research on practical problem solving shows that

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• Published: 11 January 2023

The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature

• Enwei Xu   ORCID: orcid.org/0000-0001-6424-8169 1 ,
• Wei Wang 1 &
• Qingxia Wang 1  

Humanities and Social Sciences Communications volume  10 , Article number:  16 ( 2023 ) Cite this article

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Collaborative problem-solving has been widely embraced in the classroom instruction of critical thinking, which is regarded as the core of curriculum reform based on key competencies in the field of education as well as a key competence for learners in the 21st century. However, the effectiveness of collaborative problem-solving in promoting students’ critical thinking remains uncertain. This current research presents the major findings of a meta-analysis of 36 pieces of the literature revealed in worldwide educational periodicals during the 21st century to identify the effectiveness of collaborative problem-solving in promoting students’ critical thinking and to determine, based on evidence, whether and to what extent collaborative problem solving can result in a rise or decrease in critical thinking. The findings show that (1) collaborative problem solving is an effective teaching approach to foster students’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]); (2) in respect to the dimensions of critical thinking, collaborative problem solving can significantly and successfully enhance students’ attitudinal tendencies (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI[0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI[0.58, 0.82]); and (3) the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have an impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. On the basis of these results, recommendations are made for further study and instruction to better support students’ critical thinking in the context of collaborative problem-solving.

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Introduction.

Although critical thinking has a long history in research, the concept of critical thinking, which is regarded as an essential competence for learners in the 21st century, has recently attracted more attention from researchers and teaching practitioners (National Research Council, 2012 ). Critical thinking should be the core of curriculum reform based on key competencies in the field of education (Peng and Deng, 2017 ) because students with critical thinking can not only understand the meaning of knowledge but also effectively solve practical problems in real life even after knowledge is forgotten (Kek and Huijser, 2011 ). The definition of critical thinking is not universal (Ennis, 1989 ; Castle, 2009 ; Niu et al., 2013 ). In general, the definition of critical thinking is a self-aware and self-regulated thought process (Facione, 1990 ; Niu et al., 2013 ). It refers to the cognitive skills needed to interpret, analyze, synthesize, reason, and evaluate information as well as the attitudinal tendency to apply these abilities (Halpern, 2001 ). The view that critical thinking can be taught and learned through curriculum teaching has been widely supported by many researchers (e.g., Kuncel, 2011 ; Leng and Lu, 2020 ), leading to educators’ efforts to foster it among students. In the field of teaching practice, there are three types of courses for teaching critical thinking (Ennis, 1989 ). The first is an independent curriculum in which critical thinking is taught and cultivated without involving the knowledge of specific disciplines; the second is an integrated curriculum in which critical thinking is integrated into the teaching of other disciplines as a clear teaching goal; and the third is a mixed curriculum in which critical thinking is taught in parallel to the teaching of other disciplines for mixed teaching training. Furthermore, numerous measuring tools have been developed by researchers and educators to measure critical thinking in the context of teaching practice. These include standardized measurement tools, such as WGCTA, CCTST, CCTT, and CCTDI, which have been verified by repeated experiments and are considered effective and reliable by international scholars (Facione and Facione, 1992 ). In short, descriptions of critical thinking, including its two dimensions of attitudinal tendency and cognitive skills, different types of teaching courses, and standardized measurement tools provide a complex normative framework for understanding, teaching, and evaluating critical thinking.

Cultivating critical thinking in curriculum teaching can start with a problem, and one of the most popular critical thinking instructional approaches is problem-based learning (Liu et al., 2020 ). Duch et al. ( 2001 ) noted that problem-based learning in group collaboration is progressive active learning, which can improve students’ critical thinking and problem-solving skills. Collaborative problem-solving is the organic integration of collaborative learning and problem-based learning, which takes learners as the center of the learning process and uses problems with poor structure in real-world situations as the starting point for the learning process (Liang et al., 2017 ). Students learn the knowledge needed to solve problems in a collaborative group, reach a consensus on problems in the field, and form solutions through social cooperation methods, such as dialogue, interpretation, questioning, debate, negotiation, and reflection, thus promoting the development of learners’ domain knowledge and critical thinking (Cindy, 2004 ; Liang et al., 2017 ).

Collaborative problem-solving has been widely used in the teaching practice of critical thinking, and several studies have attempted to conduct a systematic review and meta-analysis of the empirical literature on critical thinking from various perspectives. However, little attention has been paid to the impact of collaborative problem-solving on critical thinking. Therefore, the best approach for developing and enhancing critical thinking throughout collaborative problem-solving is to examine how to implement critical thinking instruction; however, this issue is still unexplored, which means that many teachers are incapable of better instructing critical thinking (Leng and Lu, 2020 ; Niu et al., 2013 ). For example, Huber ( 2016 ) provided the meta-analysis findings of 71 publications on gaining critical thinking over various time frames in college with the aim of determining whether critical thinking was truly teachable. These authors found that learners significantly improve their critical thinking while in college and that critical thinking differs with factors such as teaching strategies, intervention duration, subject area, and teaching type. The usefulness of collaborative problem-solving in fostering students’ critical thinking, however, was not determined by this study, nor did it reveal whether there existed significant variations among the different elements. A meta-analysis of 31 pieces of educational literature was conducted by Liu et al. ( 2020 ) to assess the impact of problem-solving on college students’ critical thinking. These authors found that problem-solving could promote the development of critical thinking among college students and proposed establishing a reasonable group structure for problem-solving in a follow-up study to improve students’ critical thinking. Additionally, previous empirical studies have reached inconclusive and even contradictory conclusions about whether and to what extent collaborative problem-solving increases or decreases critical thinking levels. As an illustration, Yang et al. ( 2008 ) carried out an experiment on the integrated curriculum teaching of college students based on a web bulletin board with the goal of fostering participants’ critical thinking in the context of collaborative problem-solving. These authors’ research revealed that through sharing, debating, examining, and reflecting on various experiences and ideas, collaborative problem-solving can considerably enhance students’ critical thinking in real-life problem situations. In contrast, collaborative problem-solving had a positive impact on learners’ interaction and could improve learning interest and motivation but could not significantly improve students’ critical thinking when compared to traditional classroom teaching, according to research by Naber and Wyatt ( 2014 ) and Sendag and Odabasi ( 2009 ) on undergraduate and high school students, respectively.

The above studies show that there is inconsistency regarding the effectiveness of collaborative problem-solving in promoting students’ critical thinking. Therefore, it is essential to conduct a thorough and trustworthy review to detect and decide whether and to what degree collaborative problem-solving can result in a rise or decrease in critical thinking. Meta-analysis is a quantitative analysis approach that is utilized to examine quantitative data from various separate studies that are all focused on the same research topic. This approach characterizes the effectiveness of its impact by averaging the effect sizes of numerous qualitative studies in an effort to reduce the uncertainty brought on by independent research and produce more conclusive findings (Lipsey and Wilson, 2001 ).

This paper used a meta-analytic approach and carried out a meta-analysis to examine the effectiveness of collaborative problem-solving in promoting students’ critical thinking in order to make a contribution to both research and practice. The following research questions were addressed by this meta-analysis:

What is the overall effect size of collaborative problem-solving in promoting students’ critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills)?

How are the disparities between the study conclusions impacted by various moderating variables if the impacts of various experimental designs in the included studies are heterogeneous?

This research followed the strict procedures (e.g., database searching, identification, screening, eligibility, merging, duplicate removal, and analysis of included studies) of Cooper’s ( 2010 ) proposed meta-analysis approach for examining quantitative data from various separate studies that are all focused on the same research topic. The relevant empirical research that appeared in worldwide educational periodicals within the 21st century was subjected to this meta-analysis using Rev-Man 5.4. The consistency of the data extracted separately by two researchers was tested using Cohen’s kappa coefficient, and a publication bias test and a heterogeneity test were run on the sample data to ascertain the quality of this meta-analysis.

Data sources and search strategies

There were three stages to the data collection process for this meta-analysis, as shown in Fig. 1 , which shows the number of articles included and eliminated during the selection process based on the statement and study eligibility criteria.

This flowchart shows the number of records identified, included and excluded in the article.

First, the databases used to systematically search for relevant articles were the journal papers of the Web of Science Core Collection and the Chinese Core source journal, as well as the Chinese Social Science Citation Index (CSSCI) source journal papers included in CNKI. These databases were selected because they are credible platforms that are sources of scholarly and peer-reviewed information with advanced search tools and contain literature relevant to the subject of our topic from reliable researchers and experts. The search string with the Boolean operator used in the Web of Science was “TS = (((“critical thinking” or “ct” and “pretest” or “posttest”) or (“critical thinking” or “ct” and “control group” or “quasi experiment” or “experiment”)) and (“collaboration” or “collaborative learning” or “CSCL”) and (“problem solving” or “problem-based learning” or “PBL”))”. The research area was “Education Educational Research”, and the search period was “January 1, 2000, to December 30, 2021”. A total of 412 papers were obtained. The search string with the Boolean operator used in the CNKI was “SU = (‘critical thinking’*‘collaboration’ + ‘critical thinking’*‘collaborative learning’ + ‘critical thinking’*‘CSCL’ + ‘critical thinking’*‘problem solving’ + ‘critical thinking’*‘problem-based learning’ + ‘critical thinking’*‘PBL’ + ‘critical thinking’*‘problem oriented’) AND FT = (‘experiment’ + ‘quasi experiment’ + ‘pretest’ + ‘posttest’ + ‘empirical study’)” (translated into Chinese when searching). A total of 56 studies were found throughout the search period of “January 2000 to December 2021”. From the databases, all duplicates and retractions were eliminated before exporting the references into Endnote, a program for managing bibliographic references. In all, 466 studies were found.

Second, the studies that matched the inclusion and exclusion criteria for the meta-analysis were chosen by two researchers after they had reviewed the abstracts and titles of the gathered articles, yielding a total of 126 studies.

Third, two researchers thoroughly reviewed each included article’s whole text in accordance with the inclusion and exclusion criteria. Meanwhile, a snowball search was performed using the references and citations of the included articles to ensure complete coverage of the articles. Ultimately, 36 articles were kept.

Two researchers worked together to carry out this entire process, and a consensus rate of almost 94.7% was reached after discussion and negotiation to clarify any emerging differences.

Eligibility criteria

Since not all the retrieved studies matched the criteria for this meta-analysis, eligibility criteria for both inclusion and exclusion were developed as follows:

The publication language of the included studies was limited to English and Chinese, and the full text could be obtained. Articles that did not meet the publication language and articles not published between 2000 and 2021 were excluded.

The research design of the included studies must be empirical and quantitative studies that can assess the effect of collaborative problem-solving on the development of critical thinking. Articles that could not identify the causal mechanisms by which collaborative problem-solving affects critical thinking, such as review articles and theoretical articles, were excluded.

The research method of the included studies must feature a randomized control experiment or a quasi-experiment, or a natural experiment, which have a higher degree of internal validity with strong experimental designs and can all plausibly provide evidence that critical thinking and collaborative problem-solving are causally related. Articles with non-experimental research methods, such as purely correlational or observational studies, were excluded.

The participants of the included studies were only students in school, including K-12 students and college students. Articles in which the participants were non-school students, such as social workers or adult learners, were excluded.

The research results of the included studies must mention definite signs that may be utilized to gauge critical thinking’s impact (e.g., sample size, mean value, or standard deviation). Articles that lacked specific measurement indicators for critical thinking and could not calculate the effect size were excluded.

Data coding design

In order to perform a meta-analysis, it is necessary to collect the most important information from the articles, codify that information’s properties, and convert descriptive data into quantitative data. Therefore, this study designed a data coding template (see Table 1 ). Ultimately, 16 coding fields were retained.

The designed data-coding template consisted of three pieces of information. Basic information about the papers was included in the descriptive information: the publishing year, author, serial number, and title of the paper.

The variable information for the experimental design had three variables: the independent variable (instruction method), the dependent variable (critical thinking), and the moderating variable (learning stage, teaching type, intervention duration, learning scaffold, group size, measuring tool, and subject area). Depending on the topic of this study, the intervention strategy, as the independent variable, was coded into collaborative and non-collaborative problem-solving. The dependent variable, critical thinking, was coded as a cognitive skill and an attitudinal tendency. And seven moderating variables were created by grouping and combining the experimental design variables discovered within the 36 studies (see Table 1 ), where learning stages were encoded as higher education, high school, middle school, and primary school or lower; teaching types were encoded as mixed courses, integrated courses, and independent courses; intervention durations were encoded as 0–1 weeks, 1–4 weeks, 4–12 weeks, and more than 12 weeks; group sizes were encoded as 2–3 persons, 4–6 persons, 7–10 persons, and more than 10 persons; learning scaffolds were encoded as teacher-supported learning scaffold, technique-supported learning scaffold, and resource-supported learning scaffold; measuring tools were encoded as standardized measurement tools (e.g., WGCTA, CCTT, CCTST, and CCTDI) and self-adapting measurement tools (e.g., modified or made by researchers); and subject areas were encoded according to the specific subjects used in the 36 included studies.

The data information contained three metrics for measuring critical thinking: sample size, average value, and standard deviation. It is vital to remember that studies with various experimental designs frequently adopt various formulas to determine the effect size. And this paper used Morris’ proposed standardized mean difference (SMD) calculation formula ( 2008 , p. 369; see Supplementary Table S3 ).

Procedure for extracting and coding data

According to the data coding template (see Table 1 ), the 36 papers’ information was retrieved by two researchers, who then entered them into Excel (see Supplementary Table S1 ). The results of each study were extracted separately in the data extraction procedure if an article contained numerous studies on critical thinking, or if a study assessed different critical thinking dimensions. For instance, Tiwari et al. ( 2010 ) used four time points, which were viewed as numerous different studies, to examine the outcomes of critical thinking, and Chen ( 2013 ) included the two outcome variables of attitudinal tendency and cognitive skills, which were regarded as two studies. After discussion and negotiation during data extraction, the two researchers’ consistency test coefficients were roughly 93.27%. Supplementary Table S2 details the key characteristics of the 36 included articles with 79 effect quantities, including descriptive information (e.g., the publishing year, author, serial number, and title of the paper), variable information (e.g., independent variables, dependent variables, and moderating variables), and data information (e.g., mean values, standard deviations, and sample size). Following that, testing for publication bias and heterogeneity was done on the sample data using the Rev-Man 5.4 software, and then the test results were used to conduct a meta-analysis.

Publication bias test

When the sample of studies included in a meta-analysis does not accurately reflect the general status of research on the relevant subject, publication bias is said to be exhibited in this research. The reliability and accuracy of the meta-analysis may be impacted by publication bias. Due to this, the meta-analysis needs to check the sample data for publication bias (Stewart et al., 2006 ). A popular method to check for publication bias is the funnel plot; and it is unlikely that there will be publishing bias when the data are equally dispersed on either side of the average effect size and targeted within the higher region. The data are equally dispersed within the higher portion of the efficient zone, consistent with the funnel plot connected with this analysis (see Fig. 2 ), indicating that publication bias is unlikely in this situation.

This funnel plot shows the result of publication bias of 79 effect quantities across 36 studies.

Heterogeneity test

To select the appropriate effect models for the meta-analysis, one might use the results of a heterogeneity test on the data effect sizes. In a meta-analysis, it is common practice to gauge the degree of data heterogeneity using the I 2 value, and I 2  ≥ 50% is typically understood to denote medium-high heterogeneity, which calls for the adoption of a random effect model; if not, a fixed effect model ought to be applied (Lipsey and Wilson, 2001 ). The findings of the heterogeneity test in this paper (see Table 2 ) revealed that I 2 was 86% and displayed significant heterogeneity ( P  < 0.01). To ensure accuracy and reliability, the overall effect size ought to be calculated utilizing the random effect model.

The analysis of the overall effect size

This meta-analysis utilized a random effect model to examine 79 effect quantities from 36 studies after eliminating heterogeneity. In accordance with Cohen’s criterion (Cohen, 1992 ), it is abundantly clear from the analysis results, which are shown in the forest plot of the overall effect (see Fig. 3 ), that the cumulative impact size of cooperative problem-solving is 0.82, which is statistically significant ( z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]), and can encourage learners to practice critical thinking.

This forest plot shows the analysis result of the overall effect size across 36 studies.

In addition, this study examined two distinct dimensions of critical thinking to better understand the precise contributions that collaborative problem-solving makes to the growth of critical thinking. The findings (see Table 3 ) indicate that collaborative problem-solving improves cognitive skills (ES = 0.70) and attitudinal tendency (ES = 1.17), with significant intergroup differences (chi 2  = 7.95, P  < 0.01). Although collaborative problem-solving improves both dimensions of critical thinking, it is essential to point out that the improvements in students’ attitudinal tendency are much more pronounced and have a significant comprehensive effect (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]), whereas gains in learners’ cognitive skill are slightly improved and are just above average. (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

The analysis of moderator effect size

The whole forest plot’s 79 effect quantities underwent a two-tailed test, which revealed significant heterogeneity ( I 2  = 86%, z  = 12.78, P  < 0.01), indicating differences between various effect sizes that may have been influenced by moderating factors other than sampling error. Therefore, exploring possible moderating factors that might produce considerable heterogeneity was done using subgroup analysis, such as the learning stage, learning scaffold, teaching type, group size, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, in order to further explore the key factors that influence critical thinking. The findings (see Table 4 ) indicate that various moderating factors have advantageous effects on critical thinking. In this situation, the subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), learning scaffold (chi 2  = 9.03, P  < 0.01), and teaching type (chi 2  = 7.20, P  < 0.05) are all significant moderators that can be applied to support the cultivation of critical thinking. However, since the learning stage and the measuring tools did not significantly differ among intergroup (chi 2  = 3.15, P  = 0.21 > 0.05, and chi 2  = 0.08, P  = 0.78 > 0.05), we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving. These are the precise outcomes, as follows:

Various learning stages influenced critical thinking positively, without significant intergroup differences (chi 2  = 3.15, P  = 0.21 > 0.05). High school was first on the list of effect sizes (ES = 1.36, P  < 0.01), then higher education (ES = 0.78, P  < 0.01), and middle school (ES = 0.73, P  < 0.01). These results show that, despite the learning stage’s beneficial influence on cultivating learners’ critical thinking, we are unable to explain why it is essential for cultivating critical thinking in the context of collaborative problem-solving.

Different teaching types had varying degrees of positive impact on critical thinking, with significant intergroup differences (chi 2  = 7.20, P  < 0.05). The effect size was ranked as follows: mixed courses (ES = 1.34, P  < 0.01), integrated courses (ES = 0.81, P  < 0.01), and independent courses (ES = 0.27, P  < 0.01). These results indicate that the most effective approach to cultivate critical thinking utilizing collaborative problem solving is through the teaching type of mixed courses.

Various intervention durations significantly improved critical thinking, and there were significant intergroup differences (chi 2  = 12.18, P  < 0.01). The effect sizes related to this variable showed a tendency to increase with longer intervention durations. The improvement in critical thinking reached a significant level (ES = 0.85, P  < 0.01) after more than 12 weeks of training. These findings indicate that the intervention duration and critical thinking’s impact are positively correlated, with a longer intervention duration having a greater effect.

Different learning scaffolds influenced critical thinking positively, with significant intergroup differences (chi 2  = 9.03, P  < 0.01). The resource-supported learning scaffold (ES = 0.69, P  < 0.01) acquired a medium-to-higher level of impact, the technique-supported learning scaffold (ES = 0.63, P  < 0.01) also attained a medium-to-higher level of impact, and the teacher-supported learning scaffold (ES = 0.92, P  < 0.01) displayed a high level of significant impact. These results show that the learning scaffold with teacher support has the greatest impact on cultivating critical thinking.

Various group sizes influenced critical thinking positively, and the intergroup differences were statistically significant (chi 2  = 8.77, P  < 0.05). Critical thinking showed a general declining trend with increasing group size. The overall effect size of 2–3 people in this situation was the biggest (ES = 0.99, P  < 0.01), and when the group size was greater than 7 people, the improvement in critical thinking was at the lower-middle level (ES < 0.5, P  < 0.01). These results show that the impact on critical thinking is positively connected with group size, and as group size grows, so does the overall impact.

Various measuring tools influenced critical thinking positively, with significant intergroup differences (chi 2  = 0.08, P  = 0.78 > 0.05). In this situation, the self-adapting measurement tools obtained an upper-medium level of effect (ES = 0.78), whereas the complete effect size of the standardized measurement tools was the largest, achieving a significant level of effect (ES = 0.84, P  < 0.01). These results show that, despite the beneficial influence of the measuring tool on cultivating critical thinking, we are unable to explain why it is crucial in fostering the growth of critical thinking by utilizing the approach of collaborative problem-solving.

Different subject areas had a greater impact on critical thinking, and the intergroup differences were statistically significant (chi 2  = 13.36, P  < 0.05). Mathematics had the greatest overall impact, achieving a significant level of effect (ES = 1.68, P  < 0.01), followed by science (ES = 1.25, P  < 0.01) and medical science (ES = 0.87, P  < 0.01), both of which also achieved a significant level of effect. Programming technology was the least effective (ES = 0.39, P  < 0.01), only having a medium-low degree of effect compared to education (ES = 0.72, P  < 0.01) and other fields (such as language, art, and social sciences) (ES = 0.58, P  < 0.01). These results suggest that scientific fields (e.g., mathematics, science) may be the most effective subject areas for cultivating critical thinking utilizing the approach of collaborative problem-solving.

The effectiveness of collaborative problem solving with regard to teaching critical thinking

According to this meta-analysis, using collaborative problem-solving as an intervention strategy in critical thinking teaching has a considerable amount of impact on cultivating learners’ critical thinking as a whole and has a favorable promotional effect on the two dimensions of critical thinking. According to certain studies, collaborative problem solving, the most frequently used critical thinking teaching strategy in curriculum instruction can considerably enhance students’ critical thinking (e.g., Liang et al., 2017 ; Liu et al., 2020 ; Cindy, 2004 ). This meta-analysis provides convergent data support for the above research views. Thus, the findings of this meta-analysis not only effectively address the first research query regarding the overall effect of cultivating critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills) utilizing the approach of collaborative problem-solving, but also enhance our confidence in cultivating critical thinking by using collaborative problem-solving intervention approach in the context of classroom teaching.

Furthermore, the associated improvements in attitudinal tendency are much stronger, but the corresponding improvements in cognitive skill are only marginally better. According to certain studies, cognitive skill differs from the attitudinal tendency in classroom instruction; the cultivation and development of the former as a key ability is a process of gradual accumulation, while the latter as an attitude is affected by the context of the teaching situation (e.g., a novel and exciting teaching approach, challenging and rewarding tasks) (Halpern, 2001 ; Wei and Hong, 2022 ). Collaborative problem-solving as a teaching approach is exciting and interesting, as well as rewarding and challenging; because it takes the learners as the focus and examines problems with poor structure in real situations, and it can inspire students to fully realize their potential for problem-solving, which will significantly improve their attitudinal tendency toward solving problems (Liu et al., 2020 ). Similar to how collaborative problem-solving influences attitudinal tendency, attitudinal tendency impacts cognitive skill when attempting to solve a problem (Liu et al., 2020 ; Zhang et al., 2022 ), and stronger attitudinal tendencies are associated with improved learning achievement and cognitive ability in students (Sison, 2008 ; Zhang et al., 2022 ). It can be seen that the two specific dimensions of critical thinking as well as critical thinking as a whole are affected by collaborative problem-solving, and this study illuminates the nuanced links between cognitive skills and attitudinal tendencies with regard to these two dimensions of critical thinking. To fully develop students’ capacity for critical thinking, future empirical research should pay closer attention to cognitive skills.

The moderating effects of collaborative problem solving with regard to teaching critical thinking

In order to further explore the key factors that influence critical thinking, exploring possible moderating effects that might produce considerable heterogeneity was done using subgroup analysis. The findings show that the moderating factors, such as the teaching type, learning stage, group size, learning scaffold, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, could all support the cultivation of collaborative problem-solving in critical thinking. Among them, the effect size differences between the learning stage and measuring tool are not significant, which does not explain why these two factors are crucial in supporting the cultivation of critical thinking utilizing the approach of collaborative problem-solving.

In terms of the learning stage, various learning stages influenced critical thinking positively without significant intergroup differences, indicating that we are unable to explain why it is crucial in fostering the growth of critical thinking.

Although high education accounts for 70.89% of all empirical studies performed by researchers, high school may be the appropriate learning stage to foster students’ critical thinking by utilizing the approach of collaborative problem-solving since it has the largest overall effect size. This phenomenon may be related to student’s cognitive development, which needs to be further studied in follow-up research.

With regard to teaching type, mixed course teaching may be the best teaching method to cultivate students’ critical thinking. Relevant studies have shown that in the actual teaching process if students are trained in thinking methods alone, the methods they learn are isolated and divorced from subject knowledge, which is not conducive to their transfer of thinking methods; therefore, if students’ thinking is trained only in subject teaching without systematic method training, it is challenging to apply to real-world circumstances (Ruggiero, 2012 ; Hu and Liu, 2015 ). Teaching critical thinking as mixed course teaching in parallel to other subject teachings can achieve the best effect on learners’ critical thinking, and explicit critical thinking instruction is more effective than less explicit critical thinking instruction (Bensley and Spero, 2014 ).

In terms of the intervention duration, with longer intervention times, the overall effect size shows an upward tendency. Thus, the intervention duration and critical thinking’s impact are positively correlated. Critical thinking, as a key competency for students in the 21st century, is difficult to get a meaningful improvement in a brief intervention duration. Instead, it could be developed over a lengthy period of time through consistent teaching and the progressive accumulation of knowledge (Halpern, 2001 ; Hu and Liu, 2015 ). Therefore, future empirical studies ought to take these restrictions into account throughout a longer period of critical thinking instruction.

With regard to group size, a group size of 2–3 persons has the highest effect size, and the comprehensive effect size decreases with increasing group size in general. This outcome is in line with some research findings; as an example, a group composed of two to four members is most appropriate for collaborative learning (Schellens and Valcke, 2006 ). However, the meta-analysis results also indicate that once the group size exceeds 7 people, small groups cannot produce better interaction and performance than large groups. This may be because the learning scaffolds of technique support, resource support, and teacher support improve the frequency and effectiveness of interaction among group members, and a collaborative group with more members may increase the diversity of views, which is helpful to cultivate critical thinking utilizing the approach of collaborative problem-solving.

With regard to the learning scaffold, the three different kinds of learning scaffolds can all enhance critical thinking. Among them, the teacher-supported learning scaffold has the largest overall effect size, demonstrating the interdependence of effective learning scaffolds and collaborative problem-solving. This outcome is in line with some research findings; as an example, a successful strategy is to encourage learners to collaborate, come up with solutions, and develop critical thinking skills by using learning scaffolds (Reiser, 2004 ; Xu et al., 2022 ); learning scaffolds can lower task complexity and unpleasant feelings while also enticing students to engage in learning activities (Wood et al., 2006 ); learning scaffolds are designed to assist students in using learning approaches more successfully to adapt the collaborative problem-solving process, and the teacher-supported learning scaffolds have the greatest influence on critical thinking in this process because they are more targeted, informative, and timely (Xu et al., 2022 ).

With respect to the measuring tool, despite the fact that standardized measurement tools (such as the WGCTA, CCTT, and CCTST) have been acknowledged as trustworthy and effective by worldwide experts, only 54.43% of the research included in this meta-analysis adopted them for assessment, and the results indicated no intergroup differences. These results suggest that not all teaching circumstances are appropriate for measuring critical thinking using standardized measurement tools. “The measuring tools for measuring thinking ability have limits in assessing learners in educational situations and should be adapted appropriately to accurately assess the changes in learners’ critical thinking.”, according to Simpson and Courtney ( 2002 , p. 91). As a result, in order to more fully and precisely gauge how learners’ critical thinking has evolved, we must properly modify standardized measuring tools based on collaborative problem-solving learning contexts.

With regard to the subject area, the comprehensive effect size of science departments (e.g., mathematics, science, medical science) is larger than that of language arts and social sciences. Some recent international education reforms have noted that critical thinking is a basic part of scientific literacy. Students with scientific literacy can prove the rationality of their judgment according to accurate evidence and reasonable standards when they face challenges or poorly structured problems (Kyndt et al., 2013 ), which makes critical thinking crucial for developing scientific understanding and applying this understanding to practical problem solving for problems related to science, technology, and society (Yore et al., 2007 ).

Suggestions for critical thinking teaching

Other than those stated in the discussion above, the following suggestions are offered for critical thinking instruction utilizing the approach of collaborative problem-solving.

First, teachers should put a special emphasis on the two core elements, which are collaboration and problem-solving, to design real problems based on collaborative situations. This meta-analysis provides evidence to support the view that collaborative problem-solving has a strong synergistic effect on promoting students’ critical thinking. Asking questions about real situations and allowing learners to take part in critical discussions on real problems during class instruction are key ways to teach critical thinking rather than simply reading speculative articles without practice (Mulnix, 2012 ). Furthermore, the improvement of students’ critical thinking is realized through cognitive conflict with other learners in the problem situation (Yang et al., 2008 ). Consequently, it is essential for teachers to put a special emphasis on the two core elements, which are collaboration and problem-solving, and design real problems and encourage students to discuss, negotiate, and argue based on collaborative problem-solving situations.

Second, teachers should design and implement mixed courses to cultivate learners’ critical thinking, utilizing the approach of collaborative problem-solving. Critical thinking can be taught through curriculum instruction (Kuncel, 2011 ; Leng and Lu, 2020 ), with the goal of cultivating learners’ critical thinking for flexible transfer and application in real problem-solving situations. This meta-analysis shows that mixed course teaching has a highly substantial impact on the cultivation and promotion of learners’ critical thinking. Therefore, teachers should design and implement mixed course teaching with real collaborative problem-solving situations in combination with the knowledge content of specific disciplines in conventional teaching, teach methods and strategies of critical thinking based on poorly structured problems to help students master critical thinking, and provide practical activities in which students can interact with each other to develop knowledge construction and critical thinking utilizing the approach of collaborative problem-solving.

Third, teachers should be more trained in critical thinking, particularly preservice teachers, and they also should be conscious of the ways in which teachers’ support for learning scaffolds can promote critical thinking. The learning scaffold supported by teachers had the greatest impact on learners’ critical thinking, in addition to being more directive, targeted, and timely (Wood et al., 2006 ). Critical thinking can only be effectively taught when teachers recognize the significance of critical thinking for students’ growth and use the proper approaches while designing instructional activities (Forawi, 2016 ). Therefore, with the intention of enabling teachers to create learning scaffolds to cultivate learners’ critical thinking utilizing the approach of collaborative problem solving, it is essential to concentrate on the teacher-supported learning scaffolds and enhance the instruction for teaching critical thinking to teachers, especially preservice teachers.

Implications and limitations

There are certain limitations in this meta-analysis, but future research can correct them. First, the search languages were restricted to English and Chinese, so it is possible that pertinent studies that were written in other languages were overlooked, resulting in an inadequate number of articles for review. Second, these data provided by the included studies are partially missing, such as whether teachers were trained in the theory and practice of critical thinking, the average age and gender of learners, and the differences in critical thinking among learners of various ages and genders. Third, as is typical for review articles, more studies were released while this meta-analysis was being done; therefore, it had a time limit. With the development of relevant research, future studies focusing on these issues are highly relevant and needed.

Conclusions

The subject of the magnitude of collaborative problem-solving’s impact on fostering students’ critical thinking, which received scant attention from other studies, was successfully addressed by this study. The question of the effectiveness of collaborative problem-solving in promoting students’ critical thinking was addressed in this study, which addressed a topic that had gotten little attention in earlier research. The following conclusions can be made:

Regarding the results obtained, collaborative problem solving is an effective teaching approach to foster learners’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]). With respect to the dimensions of critical thinking, collaborative problem-solving can significantly and effectively improve students’ attitudinal tendency, and the comprehensive effect is significant (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

As demonstrated by both the results and the discussion, there are varying degrees of beneficial effects on students’ critical thinking from all seven moderating factors, which were found across 36 studies. In this context, the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have a positive impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. Since the learning stage (chi 2  = 3.15, P  = 0.21 > 0.05) and measuring tools (chi 2  = 0.08, P  = 0.78 > 0.05) did not demonstrate any significant intergroup differences, we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving.

Data availability

All data generated or analyzed during this study are included within the article and its supplementary information files, and the supplementary information files are available in the Dataverse repository: https://doi.org/10.7910/DVN/IPFJO6 .

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Acknowledgements

This research was supported by the graduate scientific research and innovation project of Xinjiang Uygur Autonomous Region named “Research on in-depth learning of high school information technology courses for the cultivation of computing thinking” (No. XJ2022G190) and the independent innovation fund project for doctoral students of the College of Educational Science of Xinjiang Normal University named “Research on project-based teaching of high school information technology courses from the perspective of discipline core literacy” (No. XJNUJKYA2003).

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Xu, E., Wang, W. & Wang, Q. The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature. Humanit Soc Sci Commun 10 , 16 (2023). https://doi.org/10.1057/s41599-023-01508-1

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8 consistent behaviors of practically perfect problem solvers.

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This past month I celebrated my 42nd anniversary with my dear wife. One of her finest qualities is her ability to solve problems. I admit, while I like to analyze and contemplate the various approaches to solving a problem, she just gets it done. It turns out she is not the only female with this fantastic quality. According to our database, there is a trend among male and female leaders in solving problems.

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Understanding the Results

The results for the analysis were confusing because it was clear that being rated better at technical expertise should give men an advantage at solving problems. 

To verify the results, I re-ran the data with more of an experimental design selecting only 50% of the cases for the analysis. In the experimental design, the results yielded the same conclusions. Technical/Professional Expertise rated significantly higher for men (T-Value 2.276, Sig. 0.023). Problem Solving rated significantly higher for women (T-Value 2.432, Sig. 0.015).

So... What Does This Mean?

To better understand what created the differences in the results on Problem Solving, I analyzed the top behaviors highly correlated with problem-solving. Why? Because these were behaviors that would impact the perceptions about HOW problems were solved. I then compared the results for men versus women on 16 behaviors and found that 12 behaviors showed significant differences between men and women. Four of the behaviors were rated more positively for men, and eight were rated more positively for women. The graph below shows the 12 items that were significantly different for women and men. The items that were significantly different for men clustered around two issues. Technical/Professional expertise was rated significantly higher on two items and can influence problem-solving ability. The two other items focused on strategic perspective. Having the ability to understand how a problem connects to the vision and direction of the organization was a skill that also helped men solve problems. While these four behaviors were helpful for men, the eight behaviors that women performed more effectively made a bigger difference in the results.

In the end, regardless of men or women, these behaviors teach us some essential requirements for practical problem-solving that we ALL need to improve!

8 Behaviors of Practically Perfect Problem Solvers

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ZFCO Problem Solving Study (2021)

1.       They get it done right away . In other studies comparing men and women leaders, we have found that this competency consistently shows the most significant difference between genders. It is easy for problems to get put on the "I will do that later list." It seems we can learn a lot from the women in our lives that take on problems sooner and invest more energy to get them corrected. 

2.       They model this behavior to those around them . If you want to change the way others perceive you in that behavior, you need to be considered the role model for it. Be consistent. Those who are good role models are more trusted. 

3.       They don't work on problems alone . Many problems in an organization flow across multiple groups and cannot be resolved without collaboration. Women were rated as better at collaboration. Men tended to act more independently. If you're going to solve a problem quickly, involve those around you and share the glory. 

4.       They know how to explain the problem and solution effectively.  A significant part of solving any problem is having good communication between everyone impacted by the problem. The first benefit of good communication is that it helps everyone understand the problem, when it occurs, and why it occurs. Second, the solution needs to be communicated to all involved parties. 

5.       They can influence others to stretch their abilities to solve the problem.   Many problems are hard to solve and require that people do something differently than they have done in the past. This requires you to be more skillful at getting others to step up and stretch to accomplish difficult goals.

6.       They quickly recognize where change is needed.  It is easy to ignore many problems. It's harder to identify where change is needed and do something about it quickly. 

7.       They know how to focus on top priorities.  We cannot fix everything, so concentrating on top priorities makes it possible for an organization to change the most pressing issues. 

8.       They understand the full context.  Solving problems requires that all people affected know how their role impacts the problem to be solved. Solving problems is more than just coming up with an excellent solution. 

Aren't you grateful for the problem solvers in your life? Problems can be stressful, overwhelming, and many of us want to pretend they don't exist. We want to hide them in a corner and tiptoe around them, pretending they are not there, and if we don't give them attention, they will walk away. They won't. 

Problems get solved when someone takes the initiative to fix the problem, understands their role in the solution, and cooperates. Problem-solving frequently requires the efforts and involvement of others. If you have a significant problem that needs to be solved in your organization, be the person that doesn’t just understand the problem but solves it.

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To Solve a Tough Problem, Reframe It

• Julia Binder
• Michael D. Watkins

Research shows that companies devote too little effort to examining problems before trying to solve them. By jumping immediately into problem-solving, teams limit their ability to design innovative solutions.

The authors recommend that companies spend more time up front on problem-framing, a process for understanding and defining a problem. Exploring different frames is like looking at a scene through various camera lenses while adjusting your angle, aperture, and focus. A wide-angle lens gives you a very different photo from that taken with a telephoto lens, and shifting your angle and depth of focus yields distinct images. Effective problem-framing is similar: Looking at a problem from a variety of perspectives helps you uncover new insights and generate fresh ideas.

This article introduces a five-phase approach to problem-framing: In the expand phase, the team identifies all aspects of a problem; in examine, it dives into root causes; in empathize, it considers key stakeholders’ perspectives; in elevate, it puts the problem into a broader context; and in envision, it creates a road map toward the desired outcome.

Five steps to ensure that you don’t jump to solutions

Idea in Brief

The problem.

Research shows that most companies devote too little effort to examining problems from all angles before trying to solve them. That limits their ability to come up with innovative ways to address them.

The Solution

Companies need a structured approach for understanding and defining complex problems to uncover new insights and generate fresh ideas.

The Approach

This article introduces a five-phase approach to problem-framing: In the expand phase, the team identifies all aspects of a problem; in examine, it dives into root causes; in empathize, it considers key stakeholders’ perspectives; in elevate, it puts the problem into a broader context; and in envision, it creates a road map toward the desired outcome.

When business leaders confront complex problems, there’s a powerful impulse to dive right into “solving” mode: You gather a team and then identify potential solutions. That’s fine for challenges you’ve faced before or when proven methods yield good results. But what happens when a new type of problem arises or aspects of a familiar one shift substantially? Or if you’re not exactly sure what the problem is?

Research conducted by us and others shows that leaders and their teams devote too little effort to examining and defining problems before trying to solve them. A study by Paul Nutt of Ohio State University, for example, looked at 350 decision-making processes at medium to large companies and found that more than half failed to achieve desired results, often because perceived time pressure caused people to pay insufficient attention to examining problems from all angles and exploring their complexities. By jumping immediately into problem-solving, teams limit their ability to design innovative and durable solutions.

When we work with organizations and teams, we encourage them to spend more time up front on problem-framing, a process for understanding and defining a problem. Exploring frames is like looking at a scene through various camera lenses while adjusting your angle, aperture, and focus. A wide-angle lens will give you a very different photo from that taken with a telephoto lens, and shifting your angle and depth of focus yields distinct images. Effective problem-framing is similar: Looking at a problem from a variety of perspectives lets you uncover new insights and generate fresh ideas.

As with all essential processes, it helps to have a methodology and a road map. This article introduces the E5 approach to problem-framing—expand, examine, empathize, elevate, and envision—and offers tools that enable leaders to fully explore the problem space.

Phase 1: Expand

In the first phase, set aside preconceptions and open your mind. We recommend using a tool called frame-storming, which encourages a comprehensive exploration of an issue and its nuances. It is a neglected precursor to brainstorming, which typically focuses on generating many different answers for an already framed challenge. Frame-storming helps teams identify assumptions and blind spots, mitigating the risk of pursuing inadequate or biased solutions. The goal is to spark innovation and creativity as people dig into—or as Tina Seelig from Stanford puts it, “fall in love with”—the problem.

Begin by assembling a diverse team, encompassing a variety of types of expertise and perspectives. Involving outsiders can be helpful, since they’re often coming to the issue cold. A good way to prompt the team to consider alternative scenarios is by asking “What if…?” and “How might we…?” questions. For example, ask your team, “What if we had access to unlimited resources to tackle this issue?” or “How might better collaboration between departments or teams help us tackle this issue?” The primary objective is to generate many alternative problem frames, allowing for a more holistic understanding of the issue. Within an open, nonjudgmental atmosphere, you deliberately challenge established thinking—what we call “breaking” the frame.

It may be easy to eliminate some possibilities, and that’s exactly what you should do. Rather than make assumptions, generate alternative hypotheses and then test them.

Consider the problem-framing process at a company we’ll call Omega Soundscapes, a midsize producer of high-end headphones. (Omega is a composite of several firms we’ve worked with.) Omega’s sales had declined substantially over the past two quarters, and the leadership team’s initial diagnosis, or reference frame, was that recent price hikes to its flagship product made it too expensive for its target market. Before acting on this assumption, the team convened knowledgeable representatives from sales, marketing, R&D, customer service, and external consultants to do some frame-storming. Team members were asked:

• What if we lowered the price of our flagship product? How would that impact sales and profitability?
• How might we identify customers in new target markets who could afford our headphones at the current price?
• What if we offered financing or a subscription-based model for our headphones? How would that change perceptions of affordability?
• How might we optimize our supply chain and production processes to reduce manufacturing costs without compromising quality?

In playing out each of those scenarios, the Omega team generated several problem frames:

• The target market’s preferences have evolved.
• New competitors have entered the market.
• Product quality has decreased.
• Something has damaged perceptions of the brand.
• Something has changed in the priorities of our key distributors.

Each of the frames presented a unique angle from which to approach the problem of declining sales, setting the stage for the development of diverse potential solutions. At this stage, it may be relatively easy to eliminate some possibilities, and that’s exactly what you should do. Rather than make assumptions, generate alternative hypotheses and then test them.

See more HBR charts in Data & Visuals

Phase 2: Examine

If the expand phase is about identifying all the facets of a problem, this one is about diving deep to identify root causes. The team investigates the issue thoroughly, peeling back the layers to understand underlying drivers and systemic contributors.

A useful tool for doing this is the iceberg model, which guides the team through layers of causation: surface-level events, the behavioral patterns that drive them, underlying systematic structures, and established mental models. As you probe ever deeper and document your findings, you begin to home in on the problem’s root causes. As is the case in the expand phase, open discussions and collaborative research are crucial for achieving a comprehensive analysis.

Let’s return to our Omega Soundscapes example and use the iceberg model to delve into the issues surrounding the two quarters of declining sales. Starting with the first layer beneath the surface, the behavioral pattern, the team diligently analyzed customer feedback. It discovered a significant drop in brand loyalty. This finding validated the problem frame of a “shifting brand perception,” prompting further investigation into what might have been causing it.

Phase 3: Empathize

In this phase, the focus is on the stakeholders—employees, customers, clients, investors, supply chain partners, and other parties—who are most central to and affected by the problem under investigation. The core objective is to understand how they perceive the issue: what they think and feel, how they’re acting, and what they want.

First list all the people who are directly or indirectly relevant to the problem. It may be helpful to create a visual representation of the network of relationships in the ecosystem. Prioritize the stakeholders according to their level of influence on and interest in the problem, and focus on understanding the roles, demographics, behavior patterns, motivations, and goals of the most important ones.

Now create empathy maps for those critical stakeholders. Make a template divided into four sections: Say, Think, Feel, and Do. Conduct interviews or surveys to gather authentic data. How do various users explain the problem? How do they think about the issue, and how do their beliefs inform that thinking? What emotions are they feeling and expressing? How are they behaving? Populate each section of the map with notes based on your observations and interactions. Finally, analyze the completed empathy maps. Look for pain points, inconsistencies, and patterns in stakeholder perspectives.

Returning to the Omega case study, the team identified its ecosystem of stakeholders: customers (both current and potential); retail partners and distributors; the R&D, marketing, and sales teams; suppliers of headphone components; investors and shareholders; and new and existing competitors. They narrowed the list to a few key stakeholders related to the declining-sales problem: customers, retail partners, and investors/shareholders; Omega created empathy maps for representatives from each.

Here’s what the empathy maps showed about what the stakeholders were saying, thinking, feeling, and doing:

Sarah, the customer, complained on social media about the high price of her favorite headphones. Dave, the retailer, expressed concerns about unsold inventory and the challenge of convincing customers to buy the expensive headphones. Alex, the shareholder, brought up Omega’s declining financial performance during its annual investor day.

Sarah thought that Omega was losing touch with its loyal customer base. Dave was considering whether to continue carrying Omega’s products in his store or explore other brands. Alex was contemplating diversifying his portfolio into other consumer-tech companies.

As a longtime supporter of the brand, Sarah felt frustrated and slightly betrayed. Dave was feeling anxious about the drop in sales and the impact on his store’s profitability. Alex was unhappy with the declining stock value.

Sarah was looking for alternatives to the headphones, even though she loves the product’s quality. Dave was scheduling a call with Omega to negotiate pricing and terms. Alex was planning to attend Omega’s next shareholder meeting to find out more information from the leadership team.

When Omega leaders analyzed the data in the maps, they realized that pricing wasn’t the only reason for declining sales. A more profound issue was customers’ dissatisfaction with the perceived price-to-quality ratio, especially when compared with competitors’ offerings. That insight prompted the team to consider enhancing the headphones with additional features, offering more-affordable alternatives, and possibly switching to a service model.

Phase 4: Elevate

This phase involves exploring how the problem connects to broader organizational issues. It’s like zooming out on a map to understand where a city lies in relation to the whole country or continent. This bird’s-eye view reveals interconnected issues and their implications.

For this analysis, we recommend the four-frame model developed by Lee Bolman and Terrence Deal, which offers distinct lenses through which to view the problem at a higher level. The structural frame helps you explore formal structures (such as hierarchy and reporting relationships); processes (such as workflow); and systems, rules, and policies. This frame examines efficiency, coordination, and alignment of activities.

The human resources frame focuses on people, relationships, and social dynamics. This includes teamwork, leadership, employee motivation, engagement, professional development, and personal growth. In this frame, the organization is seen as a community or a family that recognizes that talent is its most valuable asset. The political frame delves into power dynamics, competing interests, conflicts, coalitions, and negotiations. From this perspective, organizations are arenas where various stakeholders vie for resources and engage in political struggles to influence decisions. It helps you see how power is distributed, used, and contested.

The symbolic frame highlights the importance of symbols, rituals, stories, and shared values in shaping group identity and culture. In it, organizations are depicted as theaters through which its members make meaning.

Using this model, the Omega team generated the following insights in the four frames:

Structural.

A deeper look into the company’s structure revealed siloing and a lack of coordination between the R&D and marketing departments, which had led to misaligned messaging to customers. It also highlighted a lack of collaboration between the two functions and pointed to the need to communicate with the target market about the product’s features and benefits in a coherent and compelling way.

Human resources.

This frame revealed that the declining sales and price hikes had ramped up pressure on the sales team, damaging morale. The demotivated team was struggling to effectively promote the product, making it harder to recover from declining sales. Omega realized it was lacking adequate support, training, and incentives for the team.

The key insight from this frame was that the finance team’s reluctance to approve promotions in the sales group to maintain margins was exacerbating the morale problem. Omega understood that investing in sales leadership development while still generating profits was crucial for long-term success and that frank discussions about the issue were needed.

This frame highlighted an important misalignment in perception: The company believed that its headphones were of “top quality,” while customers reported in surveys that they were “overpriced.” This divergence raised alarm that branding, marketing, and pricing strategies, which were all predicated on the central corporate value of superior quality, were no longer resonating with customers. Omega realized that it had been paying too little attention to quality assurance and functionality.

Phase 5: Envision

In this phase, you transition from framing the problem to actively imagining and designing solutions. This involves synthesizing the insights gained from earlier phases and crafting a shared vision of the desired future state.

Here we recommend using a technique known as backcasting. First, clearly define your desired goal. For example, a team struggling with missed deadlines and declining productivity might aim to achieve on-time completion rates of 98% for its projects and increase its volume of projects by 5% over the next year. Next, reverse engineer the path to achieving your goal. Outline key milestones required over both the short term and the long term. For each one, pinpoint specific interventions, strategies, and initiatives that will propel you closer to your goal. These may encompass changes in processes, policies, technologies, and behaviors. Synthesize the activities into a sequenced, chronological, prioritized road map or action plan, and allocate the resources, including time, budget, and personnel, necessary to implement your plan. Finally, monitor progress toward your goal and be prepared to adjust the plan in response to outcomes, feedback, or changing circumstances. This approach ensures that the team’s efforts in implementing the insights from the previous phases are strategically and purposefully directed toward a concrete destination.

Applying the Approach

Albert Einstein once said, “If I had one hour to solve a problem, I would spend 55 minutes thinking about the problem and five minutes thinking about the solution.” That philosophy underpins our E5 framework, which provides a structured approach for conscientiously engaging with complex problems before leaping to solutions.

As teams use the methodology, they must understand that problem-framing in today’s intricate business landscape is rarely a linear process. While we’re attempting to provide a structured path, we also recognize the dynamic nature of problems and the need for adaptability. Invariably, as teams begin to implement solutions, new facets of a problem may come to light, unforeseen challenges may arise, or external circumstances may evolve. Your team should be ready to loop back to previous phases—for instance, revisiting the expand phase to reassess the problem’s frame, delving deeper into an overlooked root cause in another examine phase, or gathering fresh insights from stakeholders in a new empathize phase. Ultimately, the E5 framework is intended to foster a culture of continuous improvement and innovation.

• JB Julia Binder is the director of the Center for Sustainable and Inclusive Business and a professor of sustainable innovation at IMD.
• Michael D. Watkins is a professor of leadership and organizational change at IMD , a cofounder of Genesis Advisers , and the author of The Six Disciplines of Strategic Thinking .

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What is a Research Problem? Characteristics, Types, and Examples

A research problem is a gap in existing knowledge, a contradiction in an established theory, or a real-world challenge that a researcher aims to address in their research. It is at the heart of any scientific inquiry, directing the trajectory of an investigation. The statement of a problem orients the reader to the importance of the topic, sets the problem into a particular context, and defines the relevant parameters, providing the framework for reporting the findings. Therein lies the importance of research problem s.  

The formulation of well-defined research questions is central to addressing a research problem . A research question is a statement made in a question form to provide focus, clarity, and structure to the research endeavor. This helps the researcher design methodologies, collect data, and analyze results in a systematic and coherent manner. A study may have one or more research questions depending on the nature of the study.   

Identifying and addressing a research problem is very important. By starting with a pertinent problem , a scholar can contribute to the accumulation of evidence-based insights, solutions, and scientific progress, thereby advancing the frontier of research. Moreover, the process of formulating research problems and posing pertinent research questions cultivates critical thinking and hones problem-solving skills.   

Table of Contents

What is a Research Problem ?  

Before you conceive of your project, you need to ask yourself “ What is a research problem ?” A research problem definition can be broadly put forward as the primary statement of a knowledge gap or a fundamental challenge in a field, which forms the foundation for research. Conversely, the findings from a research investigation provide solutions to the problem .  

A research problem guides the selection of approaches and methodologies, data collection, and interpretation of results to find answers or solutions. A well-defined problem determines the generation of valuable insights and contributions to the broader intellectual discourse.  

Characteristics of a Research Problem  

Knowing the characteristics of a research problem is instrumental in formulating a research inquiry; take a look at the five key characteristics below:  

Novel : An ideal research problem introduces a fresh perspective, offering something new to the existing body of knowledge. It should contribute original insights and address unresolved matters or essential knowledge.   

Significant : A problem should hold significance in terms of its potential impact on theory, practice, policy, or the understanding of a particular phenomenon. It should be relevant to the field of study, addressing a gap in knowledge, a practical concern, or a theoretical dilemma that holds significance.  

Feasible: A practical research problem allows for the formulation of hypotheses and the design of research methodologies. A feasible research problem is one that can realistically be investigated given the available resources, time, and expertise. It should not be too broad or too narrow to explore effectively, and should be measurable in terms of its variables and outcomes. It should be amenable to investigation through empirical research methods, such as data collection and analysis, to arrive at meaningful conclusions A practical research problem considers budgetary and time constraints, as well as limitations of the problem . These limitations may arise due to constraints in methodology, resources, or the complexity of the problem.  

Clear and specific : A well-defined research problem is clear and specific, leaving no room for ambiguity; it should be easily understandable and precisely articulated. Ensuring specificity in the problem ensures that it is focused, addresses a distinct aspect of the broader topic and is not vague.  

Rooted in evidence: A good research problem leans on trustworthy evidence and data, while dismissing unverifiable information. It must also consider ethical guidelines, ensuring the well-being and rights of any individuals or groups involved in the study.

Types of Research Problems  

Across fields and disciplines, there are different types of research problems . We can broadly categorize them into three types.  

• Theoretical research problems

Theoretical research problems deal with conceptual and intellectual inquiries that may not involve empirical data collection but instead seek to advance our understanding of complex concepts, theories, and phenomena within their respective disciplines. For example, in the social sciences, research problem s may be casuist (relating to the determination of right and wrong in questions of conduct or conscience), difference (comparing or contrasting two or more phenomena), descriptive (aims to describe a situation or state), or relational (investigating characteristics that are related in some way).  

Here are some theoretical research problem examples :   

• Ethical frameworks that can provide coherent justifications for artificial intelligence and machine learning algorithms, especially in contexts involving autonomous decision-making and moral agency.  
• Determining how mathematical models can elucidate the gradual development of complex traits, such as intricate anatomical structures or elaborate behaviors, through successive generations.  
• Applied research problems

Applied or practical research problems focus on addressing real-world challenges and generating practical solutions to improve various aspects of society, technology, health, and the environment.  

Here are some applied research problem examples :   

• Studying the use of precision agriculture techniques to optimize crop yield and minimize resource waste.  
• Designing a more energy-efficient and sustainable transportation system for a city to reduce carbon emissions.  
• Action research problems

Action research problems aim to create positive change within specific contexts by involving stakeholders, implementing interventions, and evaluating outcomes in a collaborative manner.  

Here are some action research problem examples :   

• Partnering with healthcare professionals to identify barriers to patient adherence to medication regimens and devising interventions to address them.  
• Collaborating with a nonprofit organization to evaluate the effectiveness of their programs aimed at providing job training for underserved populations.  

These different types of research problems may give you some ideas when you plan on developing your own.  

How to Define a Research Problem  

You might now ask “ How to define a research problem ?” These are the general steps to follow:   

• Look for a broad problem area: Identify under-explored aspects or areas of concern, or a controversy in your topic of interest. Evaluate the significance of addressing the problem in terms of its potential contribution to the field, practical applications, or theoretical insights.
• Learn more about the problem: Read the literature, starting from historical aspects to the current status and latest updates. Rely on reputable evidence and data. Be sure to consult researchers who work in the relevant field, mentors, and peers. Do not ignore the gray literature on the subject.
• Identify the relevant variables and how they are related: Consider which variables are most important to the study and will help answer the research question. Once this is done, you will need to determine the relationships between these variables and how these relationships affect the research problem . 
• Think of practical aspects : Deliberate on ways that your study can be practical and feasible in terms of time and resources. Discuss practical aspects with researchers in the field and be open to revising the problem based on feedback. Refine the scope of the research problem to make it manageable and specific; consider the resources available, time constraints, and feasibility.
• Formulate the problem statement: Craft a concise problem statement that outlines the specific issue, its relevance, and why it needs further investigation.
• Stick to plans, but be flexible: When defining the problem , plan ahead but adhere to your budget and timeline. At the same time, consider all possibilities and ensure that the problem and question can be modified if needed.

Key Takeaways  

• A research problem concerns an area of interest, a situation necessitating improvement, an obstacle requiring eradication, or a challenge in theory or practical applications.   
• The importance of research problem is that it guides the research and helps advance human understanding and the development of practical solutions.  
• Research problem definition begins with identifying a broad problem area, followed by learning more about the problem, identifying the variables and how they are related, considering practical aspects, and finally developing the problem statement.  
• Different types of research problems include theoretical, applied, and action research problems , and these depend on the discipline and nature of the study.  
• An ideal problem is original, important, feasible, specific, and based on evidence.  

Frequently Asked Questions  

Why is it important to define a research problem?  

Identifying potential issues and gaps as research problems is important for choosing a relevant topic and for determining a well-defined course of one’s research. Pinpointing a problem and formulating research questions can help researchers build their critical thinking, curiosity, and problem-solving abilities.   

How do I identify a research problem?  

Identifying a research problem involves recognizing gaps in existing knowledge, exploring areas of uncertainty, and assessing the significance of addressing these gaps within a specific field of study. This process often involves thorough literature review, discussions with experts, and considering practical implications.  

Can a research problem change during the research process?  

Yes, a research problem can change during the research process. During the course of an investigation a researcher might discover new perspectives, complexities, or insights that prompt a reevaluation of the initial problem. The scope of the problem, unforeseen or unexpected issues, or other limitations might prompt some tweaks. You should be able to adjust the problem to ensure that the study remains relevant and aligned with the evolving understanding of the subject matter.

How does a research problem relate to research questions or hypotheses?  

A research problem sets the stage for the study. Next, research questions refine the direction of investigation by breaking down the broader research problem into manageable components. Research questions are formulated based on the problem , guiding the investigation’s scope and objectives. The hypothesis provides a testable statement to validate or refute within the research process. All three elements are interconnected and work together to guide the research.  

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

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How To Solve The Problems? Practical Problem Solving Skills

Problem solving is a process in which problems can break down into three steps: identify the problem, generate solutions, and evaluate and choose one of the developed solutions as an appropriate solution for this specific situation. Breaking the problem solving process down into these three steps makes it easier to understand and follow.

The first step in problem solving is to identify the problem. This may seem like a simple task, but it can be challenging to accurately determine the situation when multiple issues are involved. Once the problem has been identified, it is important to understand what the problem is and what needs to be done to fix it.

The second step in problem-solving is to generate possible solutions. Many different strategies can be used when developing these potential solutions. One strategy is brainstorming, where each person in a group shares all of their ideas no matter how ridiculous they may seem. Another strategy involves using a Venn diagram and either expanding or reducing it as you start considering more or less possible solutions.

The third step in problem-solving is to evaluate and choose one of the generated solutions appropriate for this specific situation. This step can be difficult, as it can be hard to determine which solution is best. A few different factors can be considered when making this decision, such as how realistic the answer is, how effective it will be in solving the problem, and whether or not it will make things better or worse. Some other factors include how much time and effort it will take to implement the solution and whether or not there are any laws or regulations that must be considered.

Once a problem has been properly identified, possible solutions have been generated, and a decision has been made as to which possible explanation is the most appropriate for this specific situation, it can be put into action. If issues with this solution or other problems arise, the problem solving process must start over. This process can take place many times before a final resolution is reached.

Understanding and following the three steps of problem solving can be easier to identify and fix problems. However, it is essential to note that these steps are not always linear and that different solutions may need to be tried to find the best one. The key is to stay focused on solving the problem and not give up until a resolution is reached.

Creative Solutions For Better Resolving The Issues

Sometimes, reasoning with others works wonders. However, you may find yourself up against a brick wall at other times. And if that happens, there are ways to do things the right way, so the next time someone tries to hold their ground stubbornly, your side of the story comes across as being more persuasive than theirs does. For example, instead of arguing with someone and resorting to insults or name-calling, you can try coming up with a creative solution to the problem at hand.

That's because when it comes to problem-solving, creativity is key. If you can think of a unique way to resolve the situation, then there's a good chance that things will go more smoothly than if you try to overpower the other person or take a more traditional route. Granted, there's no guarantee that things will work out in your favor, but it's always worth a shot, especially if the alternative is an all-out war.

Being creative with your problem-solving skills can mean the difference between coming across as professional or childish. Sure, there are certain situations where you'll want to be respectful of others even if they're being difficult, but when it comes down to brass tacks. Someone is refusing to budge on an issue that needs to be resolved (or an argument needs to end). Creativity can work wonders in getting what you want. So the next time you find yourself in a sticky situation, try thinking outside the box and see if that helps resolve things more positively. Who knows? You may be surprised at how well it works.

There are many different types of problems; however, you should follow some general guidelines when trying to solve any problem.

Problems come in all shapes and sizes. However, there are some general guidelines you should always follow when trying to solve any problem!

Types of Problems

Solving quantitative problems will require you to use mathematical equations within a set answer range (ex. finding the length of a rectangle using its width and height).

Analyzing qualitative problems will require you to use your critical thinking skills to understand the problem and develop a solution. (ex. What is the best way to reduce traffic congestion in a city?)

Synthesizing information from multiple sources is another common problem-solving situation (ex. creating a research paper using information from different sources)

Figure out what kind of problem you're trying to solve

Make sure you understand the problem. This may require reading and re-reading the issue several times and brainstorming possible solutions.

Come up with a solution. Try out different methods to see which one works best for you.

Check your work. Go back over your job to make sure everything is correct and that you haven't made any careless mistakes.

Have someone else check your work. Sometimes it's helpful to have someone else look at your work to see if they can find any mistakes you may have missed.

Problem-solving can be difficult, but with these guidelines in mind, you'll be able to solve any problem that comes your way!

​What are the best ways to solve problems?

How do I know if a problem can be fixed by logic and reasoning?

What creates a need for problem-solving in the first place.

Is it possible to improve my own problem-solving skills without taking an educational class or online course?

What should I do if there is no solution to a particular problem?

What are the best ways to solve problems?

The best way to solve any problem is to first understand the issue, brainstorm possible solutions, and then try out different methods to see which one works best for you. Additionally, it can be helpful to have someone else look at your work to see if they can find any mistakes you may have missed.

If you’re dealing with a quantitative problem, then logic and reasoning will likely provide the answer. However, if the issue is more qualitative in nature (i.e., requiring critical thinking skills), then logic and reason may not be enough and you may need to brainstorm different solutions.

A need for problem-solving arises when an issue or situation presents itself that needs to be addressed or resolved. This could be anything from figuring out how to reduce traffic congestion in a city, creating a research paper using information from various sources, or finding the length of a rectangle given its width and height.

How do I know if a problem requires a practical solution?

A practical solution is one that can be applied in a practical way to solve a problem. To determine if a problem requires a practical solution, you should assess the nature of the problem and determine if its solution lies in a practical application. Consider factors such as cost, time, resources, and complexity of the problem. If the problem is complex or requires a lot of resources, a practical solution may be the best approach.

What techniques can I use to solve problems in a practical manner?

1. Brainstorming: Generate ideas and potential solutions by brainstorming with others. 2. Divide and Conquer: Break down large problems into smaller, more manageable pieces. 3. Research: Research potential solutions or similar problems that have been solved. 4. Experimentation: Try out different potential solutions to see which works best. 5. Analysis: Analyze the data and make an informed decision. 6. Evaluation: Evaluate the results of the solution and make changes as necessary. 7. Reflection: Reflect on the process and look for ways to improve it.

How can I ensure I am approaching a problem in the most efficient way?

You can ensure you are approaching a problem in the most efficient way by breaking it down into smaller parts and tackling each part one at a time. Additionally, research and brainstorming can help you to think of better strategies and solutions. It is also important to take time to think through the problem, rather than rushing into a solution. Finally, it can be helpful to talk to others who have experience with the problem or get feedback from a mentor.

How can I identify the root cause of a practical problem?

Analyzing the Practical Problem To identify the root cause of a practical problem, it is crucial to follow a systematic approach that involves analyzing the issue and breaking it down into smaller components. This process will enable a deeper understanding of the factors contributing to the problem and help in determining the root cause. Gathering Relevant Information Initially, gather all relevant information associated with the problem. This step includes collecting data, identifying the key stakeholders, and understanding the circumstances surrounding the issue. Conducting interviews, analyzing historical records or observing the problem firsthand will provide the necessary evidence for examination. Mapping the Causal Relationships Next, create a cause-and-effect diagram to map the relationships between different elements influencing the problem. This visual representation allows for an organized analysis of the causes contributing to the problem. A popular technique for creating such diagrams is the Ishikawa or fishbone diagram, which clarifies the interrelations between various factors. Evaluating Possible Causes After mapping the causal relationships, assess the possible causes for the practical problem. Generate hypotheses about the root causes by questioning the reasons behind the issue's existence. Tools such as the '5 Whys' technique can be useful to dig deeper into the causes by repeatedly asking the question 'why?' until the root cause becomes evident. Identifying the Root Cause To pinpoint the root cause, verify each hypothesis by reviewing the collected evidence and consulting with experts if possible. Rigorous evaluation of the supporting data and elimination of contributing factors will lead to the identification of the true root cause. Remember that complex problems may have multiple root causes that need to be tackled simultaneously. Designing an Action Plan Once the root cause has been identified, it is essential to act on it to resolve the issue. Develop a targeted action plan that addresses the root cause and the associated contributing factors. The plan should outline the necessary steps, the resources required, and the expected outcomes. Moreover, monitor the progress of the action plan to ensure its effectiveness and adapt the strategy as needed. In conclusion, identifying the root cause of a practical problem demands a systematic approach, from collecting information to designing an effective action plan. Using various analytical tools and techniques, like causal diagrams and the '5 Whys' method, can help uncover underlying reasons for issues and resolve them at their core.

What are some effective strategies for generating multiple solutions to a practical problem?

**Identifying the Problem** To generate multiple solutions for a practical problem, one must first have a clear understanding of the issue at hand. This involves identifying the root cause of the problem and defining the desired outcome. **Brainstorming Ideas** Once the problem is accurately defined, an effective strategy is to engage in brainstorming. Conducting group discussions encourages team members to share their insights on the problem and contribute diverse ideas. Additionally, the more ideas generated, the greater the likelihood of finding a suitable solution. **Considering Alternative Perspectives** Another approach is to analyze the problem from different viewpoints or perspectives. This may involve dividing the problem into smaller and more manageable parts, so that each aspect can be assessed independently. Looking at the problem from different angles can lead to the development of an array of solutions. **Benchmarking and Best Practices** An examination of how other organizations or individuals have addressed similar problems is an effective strategy for generating solutions. Identifying and analyzing the best practices and lessons learned from others can provide valuable insights and ideas that could be adapted and applied to the problem at hand. **Using Creativity Techniques** Utilizing creativity techniques, such as lateral thinking, can stimulate the ability to conceive innovative solutions. Encouraging the use of metaphors, analogies, and imagination allows for a diverse range of ideas to be developed. This cultivates an environment where new and unconventional solutions can be discovered. **Evaluating and Refining Solutions** Once multiple potential solutions have been generated, it is essential to evaluate each one based on its feasibility and effectiveness. Considering the advantages and disadvantages, resources needed, and the likelihood of success will aid in selecting the most appropriate resolution. **Implementing and Reviewing Solutions** Implementing the chosen solution requires careful planning and constant monitoring. This allows for adjustments to be made, ensuring the solution remains effective while mitigating any potential adverse effects. Moreover, in the case of unsuccessful attempts, organizations should remain open to revisiting their initial list of potential solutions and experimenting with alternative options. In conclusion, generating multiple solutions to a practical problem involves understanding the problem, brainstorming ideas, considering alternative perspectives, benchmarking, using creativity techniques, evaluating and refining potential solutions, and implementing and reviewing the chosen resolution. These strategies, when used collaboratively, can contribute to the successful identification and resolution of practical problems.

How can I evaluate and choose the best solution for a specific practical problem?

Understanding the Problem To evaluate and choose the best solution for a specific practical problem, one must first have a comprehensive understanding of the problem at hand. This entails identifying the root cause, assessing the scope and impact of the issue, and determining the desired outcome or goal. Clear and concise problem statements are crucial for coherent analysis. Identifying Possible Solutions Once the problem is understood, a list of possible solutions can be generated. Brainstorming, consulting experts, and researching similar cases can provide valuable insights for potential strategies. When creating this list, it's important not to disregard any ideas, as unconventional solutions may reveal unforeseen benefits. Evaluating Solutions After identifying potential solutions, each must be evaluated systematically. Considerations should include effectiveness, feasibility, costs, benefits, and potential consequences. Achieving a balance between these factors is essential in making an informed decision. Assigning numerical values to each criterion can help compare and contrast various solutions. Seeking Input Seeking input from stakeholders who may be affected by the proposed solution can offer additional perspectives on the merits and drawbacks of each option. This is invaluable in identifying any potential oversights and ensuring the solution is best suited for all concerned parties. Open communication and collaboration can lead to insightful discussions and strengthen the final decision. Testing and Refining Before fully committing to a solution, it may be beneficial to conduct a trial or test. This can help gather real-world data and feedback, enabling further refinement of the solution. The process of testing and refining can continue until the best possible solution is found. Making a Decision After collecting and synthesizing all the relevant information, it is time to choose the most suitable solution. This decision should be based on thorough analysis, feedback, and testing. Confidence in the chosen solution is essential in its successful implementation and execution. In conclusion, to evaluate and choose the best solution for a specific practical problem, one needs to understand the problem, identify and evaluate possible solutions, seek input, test and refine, and finally make a decision based on informed analysis. This structured approach will increase the likelihood of achieving an optimal solution to a complex issue.

How do you determine the most effective approach to solving a complex practical problem?

Understanding the Problem To determine the most effective approach to solving a complex practical problem, one must begin by conducting a thorough analysis of the issue at hand. This involves breaking it down into smaller, manageable components and identifying the key factors that contribute to its complexity. Such a comprehensive understanding of the problem allows for the identification of potential solutions and provides a solid foundation for decision making. Gathering Relevant Information Next, it is crucial to gather as much relevant information as possible, from both quantitative data and qualitative sources. This may involve using research tools to collect and analyze data, consulting experts in the field, and examining best practices from similar situations. The combination of this information provides valuable insight into possible approaches, as well as their potential outcomes and limitations. Evaluating Alternative Approaches An essential step in determining an effective approach to solving a problem is evaluating alternative methods. It involves comparing and contrasting various options, taking into consideration their efficiency, cost, potential impact, and feasibility. Moreover, one should also account for any potential risks or unintended consequences that might arise from a particular approach. Critical Thinking and Creativity An essential component in problem-solving is the application of critical thinking and creativity. This entails the ability to evaluate options objectively and eliminate biases, while also having the flexibility to generate novel ideas and adapt traditional methods as necessary. Through critical thinking and creativity, one is more likely to arrive at a robust and innovative solution to a complex practical problem. Incorporating Stakeholder Perspectives Lastly, effective problem-solving should involve incorporating the perspectives of relevant stakeholders. By considering their needs, expectations, and potential concerns, a solution that addresses the problem in a manner that benefits all parties involved can be identified. Engaging stakeholders in the problem-solving process can also facilitate buy-in and support for the chosen solution, ensuring its successful implementation. In conclusion, determining the most effective approach to solving a complex practical problem requires a thorough understanding of the issue, gathering relevant information, evaluating alternative solutions, applying critical thinking and creativity, and incorporating stakeholder perspectives. By following these guidelines, one is more likely to arrive at a robust and innovative solution that addresses the problem in a practical and efficient manner.

In what ways can collaboration and diverse perspectives enhance practical problem-solving abilities?

Enhancing Problem-Solving Abilities One key element of effective problem-solving is collaboration. Bringing multiple individuals together to approach a unified goal can provide a broader range of ideas, leading to innovative solutions. Additionally, when group members possess diverse perspectives, it equips the team with a wider variety of thought processes and experiences, which can further contribute to improved results. Collaborative Benefits There are several ways in which collaboration can enhance practical problem-solving abilities. Firstly, having multiple individuals tackling a single issue allows for increased creativity, leading to more diverse opinions and a higher likelihood of developing innovative solutions. Secondly, the combined knowledge of all team members can provide a more comprehensive understanding of the problem, including the identification of any potential pitfalls or obstacles. Diverse Perspectives Incorporating diverse perspectives further amplifies the benefits of collaboration. Since individuals from different backgrounds, disciplines, and personal experiences bring unique ways of thinking to the group, this diversity can expand the pool of ideas generated during problem-solving. Additionally, varied viewpoints can inspire new ways of thinking among other team members, leading to a greater range of innovative solutions. Cognitive Diversity Cognitive diversity also plays a significant role in problem-solving enhancement. When team members possess different thinking styles or cognitive abilities, they can more effectively navigate complex issues. For example, the analytical thinker may excel at breaking down a problem, while the creative thinker may imagine alternative approaches. Combining these diverse thought processes can expedite the problem-solving process. Conflict Resolution While collaboration and diverse perspectives can contribute to improved problem-solving, it is important to recognize the potential for conflict within diverse groups. However, this conflict can be advantageous when managed effectively. By facilitating constructive debate and embracing alternative viewpoints, teams can use these tensions to further refine and improve their solutions. In conclusion, collaboration and diverse perspectives significantly enhance practical problem-solving abilities by expanding the range of creative and cognitive abilities within a team. When combined, these factors can inspire innovative solutions, more comprehensive problem analysis, and a greater overall understanding of complex issues.

How can metacognitive strategies be employed to continuously refine and improve one's practical problem-solving skills?

**Understanding Metacognition in Problem-Solving** Metacognitive strategies play a crucial role in refining and improving one's practical problem-solving skills. Metacognition involves self-awareness of one's cognitive processes and the ability to control and regulate these processes (Flavell, 1979). By utilizing metacognitive strategies, individuals can examine their own thought processes, identify areas for improvement, and adjust their approaches to problem-solving tasks. **Applying Metacognitive Strategies** One way to employ metacognitive strategies is through self-questioning. This involves asking oneself questions about the problem-solving process, such as 'What am I trying to achieve?,' 'What strategies am I using?,' and 'How can I adjust my approach to be more effective?' (Ertmer & Newby, 1996). This self-assessment allows individuals to monitor their progress, evaluate their methodology and, if necessary, adjust their process. **Metacognitive Reflection and Evaluation** Regular reflection on one's problem-solving experiences also contributes to metacognitive growth. After completing tasks, individuals may consider the effectiveness of the strategies employed and check if the problem was fully understood before the implementation of the solution. Reflecting on problem-solving experiences enables learners to construct their understanding of which strategies work best in certain situations. **Adapting Problem-Solving Strategies** By developing an ability to regulate the problem-solving process and modify strategies as needed, learners can continuously improve their skills. For instance, individuals may choose to break down complex problems into smaller parts or seek external resources to enhance their understanding. This adaptability in the face of unfamiliar or challenging tasks ultimately leads to better problem-solving performance (Swanson, 1990). **Collaborative Learning and Metacognition** Collaborative learning can also bolster metacognitive development. By engaging in group problem-solving activities, individuals can observe how others approach tasks, reflecting on the similarities and differences between their strategies. This type of social interaction can contribute to the refinement of one's problem-solving skills by offering diverse perspectives and approaches. In conclusion, metacognitive strategies provide a robust framework for the ongoing improvement of practical problem-solving skills. By consistently employing self-questioning, reflection, strategy adaptation, and collaborative learning, individuals can become more aware of their cognitive processes and develop effective and flexible problem-solving abilities.

How can the application of critical thinking skills enhance practical problem-solving?

Developing Critical Thinking Skills The application of critical thinking skills can significantly enhance practical problem-solving by fostering a comprehensive understanding of issues and situations at hand. Critical thinking is an essential attribute in navigating complex problems while considering various perspectives, thus promoting informed decision-making. Implementing this approach enables individuals to identify potential obstacles, assess possible solutions, and verify the effectiveness of chosen strategies. Effective Analysis and Evaluation Applying critical thinking skills involves careful analysis and evaluation of all aspects of a problem, ensuring various angles and viewpoints are considered. This comprehensive approach aids in identifying the root cause of an issue, eliminating potential assumptions and biases. Furthermore, it encourages individuals to consider multiple alternatives, enhancing creativity in devising problem-solving strategies. The consideration of alternative perspectives also prevents the dismissal of potential solutions due to personal biases or limited knowledge. Ethical and Logical Considerations Incorporating critical thinking into practical problem-solving involves applying ethical and logical considerations in the decision-making process. This entails questioning and examining underlying assumptions, as well as identifying inconsistencies and fallacies in presented arguments. Such a practice promotes rationality and objectivity, fostering informed decisions and effective solutions. Moreover, an emphasis on ethical considerations helps maintain integrity and fairness, ensuring responsible resolution of issues that may have broader societal implications. Continuous Improvement and Reflexivity Another advantage of critical thinking in problem-solving is the promotion of continuous improvement and reflexivity. By consistently reflecting on one's problem-solving processes and strategies, critical thinkers become more adaptive and resilient in addressing challenges. This practice of self-improvement leads to a growth mindset, allowing for the enhancement and refinement of problem-solving skills over time. In conclusion, the application of critical thinking skills significantly enhances practical problem-solving, offering a comprehensive, ethical, and logical approach to complex issues. Emphasis on analysis, evaluation, and reflexivity ensures informed decision-making and fosters continuous improvement. Ultimately, developing critical thinking skills promotes more effective problem-solving and adaptability within various contexts.

What role does adaptability play in successfully tackling practical problems?

Role of Adaptability in Problem Solving Adaptability is crucial for successfully tackling practical problems. It allows individuals and organizations to thrive amid change by accepting novel situations and altering their perspectives, behaviors, and strategies according to the new context. Moreover, in a rapidly evolving world, adaptability promotes innovative thinking and enhances effectiveness in problem solving. Flexible Mindset and Creative Approaches Developing a flexible mindset is essential in recognizing the need for change and adapting to it. A rigid approach often leads to stagnation and missed opportunities. In contrast, flexibility invites alternative solutions and encourages individuals to challenge their preconceptions. Consequently, one becomes more open to embracing new ideas and methods for resolving practical issues. Learning from Experience and Applying Knowledge When confronted with problems, adaptive individuals can draw on their experiences and acquired knowledge. By reflecting on past situations, they can discern patterns and derive insights, ultimately shaping their future course of action. Adaptability, thus, enables one to gather relevant information and apply it in different contexts, effectively utilizing past lessons to solve present and future challenges. Embracing Technology and Collaborating Being adaptable also encompasses embracing technological advancements, which facilitate problem-solving processes. These advancements can help in modeling complex problems, simulating potential outcomes, and optimizing solutions. Additionally, adaptability also involves recognizing the necessity of collaboration to pool expertise, fostering diverse perspectives that contribute to more innovative and effective solutions. Coping with Uncertainty and Ambiguity Lastly, adaptability helps in navigating the inherent uncertainty and ambiguity that come with practical problems. By embracing uncertainty and refusing to seek absolute certainty, one becomes more resilient and capable of dealing with unexpected challenges. This capacity is central to forging a path forward and arriving at a solution, even in the face of obstacles and setbacks. In summary, adaptability is indispensable for effectively tackling practical problems. A flexible mindset, the ability to learn from experience, embracing technology, collaboration, and coping with uncertainty form the foundations of adaptability. Developing these skills will help individuals and organizations navigate the ever-changing landscape of problem-solving, ultimately ensuring success in their endeavors.

How can an understanding of cognitive biases help in optimizing practical problem-solving techniques?

**Cognitive Biases and Problem-Solving** Understanding cognitive biases is crucial in optimizing practical problem-solving techniques, as awareness of these biases allows individuals to identify and rectify any skewed perceptions that may hinder their ability to accurately assess and solve complex issues. A cognitive bias is a systematic pattern of deviation from rationality, where individuals may perceive information or stimuli in an illogical or irrational manner. By recognizing these biases, individuals can implement strategies that counteract their influence and improve their problem-solving skills. **Identifying the Impact of Biases** Cognitive biases can impede accuracy and efficiency while working on problems. For example, individuals may fall into the 'confirmation bias' trap, only seeking information that supports their preconceived beliefs and ignoring conflicting evidence. To counteract this bias, individuals should actively search for alternative viewpoints and disconfirming evidence. This broadens their understanding of the problem, resulting in a more comprehensive and well-rounded solution. **Utilizing Debiasing Techniques** Applying debiasing techniques in problem-solving activities can enhance cognitive performance. For instance, 'considering the opposite' technique involves purposefully thinking about how opposing views or circumstances might affect the problem at hand. This helps the individual to challenge their assumptions and think creatively about potential solutions. Another useful strategy is working collaboratively in diverse groups. Different perspectives and thought processes can expose and challenge biased thinking, leading to more robust problem-solving. **Promoting Mindfulness and Awareness** Developing mindfulness and a heightened sense of self-awareness is a valuable tool in managing cognitive biases and improving problem-solving outcomes. By adopting a mindfulness practice, individuals can become more aware of their thoughts and biases, which in turn allows them to make more objective and rational decisions. Training in mindfulness techniques, such as meditation or journaling, can empower individuals to reflect on their thinking patterns, recognize cognitive biases, and focus on finding optimal solutions to problems. In conclusion, understanding cognitive biases and incorporating tools to counteract their effects can significantly optimize practical problem-solving techniques. By identifying these biases and implementing debiasing strategies, as well as fostering mindfulness and self-awareness, individuals are more likely to develop innovative and effective solutions to the challenges they face.

How can I improve my practical problem-solving skills?

Develop a Problem-Solving Mindset Aiming to improve practical problem-solving skills requires a shift in mindset. Embrace problems as opportunities for growth and learning rather than obstacles. Practice Critical Thinking Integrating critical thinking into your daily routine can help. This involves considering different perspectives, evaluating logical connections, and drawing conclusions based on evidence. Boost Creativity Creative thinking helps generate insightful solutions to problems. Engage in activities that stimulate creativity, such as brainstorming, mind mapping, or doing arts and crafts. Learn from Others Look for individuals or groups who are renowned for their problem-solving skills. Observe how they approach issues. Pull lessons from their methods and apply them to your own problem-solving processes. Apply Problem-Solving Frameworks Implementing recognized problem-solving frameworks, like SWOT analysis, root cause analysis, or design thinking, can structure your approach. This structured approach enhances the effectiveness of problem-solving endeavors. Reflect on Past Experiences Consider past situations where problem-solving was required. Reflect on the approach used, the results achieved, and the lessons learned. This introspection can inform future actions. Invest in Self-Improvement Continuous education promotes growth in all areas, including problem-solving. Consider enrolling in online courses or attending workshops aimed at enhancing such skills. Solve Puzzles and Games Solving puzzles and engaging in brain games builds cognitive capabilities, enhancing problem-solving skills. They also test your ability to strategize, think creatively, and make decisions under pressure. Encourage Feedback Feedback helps pinpoint areas of improvement. Encourage others to provide constructive criticism on your problem-solving strategies and refine them accordingly. Persistently Practice Like any skill, practical problem-solving becomes stronger through consistent practice. Dedicate time regularly to tackle problems, persevere in finding solutions, and learn from each experience. In conclusion, improving practical problem-solving skills requires a multimodal approach. By fostering a forward-thinking mindset and continuously engaging in strategies to stimulate cognitive growth, you can considerably enhance your problem-solving abilities.

What are the six steps of the practical problem-solving process?

Identifying the Problem The practical problem-solving process commences with identifying the problem. This step involves understanding the issue in depth and distinguishing it from symptoms, assumptions, or opinions. Establishing Objectives Next, objectives or desired outcomes are defined. Clear objectives provide a valuable direction and help to formulate solutions. Objectives should always be specific, measurable, achievable, relevant and time-bound. Investigating and Analyzing the Problem A thorough investigation follows the establishment of objectives. This encompasses gathering all relevant data and verifying its accuracy. Analyzing this information can then unearth root causes and contributing factors. Generating Solutions The fourth step in the process calls for generating potential solutions to the analyzed problem. This stage encourages creative thinking and involves brainstorming a range of options with no immediate judgment passed on their viability. Evaluating and Presenting Solutions Each solution must then be critically evaluated against the objectives, feasibility, and potential impact. The viable solutions are further refined and presented in a coherent, persuasive manner to decision-makers or stakeholders. Implementing the Solution The chosen solution is finally implemented in the last step. This crucial phase requires meticulous planning, defining roles and responsibilities, and executing the plan while monitoring progress. Continuous learning from this phase aids in future problem-solving endeavors. In conclusion, the six steps in the practical problem-solving process offer a structured approach to tackling issues. Each step plays a significant role to ensure the solution is effective, reasonable, and beneficial for all.

What are the 7 steps to problem-solving skills?

Understanding the Seven Steps of Problem-Solving Identifying the Problem The initial step in problem-solving involves determining the actual problem. The step entails understanding what you're attempting to resolve and why it should be addressed. Understanding the Problem The understanding process involves obtaining a clear picture of the problem. This step necessitates data gathering, noting who it affects, identifying root causes, and defining consequences. Generating Possible Solutions The third step involves brainstorming potential solutions. This process should be inclusive and creative to capture a wide range of solutions. Analyzing Potential Solutions Next, sift through the suggested solutions and examine them in terms of feasibility and impact. It's essential to consider both the advantages and drawbacks of each option. Choosing the Best Solution After analyzing potential solutions, select the one you believe most effective. This decision typically requires a delicate balance of practicability, impact, and resources available. Implementing the Solution Once you choose the best solution, it's time for implementation. Put your chosen solution into action, ensuring you've defined roles and responsibilities, and you've got a plan to monitor the progress. Reviewing the Outcome Finally, evaluate the results after implementing the solution. This review confirms whether the solution worked or if the problem remains. You may need to revisit previous steps and explore other solutions if the issue persists. In summary, the seven steps to problem-solving skills include identifying the problem, understanding the problem, generating possible solutions, analyzing these solutions, choosing the best solution, implementing the chosen solution, and reviewing the outcome. These steps, when utilized appropriately, can enhance one's ability to solve issues effectively, leading to more successful, efficient, and satisfactory outcomes.

How can I develop my capacity to adapt and respond effectively in unpredictable problem-solving situations?

Understanding the Situation To develop your ability to adapt in unpredictable problem-solving situations, first, understand the situation comprehensibly. Recognize factors, elements, and potential outcomes. Comprehend the context and relevance of the problem in bigger picture. Strengthening Senses Observation Refining your observational skills can significantly enhance adaptive capability. Paying sharp attention to nuances, hidden details, and subtle changes often provide cues to navigate through uncertainties. Stimulating Creative Thinking Encourage creative thinking for finding innovative solutions. Creativity expedites problem-solving by driving you to think outside the box, observe from different perspectives and inspect unorthodox solution methods. Training with Simulated Scenarios Simulated training can remarkably improve your adaptive abilities. Facing a variety of hypothetical situations can enrich both cognitive flexibility and problem-solving skills in dynamic conditions. Encouraging Learning from Failures Embrace setbacks as avenues for learning. Failures often offer valuable insights into what doesn't work, thus enhancing our ability to adapt and respond effectively. Emphasizing Emotional Intelligence Developing emotional intelligence aids in managing stress during unpredictable situations. It helps to maintain a positive attitude, stay focused, and make balanced decisions amidst adversities. Maintaining Self-Belief Have faith in your abilities. Self-belief is instrumental in tackling unknown territories as it fuels perseverance, resilience, and courage to face any problem. Promoting Continuous Learning Promote a culture of continuous learning. Mastery over new skills and knowledge enhances adaptation ability. Stay versatile to adjust with evolving scenarios and to incorporate newfound learnings readily. In essence, enhancing adaptation in unforeseen problem-solving situations requires understanding the situation, strengthening observational skills, fostering creativity, getting trained in simulated environments, learning from failures, honing emotional intelligence, believing in oneself, and encouraging constant learning. By strengthening these areas, one could face challenges head-on and navigate through unpredictable situations confidently.

In what ways can upskilling in interdisciplinary knowledge contribute to enhancing practical problem-solving skills?

Enhanced Understanding through Interdisciplinary Knowledge Upskilling in interdisciplinary knowledge can foster enhanced understanding of varied domains. Being skilled in different study areas provides a unique amalgam of insights. It ruptures the traditional silos of knowledge, triggering innovative thinking. Boosting Problem-Solving Ability This innovative thinking in turn empowers the practical problem-solving skills. Decision-making models that include more than one discipline heighten the potential for comprehensive solutions. The blended expertise helps in deconstructing complex problems into manageable parts. Boosting Innovation Interdisciplinary knowledge escalates innovation. It equips individuals with diverse perspectives, fueling creativity. Fresh, innovative solutions often emerge from this amalgamation of varying viewpoints. As result, problem solving extends beyond the routine approaches. Facilitating Collaboration Interdisciplinary skills facilitate collaboration. Working as a team means encountering various perspectives. Adequate knowledge about diverse fields aids communication and understanding among team members. Improved collaboration results in effective problem-solving. Broadened Horizon Interdisciplinary skills foster a broader horizon, intensifying curiosity. They equip individuals to explore unfamiliar territories and face new challenges with confidence. This eagerness to explore further magnifies problem-solving capacities. In short, upskilling in interdisciplinary knowledge acts as a catalyzer, enhancing practical problem-solving skills. It not only instills innovative, comprehensive, and collaborative approaches, but also broadens horizons, boosting problem-solving capabilities. Hence, acquiring interdisciplinary knowledge and skills is crucial in today's complex and interconnected world.

How can I incorporate effective feedback and reflection techniques to continuously refine my problem-solving capabilities?

Importance of Feedback Integrating effective feedback is paramount to refining problem-solving skills. Feedback offers clear evidence of your thought processes and indicates areas for improvement. Encourage feedback from peers, mentors, and teachers. Established channels of open and honest communication can act as a support system to guide your growth. Reflection Techniques Reflection, on the other hand, lets you critically examine your problem-solving procedure. Use reflective journals to jot down your experiences, noting what went well, what didn't, and potential areas of improvement. Analyze these experiences and identify the strategies that worked best. Adopting Experimentation Experimentation encourages a trial-and-error approach. It promotes risk-taking and resilience in the face of unsuccessful attempts. Learn from these failures and use them as stepping-stones to devise new, innovative strategies. Leveraging Collaborative Problem Solving Collaborative problem-solving introduces new perspectives. Explain your problem-solving approach to others and grasp their suggestions. Diverse viewpoints can spark creativity and faster solution finding. Include these insights in your problem-solving toolkit. Continuous Learning Continuous learning is crucial for constant refinement of skills. Embarking on lifelong learning equips you with new techniques that can supplement your existing problem-solving chops. Enrolling in online courses or attending workshops can provide deeper insights. In sum, effectively incorporating feedback and reflection techniques can sharpen your problem-solving abilities. Experimentation and collaboration serve to further enhance these skills. Continuous learning is ultimately the key to stay updated with evolving best practices and strategies.

SHe is a graduate of Akdeniz University, Department of Business Administration. She graduated from the university with a faculty degree. It has contributed to its environment with its social responsibility project. She writes articles about business and its fields.

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45 Research Problem Examples & Inspiration

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

Learn about our Editorial Process

A research problem is an issue of concern that is the catalyst for your research. It demonstrates why the research problem needs to take place in the first place.

Generally, you will write your research problem as a clear, concise, and focused statement that identifies an issue or gap in current knowledge that requires investigation.

The problem will likely also guide the direction and purpose of a study. Depending on the problem, you will identify a suitable methodology that will help address the problem and bring solutions to light.

Research Problem Examples

In the following examples, I’ll present some problems worth addressing, and some suggested theoretical frameworks and research methodologies that might fit with the study. Note, however, that these aren’t the only ways to approach the problems. Keep an open mind and consult with your dissertation supervisor!

Psychology Problems

1. Social Media and Self-Esteem: “How does prolonged exposure to social media platforms influence the self-esteem of adolescents?”

• Theoretical Framework : Social Comparison Theory
• Methodology : Longitudinal study tracking adolescents’ social media usage and self-esteem measures over time, combined with qualitative interviews.

2. Sleep and Cognitive Performance: “How does sleep quality and duration impact cognitive performance in adults?”

• Theoretical Framework : Cognitive Psychology
• Methodology : Experimental design with controlled sleep conditions, followed by cognitive tests. Participant sleep patterns can also be monitored using actigraphy.

3. Childhood Trauma and Adult Relationships: “How does unresolved childhood trauma influence attachment styles and relationship dynamics in adulthood?

• Theoretical Framework : Attachment Theory
• Methodology : Mixed methods, combining quantitative measures of attachment styles with qualitative in-depth interviews exploring past trauma and current relationship dynamics.

4. Mindfulness and Stress Reduction: “How effective is mindfulness meditation in reducing perceived stress and physiological markers of stress in working professionals?”

• Theoretical Framework : Humanist Psychology
• Methodology : Randomized controlled trial comparing a group practicing mindfulness meditation to a control group, measuring both self-reported stress and physiological markers (e.g., cortisol levels).

5. Implicit Bias and Decision Making: “To what extent do implicit biases influence decision-making processes in hiring practices?

• Theoretical Framework : Cognitive Dissonance Theory
• Methodology : Experimental design using Implicit Association Tests (IAT) to measure implicit biases, followed by simulated hiring tasks to observe decision-making behaviors.

6. Emotional Regulation and Academic Performance: “How does the ability to regulate emotions impact academic performance in college students?”

• Theoretical Framework : Cognitive Theory of Emotion
• Methodology : Quantitative surveys measuring emotional regulation strategies, combined with academic performance metrics (e.g., GPA).

7. Nature Exposure and Mental Well-being: “Does regular exposure to natural environments improve mental well-being and reduce symptoms of anxiety and depression?”

• Theoretical Framework : Biophilia Hypothesis
• Methodology : Longitudinal study comparing mental health measures of individuals with regular nature exposure to those without, possibly using ecological momentary assessment for real-time data collection.

8. Video Games and Cognitive Skills: “How do action video games influence cognitive skills such as attention, spatial reasoning, and problem-solving?”

• Theoretical Framework : Cognitive Load Theory
• Methodology : Experimental design with pre- and post-tests, comparing cognitive skills of participants before and after a period of action video game play.

9. Parenting Styles and Child Resilience: “How do different parenting styles influence the development of resilience in children facing adversities?”

• Theoretical Framework : Baumrind’s Parenting Styles Inventory
• Methodology : Mixed methods, combining quantitative measures of resilience and parenting styles with qualitative interviews exploring children’s experiences and perceptions.

10. Memory and Aging: “How does the aging process impact episodic memory , and what strategies can mitigate age-related memory decline?

• Theoretical Framework : Information Processing Theory
• Methodology : Cross-sectional study comparing episodic memory performance across different age groups, combined with interventions like memory training or mnemonic strategies to assess potential improvements.

Education Problems

11. Equity and Access : “How do socioeconomic factors influence students’ access to quality education, and what interventions can bridge the gap?

• Theoretical Framework : Critical Pedagogy
• Methodology : Mixed methods, combining quantitative data on student outcomes with qualitative interviews and focus groups with students, parents, and educators.

12. Digital Divide : How does the lack of access to technology and the internet affect remote learning outcomes, and how can this divide be addressed?

• Theoretical Framework : Social Construction of Technology Theory
• Methodology : Survey research to gather data on access to technology, followed by case studies in selected areas.

13. Teacher Efficacy : “What factors contribute to teacher self-efficacy, and how does it impact student achievement?”

• Theoretical Framework : Bandura’s Self-Efficacy Theory
• Methodology : Quantitative surveys to measure teacher self-efficacy, combined with qualitative interviews to explore factors affecting it.

14. Curriculum Relevance : “How can curricula be made more relevant to diverse student populations, incorporating cultural and local contexts?”

• Theoretical Framework : Sociocultural Theory
• Methodology : Content analysis of curricula, combined with focus groups with students and teachers.

15. Special Education : “What are the most effective instructional strategies for students with specific learning disabilities?

• Theoretical Framework : Social Learning Theory
• Methodology : Experimental design comparing different instructional strategies, with pre- and post-tests to measure student achievement.

16. Dropout Rates : “What factors contribute to high school dropout rates, and what interventions can help retain students?”

• Methodology : Longitudinal study tracking students over time, combined with interviews with dropouts.

17. Bilingual Education : “How does bilingual education impact cognitive development and academic achievement?

• Methodology : Comparative study of students in bilingual vs. monolingual programs, using standardized tests and qualitative interviews.

18. Classroom Management: “What reward strategies are most effective in managing diverse classrooms and promoting a positive learning environment?

• Theoretical Framework : Behaviorism (e.g., Skinner’s Operant Conditioning)
• Methodology : Observational research in classrooms , combined with teacher interviews.

19. Standardized Testing : “How do standardized tests affect student motivation, learning, and curriculum design?”

• Theoretical Framework : Critical Theory
• Methodology : Quantitative analysis of test scores and student outcomes, combined with qualitative interviews with educators and students.

20. STEM Education : “What methods can be employed to increase interest and proficiency in STEM (Science, Technology, Engineering, and Mathematics) fields among underrepresented student groups?”

• Theoretical Framework : Constructivist Learning Theory
• Methodology : Experimental design comparing different instructional methods, with pre- and post-tests.

21. Social-Emotional Learning : “How can social-emotional learning be effectively integrated into the curriculum, and what are its impacts on student well-being and academic outcomes?”

• Theoretical Framework : Goleman’s Emotional Intelligence Theory
• Methodology : Mixed methods, combining quantitative measures of student well-being with qualitative interviews.

22. Parental Involvement : “How does parental involvement influence student achievement, and what strategies can schools use to increase it?”

• Theoretical Framework : Reggio Emilia’s Model (Community Engagement Focus)
• Methodology : Survey research with parents and teachers, combined with case studies in selected schools.

23. Early Childhood Education : “What are the long-term impacts of quality early childhood education on academic and life outcomes?”

• Theoretical Framework : Erikson’s Stages of Psychosocial Development
• Methodology : Longitudinal study comparing students with and without early childhood education, combined with observational research.

24. Teacher Training and Professional Development : “How can teacher training programs be improved to address the evolving needs of the 21st-century classroom?”

• Theoretical Framework : Adult Learning Theory (Andragogy)
• Methodology : Pre- and post-assessments of teacher competencies, combined with focus groups.

25. Educational Technology : “How can technology be effectively integrated into the classroom to enhance learning, and what are the potential drawbacks or challenges?”

• Theoretical Framework : Technological Pedagogical Content Knowledge (TPACK)
• Methodology : Experimental design comparing classrooms with and without specific technologies, combined with teacher and student interviews.

Sociology Problems

26. Urbanization and Social Ties: “How does rapid urbanization impact the strength and nature of social ties in communities?”

• Theoretical Framework : Structural Functionalism
• Methodology : Mixed methods, combining quantitative surveys on social ties with qualitative interviews in urbanizing areas.

27. Gender Roles in Modern Families: “How have traditional gender roles evolved in families with dual-income households?”

• Theoretical Framework : Gender Schema Theory
• Methodology : Qualitative interviews with dual-income families, combined with historical data analysis.

28. Social Media and Collective Behavior: “How does social media influence collective behaviors and the formation of social movements?”

• Theoretical Framework : Emergent Norm Theory
• Methodology : Content analysis of social media platforms, combined with quantitative surveys on participation in social movements.

29. Education and Social Mobility: “To what extent does access to quality education influence social mobility in socioeconomically diverse settings?”

• Methodology : Longitudinal study tracking educational access and subsequent socioeconomic status, combined with qualitative interviews.

30. Religion and Social Cohesion: “How do religious beliefs and practices contribute to social cohesion in multicultural societies?”

• Methodology : Quantitative surveys on religious beliefs and perceptions of social cohesion, combined with ethnographic studies.

31. Consumer Culture and Identity Formation: “How does consumer culture influence individual identity formation and personal values?”

• Theoretical Framework : Social Identity Theory
• Methodology : Mixed methods, combining content analysis of advertising with qualitative interviews on identity and values.

32. Migration and Cultural Assimilation: “How do migrants negotiate cultural assimilation and preservation of their original cultural identities in their host countries?”

• Theoretical Framework : Post-Structuralism
• Methodology : Qualitative interviews with migrants, combined with observational studies in multicultural communities.

33. Social Networks and Mental Health: “How do social networks, both online and offline, impact mental health and well-being?”

• Theoretical Framework : Social Network Theory
• Methodology : Quantitative surveys assessing social network characteristics and mental health metrics, combined with qualitative interviews.

34. Crime, Deviance, and Social Control: “How do societal norms and values shape definitions of crime and deviance, and how are these definitions enforced?”

• Theoretical Framework : Labeling Theory
• Methodology : Content analysis of legal documents and media, combined with ethnographic studies in diverse communities.

35. Technology and Social Interaction: “How has the proliferation of digital technology influenced face-to-face social interactions and community building?”

• Theoretical Framework : Technological Determinism
• Methodology : Mixed methods, combining quantitative surveys on technology use with qualitative observations of social interactions in various settings.

Nursing Problems

36. Patient Communication and Recovery: “How does effective nurse-patient communication influence patient recovery rates and overall satisfaction with care?”

• Methodology : Quantitative surveys assessing patient satisfaction and recovery metrics, combined with observational studies on nurse-patient interactions.

37. Stress Management in Nursing: “What are the primary sources of occupational stress for nurses, and how can they be effectively managed to prevent burnout?”

• Methodology : Mixed methods, combining quantitative measures of stress and burnout with qualitative interviews exploring personal experiences and coping mechanisms.

38. Hand Hygiene Compliance: “How effective are different interventions in improving hand hygiene compliance among nursing staff, and what are the barriers to consistent hand hygiene?”

• Methodology : Experimental design comparing hand hygiene rates before and after specific interventions, combined with focus groups to understand barriers.

39. Nurse-Patient Ratios and Patient Outcomes: “How do nurse-patient ratios impact patient outcomes, including recovery rates, complications, and hospital readmissions?”

• Methodology : Quantitative study analyzing patient outcomes in relation to staffing levels, possibly using retrospective chart reviews.

40. Continuing Education and Clinical Competence: “How does regular continuing education influence clinical competence and confidence among nurses?”

• Methodology : Longitudinal study tracking nurses’ clinical skills and confidence over time as they engage in continuing education, combined with patient outcome measures to assess potential impacts on care quality.

Communication Studies Problems

41. Media Representation and Public Perception: “How does media representation of minority groups influence public perceptions and biases?”

• Theoretical Framework : Cultivation Theory
• Methodology : Content analysis of media representations combined with quantitative surveys assessing public perceptions and attitudes.

42. Digital Communication and Relationship Building: “How has the rise of digital communication platforms impacted the way individuals build and maintain personal relationships?”

• Theoretical Framework : Social Penetration Theory
• Methodology : Mixed methods, combining quantitative surveys on digital communication habits with qualitative interviews exploring personal relationship dynamics.

43. Crisis Communication Effectiveness: “What strategies are most effective in managing public relations during organizational crises, and how do they influence public trust?”

• Theoretical Framework : Situational Crisis Communication Theory (SCCT)
• Methodology : Case study analysis of past organizational crises, assessing communication strategies used and subsequent public trust metrics.

44. Nonverbal Cues in Virtual Communication: “How do nonverbal cues, such as facial expressions and gestures, influence message interpretation in virtual communication platforms?”

• Theoretical Framework : Social Semiotics
• Methodology : Experimental design using video conferencing tools, analyzing participants’ interpretations of messages with varying nonverbal cues.

45. Influence of Social Media on Political Engagement: “How does exposure to political content on social media platforms influence individuals’ political engagement and activism?”

• Theoretical Framework : Uses and Gratifications Theory
• Methodology : Quantitative surveys assessing social media habits and political engagement levels, combined with content analysis of political posts on popular platforms.

Before you Go: Tips and Tricks for Writing a Research Problem

This is an incredibly stressful time for research students. The research problem is going to lock you into a specific line of inquiry for the rest of your studies.

So, here’s what I tend to suggest to my students:

• Start with something you find intellectually stimulating – Too many students choose projects because they think it hasn’t been studies or they’ve found a research gap. Don’t over-estimate the importance of finding a research gap. There are gaps in every line of inquiry. For now, just find a topic you think you can really sink your teeth into and will enjoy learning about.
• Take 5 ideas to your supervisor – Approach your research supervisor, professor, lecturer, TA, our course leader with 5 research problem ideas and run each by them. The supervisor will have valuable insights that you didn’t consider that will help you narrow-down and refine your problem even more.
• Trust your supervisor – The supervisor-student relationship is often very strained and stressful. While of course this is your project, your supervisor knows the internal politics and conventions of academic research. The depth of knowledge about how to navigate academia and get you out the other end with your degree is invaluable. Don’t underestimate their advice.

I’ve got a full article on all my tips and tricks for doing research projects right here – I recommend reading it:

• 9 Tips on How to Choose a Dissertation Topic

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 25 Classroom Wall Decoration Ideas
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Mathematicians Are Edging Close to Solving One of the World's 7 Hardest Math Problems

And there’s $1 million at stake.

• In new research, mathematicians have narrowed down one of the biggest outstanding problems in math.
• Huge breakthroughs in math and science are usually the work of many people over many years.
• Seven math problems were given a $1 million bounty each in 2000, and just one has been solved so far.

The “Millennium Problems” are seven infamously intractable math problems laid out in the year 2000 by the prestigious Clay Institute, each with $1 million attached as payment for a solution. They span all areas of math , as the Clay Institute was founded in 1998 to push the entire field forward with financial support for researchers and important breakthroughs.

But the only solved Millennium Problem so far, the Poincare conjecture, illustrates one of the funny pitfalls inherent to offering a large cash prize for math. The winner, Grigori Perelman, refused the Clay prize as well as the prestigious Fields Medal. He withdrew from mathematics and public life in 2006, and even in 2010, he still insisted his contribution was the same as the mathematician whose work laid the foundation on which he built his proof, Richard Hamilton.

Math, all sciences, and arguably all human inquiries are filled with pairs or groups that circle the same finding at the same time until one officially makes the breakthrough. Think about Sir Isaac Newton and Gottfried Leibniz, whose back-and-forth about calculus led to the combined version of the field we still study today. Rosalind Franklin is now mentioned in the same breath as her fellow discoverers of DNA, James Watson and Francis Crick. Even the Bechdel Test for women in media is sometimes called the Bechdel-Wallace Test, because humans are almost always in collaboration.

That’s what makes this new paper so important. Two mathematicians—Larry Guth of the Massachusetts Institute of Technology (MIT) and James Maynard of the University of Oxford—collaborated on the new finding about how certain polynomials are formed and how they reach out into the number line. Maynard is just 37, and won the Fields Medal himself in 2022. Guth, a decade older, has won a number of important prizes with a little less name recognition.

The Riemann hypothesis is not directly related to prime numbers , but it has implications that ripple through number theory in different ways (including with prime numbers). Basically, it deals with where and how the graph of a certain function of complex numbers crosses back and forth across axes. The points where the function crosses an axis is called a “zero,” and the frequency with which those zeroes appear is called the zero density.

In the far reaches of the number line, prime numbers become less and less predictable (in the proverbial sense). They are not, so far, predictable in the literal sense—a fact that is an underpinning of modern encryption , where data is protected by enormous strings of integers made by multiplying enormous prime numbers together. The idea of a periodic table of primes, of any kind of template that could help mathematicians better understand where and how large primes cluster together or not, is a holy grail.

In the new paper, Maynard and Guth focus on a new limitation of Dirichlet polynomials. These are special series of complex numbers that many believe are of the same type as the function involved in the Riemann hypothesis involves. In the paper, they claim they’ve proven that these polynomials have a certain number of large values, or solutions , within a tighter range than before.

In other words, if we knew there might be an estimated three Dirichlet values between 50 and 100 before, now we may know that range to be between 60 and 90 instead. The eye exam just switched a blurry plate for a slightly less blurry one, but we still haven’t found the perfect prescription. “If one knows some more structure about the set of large values of a Dirichlet polynomial, then one can hope to have improved bound,” Maynard and Guth conclude.

No, this is not a final proof of the Riemann hypothesis. But no one is suggesting it is. In advanced math, narrowing things down is also vital. Indeed, even finding out that a promising idea turns out to be wrong can have a lot of value—as it has a number of times in the related Twin Primes Conjecture that still eludes mathematicians.

In a collaboration that has lasted 160 years and counting, mathematicians continue to take each step together and then, hopefully, compare notes.

Caroline Delbert is a writer, avid reader, and contributing editor at Pop Mech. She's also an enthusiast of just about everything. Her favorite topics include nuclear energy, cosmology, math of everyday things, and the philosophy of it all. 

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