the foundation in 10, 15, 20 years of how we live our lives and how we do business, because it will be the foundation of any computing activity that’s happening,” Fassnacht said. “The great thing about quantum is, if you do it right, you solve real problems that face mankind. It’s not building another dating app, like Silicon Valley likes to do.”

Quantum has become a buzzword in popular culture from the show ‘Quantum Leap’ to Marvel’s movie ‘Quantummania.’ It seems like a concept too big to grasp, but quantum fields explore the smallest particles in the universe. “Technology on the scale of microns and sub-microns even down to the nanometer, almost down to the atomic scale,” Awschalom said.

It’s at that level where those unusual rules of Quantum mechanics exist, the ones that allow for all those possibilities to ‘solve the maze,’ because data exists in two states at once, like the spinning coin.

LESSONS FROM THE PAST

For Pritzker, who is leading Illinois into the quantum future, it’s a story from the not-so-distant past that should guide the state’s next steps.

“I want to analogize it to something else that happened in Illinois, about 30 years ago,” Pritzker said. “That was the development of the browser for the internet.”

It was known as “Mosaic” – the first internet browser to incorporate graphics, text, and hypertext or “links” to other pages. It was the precursor to Netscape, Explorer, and Chrome. It was developed at the National Center for Supercomputing Applications at the University of Illinois, Urbana-Champaign in 1992.

But Mosaic didn’t stay in Illinois, and neither did other tech start-ups.

“Making sure we don’t lose out on this next great opportunity,” Pritzker said. “In Illinois, we lost out 30 years ago at the University of Illinois when the browser got up and left and went to Silicon Valley, when YouTube and PayPal got up and left the University of Illinois and went to California. That’s not happening now. Quantum is the next big thing, and companies are coming to Chicago to take advantage of that.”  

For the latest news, weather, sports, and streaming video, head to WGN-TV.

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As a Teen, She Loved Video Games. Now She’s Using A.I. to Try to Quash Malaria.

Rokhaya Diagne, a 25-year-old A.I. entrepreneur in Senegal, is part of a subset of Africa’s enormous youth population that is confident technology can solve the continent’s biggest problems.

By Dionne Searcey

Reporting on tech-savvy youth from Dakar, Senegal, and its environs.

When she was in her early teens, Rokhaya Diagne would retreat to her brother’s room, where she played online computer games for hours, day after day, until her mother finally got fed up.

“My mom said, ‘This is an addiction,’” Ms. Diagne said. “She said if I didn’t stop, she would send me to the hospital to see a psychiatrist.”

Her mother’s interventions worked. While Ms. Diagne’s passion for computers has, if anything, intensified, she has redirected her energies to higher pursuits than leveling up at Call of Duty.

Now, her goals include using artificial intelligence to help the world eradicate malaria by 2030, a project she is focused on at her health start-up.

Video games “taught me a lot of things,” said Ms. Diagne, 25, a Senegalese computer science major who lives in Dakar, the capital. “They gave me problem-solving skills.”

“I don’t regret playing those things,” she added.

A fast talker in bluejeans and hijab, Ms. Diagne is part of a subset of Africa’s enormous youth population whose lives have been shaped by screens and the internet — and who are connected to the world to a degree that no generation before them could have imagined.

For young Africans interested in technology-related careers, the internet has offered a powerful addition to an education system that some experts worry is hobbling Africa’s ability to take advantage of its young people. While graduating more students than ever before, schools still rely heavily on stand-and-deliver lectures.

The wealth of free online coding boot camps, robotics lessons and lectures from the likes of Stanford, Oxford and M.I.T. are having a big impact across Africa, inspiring careers in engineering and seeding ideas for start-ups.

While some of her cohorts are most passionate about sensor fusion or robotics, Ms. Diagne is into artificial intelligence and machine deep-learning. She helped create an award-winning networking app to meet others with similar interests — like Tinder but for tech nerds. And she founded a start-up called Afyasense (she borrowed “afya,” or health, from Swahili, an East African language) for her disease-detection projects using A.I.

“She is someone with whom talking is a pleasure due to the quality of the questions she asks and also the answers she gives,” said Ismaïla Seck, a leader in Senegal’s growing A.I. community .

Like many other young people in Africa’s tech boom, Ms. Diagne is at the center of overlapping phenomena on the continent — a growing, educated middle class raising even more educated children who, with each tap on a keyboard, have adopted a sense that the continent’s biggest problems can be solved.

Ms. Diagne wants to use A.I. to improve health outcomes in the region, a choice she made after a range of childhood illnesses landed her in Dakar hospitals, which struggled to provide consistent, quality care.

“I know the mistakes that are unfortunately made,” she said.

Ms. Diagne’s drive has earned her recognition. Her malaria project recently won an award at an A.I. conference in Ghana and a national award in Senegal for social entrepreneurship, as well as $8,000 in funding.

As a child, she said she was reserved but always has had a huge appetite for research, fed by her father, a retired literature professor and writer. When faced with his daughter’s questions about how the world worked or about her Muslim faith, he would make her try to find the answer herself. He rewarded her with apples, still her favorite fruit.

She enrolled at the École Supérieure Polytechnique de Dakar as a biology major and scored an internship at the Principal Hospital of Dakar. But days of reviewing lab samples helped her realize that kind of work wasn’t for her.

“I wanted way more challenges than fearing the bacteria in my body,” she said. “What I wanted was innovation and being able to create and use my brain for something instead of predictive results that I just followed.”

Dejected that she had made the wrong choice, Ms. Diagne dropped out of school and spent a year plotting her next steps.

She recalled something her brother used to tell her: Do things that are harder because there’s less competition. She picked bioinformatics, the science of both the storing of complex biological data and of analyzing it to find new insights. The options for studying it in Senegal were extremely limited.

But the Dakar American University of Science and Technology had opened and offered a major in computer science, a field she decided would offer a solid foundation for future studies in bioinformatics.

The university’s approach emphasizes applied learning, meaning instructors assign projects to students and expect them to finish largely on their own. And the assignments always aim to solve a local problem.

One project tasked students with building a drone capable of carrying a 100-kilogram payload a distance of 10 kilometers, an act that could help relieve the polluting congestion of trucks outside Dakar’s port. Some of the university’s joint projects already have yielded promising start-ups such as Solarbox , which began as an assignment to build a solar-powered electric motorbike.

Ms. Diagne, who is now a senior, was assigned to send an underwater drone to collect information about fish as well as seagrass, plants that absorb carbon.

“When I started, I didn’t even know what seagrass was,” she said. “I’d only seen an underwater drone in movies. I didn’t even know the difference between types of fish.”

She threw herself into the project, even hiring a fisherman she spotted on the beach to teach her to fish so she could learn more about various species from someone who knew firsthand. Her team is moving on to the next phase: building their own underwater drone.

As she was looking for another project, she learned that global health officials were working to eradicate malaria before the decade is over. One of Senegal’s biggest health problems is the lack of quick and reliable malaria tests in rural areas. So she set out to design a better system of identifying positive cases.

Ms. Diagne thought back to her boredom in the hospital lab, examining biological sample after sample. That rote act seemed tailor made for A.I. to tackle.

First, she needed to find a lab that would give her a large set of malaria-infected cells that she could train A.I. to read. But some labs in Senegal are accustomed to sharing data only with researchers from abroad.

“They will openly give information to those people, but when it comes to little Africans like me who are still learning, they don’t want to help us,” Ms. Diagne said.

Her school helped her find a lab operator who gave her a cell data set that she fed into a deep learning tool, training it to spot positive cases. Users will plug microscopes into a laptop loaded with her A.I. program — including 3D-printed microscopes that are inexpensive and small enough to be deployed in rural areas.

As her malaria project gets closer to going to market, Ms. Diagne already knows what she wants to undertake next: using A.I. to detect cancer cells.

Ms. Diagne has relied on her university’s leaders and on West Africa’s growing tech community, who have been eager to offer advice as her projects earn recognition.

“They’ve been pushing me so that I can get out there and show to the world what I do,” she said. “Well, they haven’t succeed in that part yet.”

But she’s moving in that direction. The Ghana A.I. conference was her first trip abroad, and later this month she will travel to Switzerland for an innovators training program to get more help launching her malaria project.

And she’s ready to lend a hand to those coming up behind her.

“A lot of people are reaching out to me, saying, ‘how did you do this, how did you do that,’” she said. “I can mentor them and show them the way.”

Dionne Searcey is part of a team that won the 2020 Pulitzer Prize for international reporting and author of the book, " In Pursuit of Disobedient Women ."  More about Dionne Searcey

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