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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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Center for Teaching

Group work: using cooperative learning groups effectively.

Many instructors from disciplines across the university use group work to enhance their students’ learning. Whether the goal is to increase student understanding of content, to build particular transferable skills, or some combination of the two, instructors often turn to small group work to capitalize on the benefits of peer-to-peer instruction. This type of group work is formally termed cooperative learning, and is defined as the instructional use of small groups to promote students working together to maximize their own and each other’s learning (Johnson, et al., 2008).

Cooperative learning is characterized by positive interdependence, where students perceive that better performance by individuals produces better performance by the entire group (Johnson, et al., 2014). It can be formal or informal, but often involves specific instructor intervention to maximize student interaction and learning. It is infinitely adaptable, working in small and large classes and across disciplines, and can be one of the most effective teaching approaches available to college instructors.

What can it look like?

What’s the theoretical underpinning, is there evidence that it works.

• What are approaches that can help make it effective?

Informal cooperative learning groups In informal cooperative learning, small, temporary, ad-hoc groups of two to four students work together for brief periods in a class, typically up to one class period, to answer questions or respond to prompts posed by the instructor.

Additional examples of ways to structure informal group work

Think-pair-share

The instructor asks a discussion question. Students are instructed to think or write about an answer to the question before turning to a peer to discuss their responses. Groups then share their responses with the class.

Peer Instruction

This modification of the think-pair-share involves personal responses devices (e.g. clickers). The question posted is typically a conceptually based multiple-choice question. Students think about their answer and vote on a response before turning to a neighbor to discuss. Students can change their answers after discussion, and “sharing” is accomplished by the instructor revealing the graph of student response and using this as a stimulus for large class discussion. This approach is particularly well-adapted for large classes.

In this approach, groups of students work in a team of four to become experts on one segment of new material, while other “expert teams” in the class work on other segments of new material. The class then rearranges, forming new groups that have one member from each expert team. The members of the new team then take turns teaching each other the material on which they are experts.

Formal cooperative learning groups

In formal cooperative learning students work together for one or more class periods to complete a joint task or assignment (Johnson et al., 2014). There are several features that can help these groups work well:

• The instructor defines the learning objectives for the activity and assigns students to groups.
• The groups are typically heterogeneous, with particular attention to the skills that are needed for success in the task.
• Within the groups, students may be assigned specific roles, with the instructor communicating the criteria for success and the types of social skills that will be needed.
• Importantly, the instructor continues to play an active role during the groups’ work, monitoring the work and evaluating group and individual performance.
• Instructors also encourage groups to reflect on their interactions to identify potential improvements for future group work.

This video shows an example of formal cooperative learning groups in David Matthes’ class at the University of Minnesota:

There are many more specific types of group work that fall under the general descriptions given here, including team-based learning , problem-based learning , and process-oriented guided inquiry learning .

The use of cooperative learning groups in instruction is based on the principle of constructivism, with particular attention to the contribution that social interaction can make. In essence, constructivism rests on the idea that individuals learn through building their own knowledge, connecting new ideas and experiences to existing knowledge and experiences to form new or enhanced understanding (Bransford, et al., 1999). The consideration of the role that groups can play in this process is based in social interdependence theory, which grew out of Kurt Koffka’s and Kurt Lewin’s identification of groups as dynamic entities that could exhibit varied interdependence among members, with group members motivated to achieve common goals. Morton Deutsch conceptualized varied types of interdependence, with positive correlation among group members’ goal achievements promoting cooperation.

Lev Vygotsky extended this work by examining the relationship between cognitive processes and social activities, developing the sociocultural theory of development. The sociocultural theory of development suggests that learning takes place when students solve problems beyond their current developmental level with the support of their instructor or their peers. Thus both the idea of a zone of proximal development, supported by positive group interdependence, is the basis of cooperative learning (Davidson and Major, 2014; Johnson, et al., 2014).

Cooperative learning follows this idea as groups work together to learn or solve a problem, with each individual responsible for understanding all aspects. The small groups are essential to this process because students are able to both be heard and to hear their peers, while in a traditional classroom setting students may spend more time listening to what the instructor says.

Cooperative learning uses both goal interdependence and resource interdependence to ensure interaction and communication among group members. Changing the role of the instructor from lecturing to facilitating the groups helps foster this social environment for students to learn through interaction.

David Johnson, Roger Johnson, and Karl Smith performed a meta-analysis of 168 studies comparing cooperative learning to competitive learning and individualistic learning in college students (Johnson et al., 2006). They found that cooperative learning produced greater academic achievement than both competitive learning and individualistic learning across the studies, exhibiting a mean weighted effect size of 0.54 when comparing cooperation and competition and 0.51 when comparing cooperation and individualistic learning. In essence, these results indicate that cooperative learning increases student academic performance by approximately one-half of a standard deviation when compared to non-cooperative learning models, an effect that is considered moderate. Importantly, the academic achievement measures were defined in each study, and ranged from lower-level cognitive tasks (e.g., knowledge acquisition and retention) to higher level cognitive activity (e.g., creative problem solving), and from verbal tasks to mathematical tasks to procedural tasks. The meta-analysis also showed substantial effects on other metrics, including self-esteem and positive attitudes about learning. George Kuh and colleagues also conclude that cooperative group learning promotes student engagement and academic performance (Kuh et al., 2007).

Springer, Stanne, and Donovan (1999) confirmed these results in their meta-analysis of 39 studies in university STEM classrooms. They found that students who participated in various types of small-group learning, ranging from extended formal interactions to brief informal interactions, had greater academic achievement, exhibited more favorable attitudes towards learning, and had increased persistence through STEM courses than students who did not participate in STEM small-group learning.

The box below summarizes three individual studies examining the effects of cooperative learning groups.

What are approaches that can help make group work effective?

Preparation

Articulate your goals for the group work, including both the academic objectives you want the students to achieve and the social skills you want them to develop.

Determine the group conformation that will help meet your goals.

• In informal group learning, groups often form ad hoc from near neighbors in a class.
• In formal group learning, it is helpful for the instructor to form groups that are heterogeneous with regard to particular skills or abilities relevant to group tasks. For example, groups may be heterogeneous with regard to academic skill in the discipline or with regard to other skills related to the group task (e.g., design capabilities, programming skills, writing skills, organizational skills) (Johnson et al, 2006).
• Groups from 2-6 are generally recommended, with groups that consist of three members exhibiting the best performance in some problem-solving tasks (Johnson et al., 2006; Heller and Hollabaugh, 1992).
• To avoid common problems in group work, such as dominance by a single student or conflict avoidance, it can be useful to assign roles to group members (e.g., manager, skeptic, educator, conciliator) and to rotate them on a regular basis (Heller and Hollabaugh, 1992). Assigning these roles is not necessary in well-functioning groups, but can be useful for students who are unfamiliar with or unskilled at group work.

Choose an assessment method that will promote positive group interdependence as well as individual accountability.

• In team-based learning, two approaches promote positive interdependence and individual accountability. First, students take an individual readiness assessment test, and then immediately take the same test again as a group. Their grade is a composite of the two scores. Second, students complete a group project together, and receive a group score on the project. They also, however, distribute points among their group partners, allowing student assessment of members’ contributions to contribute to the final score.
• Heller and Hollabaugh (1992) describe an approach in which they incorporated group problem-solving into a class. Students regularly solved problems in small groups, turning in a single solution. In addition, tests were structured such that 25% of the points derived from a group problem, where only those individuals who attended the group problem-solving sessions could participate in the group test problem.  This approach can help prevent the “free rider” problem that can plague group work.
• The University of New South Wales describes a variety of ways to assess group work , ranging from shared group grades, to grades that are averages of individual grades, to strictly individual grades, to a combination of these. They also suggest ways to assess not only the product of the group work but also the process.  Again, having a portion of a grade that derives from individual contribution helps combat the free rider problem.

Helping groups get started

Explain the group’s task, including your goals for their academic achievement and social interaction.

Explain how the task involves both positive interdependence and individual accountability, and how you will be assessing each.

Assign group roles or give groups prompts to help them articulate effective ways for interaction. The University of New South Wales provides a valuable set of tools to help groups establish good practices when first meeting. The site also provides some exercises for building group dynamics; these may be particularly valuable for groups that will be working on larger projects.

Monitoring group work

Regularly observe group interactions and progress , either by circulating during group work, collecting in-process documents, or both. When you observe problems, intervene to help students move forward on the task and work together effectively. The University of New South Wales provides handouts that instructors can use to promote effective group interactions, such as a handout to help students listen reflectively or give constructive feedback , or to help groups identify particular problems that they may be encountering.

Assessing and reflecting

In addition to providing feedback on group and individual performance (link to preparation section above), it is also useful to provide a structure for groups to reflect on what worked well in their group and what could be improved. Graham Gibbs (1994) suggests using the checklists shown below.

The University of New South Wales provides other reflective activities that may help students identify effective group practices and avoid ineffective practices in future cooperative learning experiences.

Bransford, J.D., Brown, A.L., and Cocking, R.R. (Eds.) (1999). How people learn: Brain, mind, experience, and school . Washington, D.C.: National Academy Press.

Bruffee, K. A. (1993). Collaborative learning: Higher education, interdependence, and the authority of knowledge. Baltimore, MD: Johns Hopkins University Press.

Cabrera, A. F., Crissman, J. L., Bernal, E. M., Nora, A., Terenzini, P. T., & Pascarella, E. T. (2002). Collaborative learning: Its impact on college students’ development and diversity. Journal of College Student Development, 43 (1), 20-34.

Davidson, N., & Major, C. H. (2014). Boundary crossing: Cooperative learning, collaborative learning, and problem-based learning. Journal on Excellence in College Teaching, 25 (3&4), 7-55.

Dees, R. L. (1991). The role of cooperative leaning in increasing problem-solving ability in a college remedial course. Journal for Research in Mathematics Education, 22 (5), 409-21.

Gokhale, A. A. (1995). Collaborative Learning enhances critical thinking. Journal of Technology Education, 7 (1).

Heller, P., and Hollabaugh, M. (1992) Teaching problem solving through cooperative grouping. Part 2: Designing problems and structuring groups. American Journal of Physics 60, 637-644.

Johnson, D.W., Johnson, R.T., and Smith, K.A. (2006). Active learning: Cooperation in the university classroom (3 rd edition). Edina, MN: Interaction.

Johnson, D.W., Johnson, R.T., and Holubec, E.J. (2008). Cooperation in the classroom (8 th edition). Edina, MN: Interaction.

Johnson, D.W., Johnson, R.T., and Smith, K.A. (2014). Cooperative learning: Improving university instruction by basing practice on validated theory. Journl on Excellence in College Teaching 25, 85-118.

Jones, D. J., & Brickner, D. (1996). Implementation of cooperative learning in a large-enrollment basic mechanics course. American Society for Engineering Education Annual Conference Proceedings.

Kuh, G.D., Kinzie, J., Buckley, J., Bridges, B., and Hayek, J.C. (2007). Piecing together the student success puzzle: Research, propositions, and recommendations (ASHE Higher Education Report, No. 32). San Francisco, CA: Jossey-Bass.

Love, A. G., Dietrich, A., Fitzgerald, J., & Gordon, D. (2014). Integrating collaborative learning inside and outside the classroom. Journal on Excellence in College Teaching, 25 (3&4), 177-196.

Smith, M. E., Hinckley, C. C., & Volk, G. L. (1991). Cooperative learning in the undergraduate laboratory. Journal of Chemical Education 68 (5), 413-415.

Springer, L., Stanne, M. E., & Donovan, S. S. (1999). Effects of small-group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis. Review of Educational Research, 96 (1), 21-51.

Uribe, D., Klein, J. D., & Sullivan, H. (2003). The effect of computer-mediated collaborative learning on solving ill-defined problems. Educational Technology Research and Development, 51 (1), 5-19.

Vygotsky, L. S. (1962). Thought and Language. Cambridge, MA: MIT Press.

Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.

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Collaborative Learning

Collaborative learning can occur peer-to-peer or in larger groups. Peer learning, or peer instruction, is a type of collaborative learning that involves students working in pairs or small groups to discuss concepts or find solutions to problems. Similar to the idea that two or three heads are better than one, educational researchers have found that through peer instruction, students teach each other by addressing misunderstandings and clarifying misconceptions.

Why use collaborative learning?

Research shows that educational experiences that are active, social, contextual, engaging, and student-owned lead to deeper learning. The benefits of collaborative learning include:

• Development of higher-level thinking, oral communication, self-management, and leadership skills.
• Promotion of student-faculty interaction.
• Increase in student retention, self-esteem, and responsibility.
• Exposure to and an increase in understanding of diverse perspectives.
• Preparation for real life social and employment situations.

Considerations for using collaborative learning

• Introduce group or peer work early in the semester to set clear student expectations.
• Establish ground rules   for participation and contributions.
• Plan for each stage of group work.
• Carefully explain to your students how groups or peer discussion will operate and how students will be graded.
• Help students develop the skills they need to succeed, such as using team-building exercises or introducing self-reflection techniques.
• Consider using written contracts.
• Incorporate   self -assessment  and   peer  assessment  for group members to evaluate their own and others' contributions.

Getting started with collaborative learning

Shorter in-class collaborative learning activities generally involve a three-step process. This process can be as short as five minutes, but can be longer, depending on the task at hand.

• Introduce the task. This can be as simple as instructing students to turn to their neighbor to discuss or debate a topic.
• Provide students with enough time to engage with the task. Walk around and address any questions as needed.
• Debrief. Call on a few students to share a summary of their conclusions. Address any misconceptions or clarify any confusing points. Open the floor for questions.

For larger group work projects, here are some strategies to help ensure productive group dynamics:

• Provide opportunities for students to develop rapport and group cohesion through   icebreakers , team-building, and reflection exercises.
• Give students time to create a group work plan allowing them to plan for deadlines and divide up their responsibilities.
• Have students   establish ground rules . Students can create a contract for each member to sign. This contract can include agreed-upon penalties for those who fail to fulfill obligations.
• Assign roles to members of each group and change the roles periodically. For example, one student can be the coordinator, another the note-taker, another the summarizer, and another the planner of next steps.
• Allow students to rate each other’s quality and quantity of contributions. Use these evaluations when giving individual grades, but do not let it weigh heavily on a student's final grade. Communicate clearly how peer assessment will influence grades.
• Check in with groups intermittently but encourage students to handle their own issues before coming to you for assistance.

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10 Strategies to Build on Student Collaboration in the Classroom

Collaborative learning – the practice of breaking students into small groups to answer questions, work on projects and learn from one another – has become one of the strongest core philosophies operating in classrooms today. The concept is not new; much of the early research on collaborative learning (also called cooperative learning) was done in the 1980s and 1990s when most classrooms favored the traditional teacher lectures and individual student work. But with the growth of technology and the increasing value society places on the ability to work in teams, collaborative learning has become more common. Here are 10 strategies for encouraging the success of collaborative learning:

1. Deliberately select which students will work together

Left to their own devices, students will sort themselves into groups of friends who share common bonds. However, when a teacher creates the groupings, he or she can match students by strengths and weaknesses, deliberately mixing ability, diversity and social capability.

2. Size the groups for maximum effectiveness

If a group is too small, ideas and discussion may not be diverse or energetic enough; if too large, some students won’t get involved. Optimum group size tends to be four to five.

3. Teach your students how to listen to one another

Among young learners, active listening isn’t a natural skill. Taking time to discuss and practice listening skills with your students – teaching them to make eye contact, avoid interruption and repeat important points – has both short and long term benefits.

4. Set the rules of language and collaboration

There will always be one or two students in each group who will be more likely to take the lead – or take over. Take the time to teach students how to clarify issues, how to paraphrase, how to disagree constructively and how to build on what others have contributed.

5. Make goals and expectations clear

Specific goals and expectations are important. If students are not clear on the goals they are expected to meet, group work has the potential to trail off into socialization or apathy.

6. Assign roles to the members of each group

With roles delineated, students are able to better understand what is expected of them. With roles like leader (directs the group’s actions for the day), recorder (takes notes and does all writing), encourager (enables discussion and gives positive feedback) and checker (checks the work and hands it in), its clear how each student needs to fulfill his or her responsibilities.

7. Use real-world problems, not imaginary ones

With practical, real-world assignments, students find information through research and forming real opinions. If you find a scenario that they feel involved in – an environmental issue, a recent Supreme Court case, a complicated social issue – they will take more ownership of the project. Even better, select a problem from the students’ own community and challenge them to solve it.

8. Consider giving each group a different task

Delegating tasks gives each group a sense of importance and emphasizes the fact that large problems are solved by people working together. By solving different pieces of an issue, your student groups will have a more personalized learning experience and will better refrain from ill-spirited competition or “borrowing” each other’s work.

9. Play a game to get students warmed up

This is particularly helpful for younger students, who may not be sure of their roles in the group or the classroom. Cooperative games require children to use the same skills that they do in collaborative schoolwork, and they can see results quickly. For example, Teach Hub offers  cooperative classroom games  that are appropriate for grades 1-3, grades 4-6 and grades 7-8.

10. Evaluate each group on its own merit

If you judge groups in relation to each other, students will feel like their success or failure is not entirely in their own hands. Try a system where you can give grades per how well each group met its goals, and/or how each student performed the duties of their assigned role. You can also reward by category, as in best discussions, best research or most original solution.

The Changing Trends of Education

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Home > Books > Active Learning - Beyond the Future

Cooperative Learning: The Foundation for Active Learning

Submitted: 24 May 2018 Reviewed: 22 August 2018 Published: 05 November 2018

DOI: 10.5772/intechopen.81086

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Active Learning - Beyond the Future

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The role of instructors is evolving from the presenter of information to the designer of active learning processes, environments, and experiences that maximize student engagement. The more active a lesson, the more students tend to engage intellectually and emotionally in the learning activities. Cooperative learning is the foundation on which many of the active learning procedures are based. Cooperative learning is the instructional use of small groups so that students work together to maximize their own and each other’s learning. Most of the active learning procedures, such as problem-based learning, team-learning, collaborative learning, and PALS, require that students work cooperatively in small groups to achieve joint learning goals. Cooperative learning is based on two theories: Structure-Process-Outcome theory and Social Interdependence theory. Four types of cooperative learning have been derived: formal cooperative learning, informal cooperative learning, cooperative base groups, and constructive controversy. There is considerable research confirming the effectiveness of cooperative learning. To be cooperative, however, five basic elements must be structured into the situation: positive interdependence, individual accountability, promotive interaction, social skills, and group processing.

• active learning
• cooperative learning
• collaborative learning
• student engagement
• student involvement

Author Information

David w. johnson *.

• University of Minnesota, Minneapolis, Minnesota, USA

Roger T. Johnson

*Address all correspondence to: [email protected]

1. Introduction

The role of instructor is evolving from the presenter of information to the designer of learning experiences that maximize student active engagement [ 1 ]. The influences behind this change include (a) the growing awareness that learning experiences should be active in ways that maximize student engagement and (b) the evidence that careful design of instructional experiences makes students’ acquisition of knowledge and competencies more efficient, effective, and appealing. One of the most useful methods of ensuring that students are actively engaged in learning experiences is cooperative learning. In addition, it is the foundation on which many of the active learning and student engagement procedures are built. First, we will explain the relationship between cooperative learning and active learning and student engagement. Second, we will explain the nature of cooperative learning.

1.1 Active learning and student engagement

The first requirement for designing a learning experience is to ensure students are active rather than passive. Passive to active is a continuum, as no learning experience is entirely passive (even sleep has active components) or entirely active. The question is the degree to which a learning experience is structured to make students passive or active. Near the passive end of the continuum, learning is typically listening to the instructor or individually reading information with or without taking notes and highlighting key passages. Characteristics of passive learning are that the student is silent, isolated (working separately from others), and under the direction of others. Near the active end of the continuum, learning occurs when students construct, discover, and transform their own knowledge. Active learning requires students to engage meaningfully cognitively and emotionally with other students, the task assigned, and the materials or resources used to complete the task. Characteristics of active learning are that students are talking with others (i.e., engaged in dialogs), interacting with others (i.e., member of a pair, triad, or group of four), generating new ideas and cognitive structures (discovering their own insights and meaning from the learning activities), and determining their own direction (i.e., coordinating with groupmates as to the direction and speed of the work). Active learning typically requires students working in pairs or small group to conceptualize, analyze, synthesize, and evaluate during discussions the information, procedures, strategies, and conceptual frameworks being learned.

Active learning subsumes students engaging intellectually and emotionally in the learning activities. The continuum of student engagement (both intellectually and emotionally) has disengagement at one end and engagement at the other. Student disengagement is defined as off-task behaviors, negative emotions, and the absence of focus, interest, effort, curiosity, persistence, the use of cognitive strategies, and other indicators of learning. Student engagement is students’ exerting effort to complete the learning task, reflecting interest in completing the task successfully, focus on the task, curiosity about the task and its content, persistence, and the use of cognitive strategies. Engagement may be differentiated into three types: behavioral engagement (attending class, doing homework), cognitive engagement (effort to understand information and master complex skills), and emotional engagement (positive reactions to classmates, academic task and materials, teachers, and so forth).

Well-designed lessons require students to be active and engaged. These two aspects of lessons overlap, so that often if you get one, you get the other. The easiest way to ensure that students are active and engaged in learning may be to use cooperative learning. In addition, many of the forms of active learning being implemented in schools and universities are based on the foundation of cooperative learning. Some of the most common are discussed below. This is by no means an exhaustive list.

1.2 Problem-based learning

Problem-based learning may be defined as assigning students to small groups and giving the groups a problem to understand and solve, with the goal of having students learn relevant information and procedures [ 2 , 3 , 4 ]. While students work in small groups the instructor facilitates and guides their work. Problem-based learning requires students to work in small groups to ensure that the relevant information and procedures are discovered and mastered by all members of the group, thus making cooperative learning the foundation on which problem-based learning is built. When this connection between cooperative learning and problem-based learning is explicit, it is known as Cooperative Problem-Based Learning or Problem-Based Cooperative Learning.

1.3 Team-based learning

In team-based learning instructors assign students with diverse skill sets and backgrounds to permanent groups of five to seven members to enhance the quality of student learning [ 5 ]. Students are individually accountable for homework assignments and for contributing to team efforts in class. Significant credit is given for inclass team activities and application exercises aimed at increasing both academic learning and team development. The activities are structured to give students frequent and timely feedback on their efforts. Since students work in teams to increase their own and teammates’ learning, team-based learning is in effect another form of cooperative learning.

1.4 Collaborative learning

In the 1970s, Sir James Britton and others in England [ 6 ] created an active learning procedure known as Collaborative Learning based on the theorizing of Vygotsky [ 7 ]. Britton believed that a student’s learning is derived from the community of learners made up of other students. Britton was opposed to providing specific definitions of the teacher’s and students’ roles, which he considered to be training (the application of explanations, instructions, or recipes for action). Instead, he recommended placing students in groups and letting them generate their own culture, community, and procedures for learning, which he considered to be natural learning (learning by making intuitive responses to whatever one’s efforts produce). Britton believed the source of learning is dialogs and interactions with other students (and sometimes the teacher resulting from the positive interdependence among students’ learning goals. The heart of collaborative learning, therefore, is the cooperative foundation of students working together to maximize their own and each other’s learning.

1.5 Peer-assisted learning

Peer-assisted learning (PALS) involves classmates of equal status actively helping each other to acquire knowledge and skills [ 8 ]. It subsumes Reciprocal Peer Tutoring , which places same-age students into pairs of comparable ability and gives them the responsibility is to keep each other engaged academically [ 9 ]. Peer-assisted learning is based on cooperation, as assistance and encouragement tends not to take place in competitive interaction.

1.6 Conclusion

Almost all forms of active learning assume that students will work cooperatively in small groups. Cooperative learning is, therefore, the foundation on which most active learning strategies are built.

2. Cooperative learning

Most methods of active learning require the use of cooperative learning as an essential part of their method. Cooperative learning is the foundation on which most active learning methods are built. Cooperation is working together to accomplish shared goals [ 10 , 11 ]. When cooperating, individuals work to achieve outcomes that benefit themselves and all other group members. Cooperative learning exists when small groups of students work to enhance their own and their groupmates’ learning [ 1 ]. It is often compared to competitive learning (students working to accomplish academic goals that only one or a few participants can attain) and individualistic learning (each student working by him- or herself to complete assignments). Student efforts are evaluated on a criteria-referenced basis in cooperative and individualistic learning, while in competitive learning students are evaluated on a norm-referenced basis. Any learning task in any subject area with any curriculum may be structured cooperatively, but there are limitations on when and where competitive and individualistic learning may be used appropriately.

Cooperative learning is largely based on two theories: Structure-Process-Outcome theory and Social Interdependence theory.

2.1 Structure-process-outcome theory

Watson and Johnson [ 12 ] theorized that the way a situation is structured determines the process individuals engage in to complete the task, which determines the outcomes of the situation. The processes of interaction, in other words, determine outcomes, not the structure of the situation directly. This theory focuses instructors on structuring learning goals to create desired processes of interaction among students and between the students and the instructor. Once the desired processes of interaction occur, outcomes will tend to automatically result [ 10 , 13 ].

2.2 Social interdependence theory

A second theory underlying cooperative learning is social interdependence theory [ 10 ]. In the early 1900s Kurt Koffka, proposed that groups were dynamic wholes in which the interdependence among members could vary. In the 1930s Kurt Lewin stated that the interdependence among members created by common goals is the essence of a group. The goal interdependence unites members into a “dynamic whole,” so that changes in the state of a member or subgroup modify the state of other members or subgroups. In addition, motivation to accomplish the common goals results from an intrinsic state of tension within each group member. For interdependence to exist, there must be more than one person or entity involved, and the persons or entities must have dynamic impact on each other. In the late 1940s, Morton Deutsch, one of Lewin’s graduate students, extended Lewin’s reasoning about interdependence and formulated a theory of cooperation and competition [ 14 , 15 ]. The authors of this chapter, David (who was a doctoral student of Deutsch) and Roger Johnson, extended and expanded Deutsch’s theory [ 10 , 13 , 16 , 17 , 18 , 19 ]. It should be noted that the authors of this chapter (David and Roger Johnson) coined the term social interdependence theory to describe their expanded version of the theory of cooperative, competitive, and individualistic efforts. Deutsch believed that social interdependence theory included more than cooperative, competitive, and individualistic processes, so he reserved the term for a future yet undefined theory.

In his theory of cooperation and competition, Deutsch posits that cooperation is created by positive goal interdependence , which exists when group members perceive that they can reach their goals if and only if the other group members also reach their goals [ 14 , 15 ]. Competition is created by negative goal interdependence , which exists when group members perceive that they can obtain their goals if and only if the other group members fail to obtain their goals. Individualistic efforts are creative by no goal interdependence , which exists when individuals perceive that reaching their goal is independent from other individuals attaining their goals.

Positive goal interdependence tends to result in promotive interaction, negative goal interdependence tends to result in oppositional interaction, and no goal interdependence results in an absence of interaction. The relationship between the cooperation and competition and the interaction pattern each elicits tends to be bidirectional. Each may cause the other.

3. Types of cooperative learning

Four types of cooperative learning have been derived from cooperation and competition theory [ 1 ]. Formal cooperative learning may be implemented to teach specific content, informal cooperative learning may be implemented to ensure active cognitive processing of information during direct teaching, cooperative base groups may be implemented to provide long-term support and assistance, and constructive controversy may be implemented to create academic, intellectual conflicts to enhance achievement and creative problem solving.

3.1 Formal cooperative learning

Makes a series of decisions about how to structure the learning groups (what size groups, how students are assigned to groups, what roles to assign, how to arrange materials, and how to arrange the room). The instructor also specifies the objectives for the lesson (one academic and one social skills).

Teaches the academic content students are expected to master and apply. The instructor then explains the (a) academic task to be completed, (b) the criteria used to determine the degree of students’ success, (c) positive interdependence, (d) individual accountability, and (e) expected student behaviors.

Monitors the functioning of the learning groups and intervenes to (a) teach needed social skills and (b) provide needed academic assistance.

Uses the preset criteria for excellent to evaluate student performance. The instructor then ensures that groups process how effectively members worked together.

3.2 Informal cooperative learning

Ref. [ 1 ] define informal cooperative learning as students working together to achieve a joint learning goal in temporary, ad-hoc groups that last from a few minutes to one class period. During direct teaching, such as a lecture, demonstration, or video, the teacher structures informal cooperative learning groups. Students engage in three-to-five minute focused discussions before and after the direct teaching and three-to-five minute turn-to-your-partner discussions interspersed throughout the direct teaching. Informal cooperative learning can create a mood conducive to learning, focus student attention on the material to be learned, set expectations as to what will be covered in a class session, ensure that students cognitively process the material being taught, and provide closure to an instructional session. During direct teaching the instructor needs to ensure that students do the intellectual work of explaining what they are learning, conceptually organizing the material, summarizing it, and integrating it into existing conceptual frameworks.

3.3 Cooperative base groups

Cooperative base groups are long-term, heterogeneous cooperative learning groups with stable membership in which students provide one another with support, encouragement, and assistance to make academic progress by attending class, completing assignments, learning assigned material) [ 1 ]. The use of base groups tends to improve attendance, personalizes the work required and the school experience, and improves the quality and quantity of learning. Base groups have permanent membership and provide the long-term caring peer relationships necessary to help students developed in healthy ways cognitively and socially as well as influence members to exert effort in striving to achieve. Base groups formally meet to provide help and assistance to each other, verify that each member is completing assignments and progressing satisfactory through the academic program, and discuss the academic progress of each member. It is especially important to have base groups in large classes or schools and when the subject matter is complex and difficult.

3.4 Constructive controversy

Johnson and Johnson [ 20 ] define constructive controversy as one person’s ideas, information, conclusions, theories, and opinions being incompatible with those of another, and the two seek to reach an agreement that reflects their best reasoned judgment. Constructive controversy involves the discussion of the advantages and disadvantages of proposed actions aimed at synthesizing novel and creative solutions. It also involves dissent and argumentation [ 20 ]. Dissent may be defined as differing in opinion or conclusion, especially from the majority. Argumentation is a social process in which two or more individuals engage in a dialog where arguments are constructed, presented, and critiqued. The theory underlying constructive controversy states that the way conflict is structured within situations determines how individuals interact with each other, which in turn determines the quality of the outcomes [ 12 , 19 ]. Intellectual conflict maybe structured along a continuum, with concurrence seeking at one end and constructive controversy at the other. The process of concurrence seeking involves avoiding open disagreement to conform to the majority opinion and reach a public consensus. The process of controversy involves utilizing the conflict among positions to achieve a synthesis or a creative integration of the various positions. The outcomes generated by the process of controversy tend to include higher quality decision making and achievement, greater creativity, higher cognitive and moral reasoning, greater motivation to improve understanding, more positive relationships and social support, and more democratic values. The conditions mediating the effects of the controversy process include a cooperative context, heterogeneity among members, skilled disagreement, and rational argument.

When used in combination, cooperative formal, informal, base groups, and constructive controversy provide an overall structure for school learning.

4. Outcomes of cooperative learning

Cooperative efforts result in numerous outcomes that may be subsumed into three broad categories: effort to achieve, positive interpersonal relationships, and psychological adjustment. The social interdependence research has considerable generalizability as (a) research participants have varied as to economic class, age, gender, and culture, (b) research tasks and measures of the dependent variables have varied widely, and (c) many different researchers with markedly different orientations working in different settings and in different decades have conducted the studies. We now have over 1200 studies on cooperative, competitive, and individualistic efforts from which we can derive effect sizes. This is far more evidence than exists for most other aspects of human interaction.

Cooperating to achieve a common goal results in higher achievement and greater productivity compared to competitive or individualistic efforts [ 10 , 13 , 19 ]. There is so much research that confirms this finding that it stands as one of the strongest principles of social and organizational psychology. Cooperation also resulted in more frequent generation of new ideas and solutions (i.e., process gain ), more higher-level reasoning, and greater transfer of what is learned (i.e., group to individual transfer ) than competitive or individualistic efforts. The superiority of cooperative efforts (as compared to competitive and individualistic efforts) increased as the task became more conceptual, the more higher-level reasoning and critical thinking was required, the more desired was problem solving, the more creativity was desired, the more long-term retention was required, and the greater the need for application of what was learned.

More positive and committed relationships develop in cooperative than in competitive or individualistic situations [ 10 , 13 , 19 ]. This is true when individuals are homogeneous. It is also true when individuals differ in ethnic membership, intellectual ability, handicapping conditions, culture, social class, and gender. Cooperative learning tends to be essential for classes with diverse students from different ethnic groups and handicapping conditions [ 10 ]. The more positive relationships that result from cooperative learning tends to reduce absenteeism and turnover, increase member commitment to academic goals, increase feelings of personal responsibility to the group and school, increase willingness to take on difficult tasks, increase motivation to achieve and persistence in working toward goal achievement, increase morale, increase readiness to endure pain and frustration on behalf of the group, increase readiness to defend the group against external criticism or attack, increase readiness to listen to and be influenced by classmates, increase commitment to each other’s academic success, and increases academic productivity. Cooperating on a task, compared to competing or working individualistically, also results in more task-oriented and personal social support.

Working cooperatively with peers, and valuing cooperation, results in greater psychological health and higher self-esteem than does competing with peers or working independently [ 10 , 13 ]. Personal ego-strength, self-confidence, independence, and autonomy are all promoted by being involved in cooperative efforts with caring people, who are committed to each other’s success and well-being. When individuals work together to complete assignments, through their interaction they master needed social skills and competencies, promote each other’s success (gaining self-worth), and form both academic and personal relationships (creating the basis for healthy social development).

When schools are dominated by cooperative efforts, students’ psychological adjustment and health tend to increase. The more students cooperate with each other, the higher tends to be their self-esteem, productivity, acceptance and support of classmates, and autonomy and independence. Working cooperatively with peers is not a luxury. It is an absolute necessity for students’ healthy development and ability to function independently.

5. Basic elements of cooperative learning lessons

Five basic elements for designing cooperative learning lessons have been derived from Social Interdependence theory and Structure-Process-Outcome theory and the research on social interdependence. The five basic elements that are required in any cooperative learning lesson are: positive interdependence, individual accountability, promotive interaction, social skills, and group processing.

Positive interdependence is the heart of cooperative efforts. Students must perceive that (a) they are linked with groupmates in a way so that they cannot succeed unless their groupmates do (and vice versa) and (b) groupmates’ work benefits them and their work benefits their groupmates [ 10 ]. Positive interdependence among students must be structured into the lesson for it to be cooperative. While every lesson must contain positive goal interdependence, positive interdependence may also be structured through mutual rewards, distributed resources, complementary roles, a mutual identity, and other methods of structuring positive interdependence.

Each group member is individually accountable to contribute his or her fair share of the group’s work. Individual accountability exists when the performance of each individual student is assessed and the results are given back as feedback to the group and the individual [ 10 ]. Individual accountability includes completing one’s share of the work and facilitating the work of other group members. A purpose of cooperative learning is to make each group member a stronger individual. There is considerable group-to-individual transfer. Students learn together so that they can subsequently perform higher as individuals. Individual accountability may be structured by (a) observing students as they work together and documenting the contributions of each member, (b) having each student explain what they have learned to a classmate, or (c) giving an individual test to each student.

Students promote each other’s success by helping, assisting, praising, encouraging, and supporting each other’s efforts to learn [ 10 ]. Doing so results in such cognitive processes as discussing the nature of the concepts being learned, orally explaining to others how to solve problems, teaching one’s knowledge to classmates, challenging each other’s reasoning and conclusions, and connecting present with past learning. Promotive interaction also includes interpersonal processes such as supporting and encouraging efforts to learn, jointly celebrating the group’s success, and modeling appropriate use of social skills.

Contributing to the success of a cooperative effort requires interpersonal and small group skills. In cooperative learning groups, students are expected to use social skills appropriately [ 10 ]. Leadership, trust-building, communication, decision-making, and conflict-management skills have to be taught just as purposefully and precisely as academic skills. How to teach students social skills is the focus of Johnson [ 21 ] and Johnson and Johnson [ 20 ].

Finally, students need to engage in group processing. Group processing may be defined as the examination of the effectiveness of the process members use to maximize their own and each other’s learning, so that ways to improve the process may be identified [ 10 ]. Group members need to (a) describe what member actions are helpful and unhelpful in ensuring that all group members (a) achieve and maintain effective working relationships, (b) decide what behaviors to continue or change and (c) celebrate group members’ hard work and success [ 22 ].

These five basic elements are the educator’s best resource. They enable instructors to (a) structure for cooperative learning any lesson in any subject area with any set of curriculum materials, (b) fine-tune and adapt cooperative learning to their specific students, needs, and circumstances, and (c) intervene in malfunctioning groups to improve their effectiveness. These five essential elements allow instructors to structure any lesson for student activeness and engagement. It is only when these five aspects are carefully structured in a lesson that the lesson becomes truly cooperative and students become active and engaged.

6. Return to active learning

Characteristics of active learning are that students engage in dialogs, interact with classmates in small groups, generate new ideas and cognitive structures within the groups, and coordinate with groupmates as to the direction and speed of the work. Active learning typically requires a learning partner or a small group in which the information being learned is analyzed, synthesizes, evaluated during discussions. In a discussion, students construct new cognitive structures or access their existing ones to subsume the new information and experiences.

It is clear from the research that having students compete with each other will result in students opposing each other’s learning, thereby reducing their motivation and achievement. It is also clear that having students work alone without interacting with classmates will have students being indifferent to each other’s learning, also reducing their motivation and learning. What does increase motivation and achievement is cooperative learning. In cooperative learning lessons, students are assigned to small groups (usually two, three, or four members) and given an assignment to complete (such as solving a problem or mastering a set of procedures). Working cooperatively with classmates to solve a problem is far more effective than competing with classmates or working by oneself to solve the problem. It is the cooperative structure that promotes students to engage cognitively and emotionally with other students, the task assigned, and the materials or resources used to complete the task. Doing so allows students to construct, discover, and transform their own knowledge.

Students are engaged in a learning task when they exert effort to complete the task successfully, focus on the task, are curious about the task and its content, persist in completing the task, and use higher-level cognitive strategies in completing the task. Students engaged in cooperative learning activities tend to engage in more on-task behavior (and therefore are more engaged, behaviorally, cognitively, and emotionally) than do students participating in competitive or individualistic learning activities [ 10 ].

Cooperative learning is the instructional use of small groups so that students work together to maximize their own and each other’s learning. Cooperative learning is based on two theories: Structure-Process-Outcome theory and Social Interdependence theory. There are four types of cooperative learning: formal cooperative learning, informal cooperative learning, cooperative base groups, and constructive controversy. To be cooperative, five basic elements need to be structured into the learning situation: positive interdependence, individual accountability, promotive interaction, social skills, and group processing. Cooperative learning, compared with competitive or individualistic learning, tends to result in students exerting more effort to learn, building more positive relationships with classmates, and improving their psychological health.

Cooperative learning is one of the foremost active learning procedures. It is also the foundation on which many of the active learning procedures are based.

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Cooperative Education: Challenges, Problems, Potential

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• Vera A. Drobisheva   ORCID: orcid.org/0000-0001-7895-2536 13 ,
• Oksana A. Konnova   ORCID: orcid.org/0000-0002-3230-5277 13 ,
• Elena V. Suvorova   ORCID: orcid.org/0000-0002-7151-272X 13 &
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The purpose of this research is to reveal the nature, directions and tasks of cooperative education, to consider the problems, potential opportunities and its key elements in different age groups and different national conditions. It is particularly important to identify the contribution of cooperative higher education to solving the most important socio-economic problems of our time. Cooperatives are credited with the ability to solve many problems, and their future is linked to solving market problems, or they are claimed to contribute to structural change. Another argument is that a pluralistic economy is sustainable in times of recent crises, and that cooperatives play an educational role for those involved in the functioning of civil society. Finally, there is the idea that cooperatives can be transformative, so they are able to gradually transform the economy into something similar to a cooperative community. Cooperatives do not exist everywhere and are not considered necessarily on the periphery of society: they are valued in many countries. The International Cooperative Alliance (ICA) and the International Labour Organization (ILO) (ILO and ICA, Cooperatives and the sustainable development goals: a contribution to the post-2015 development debate, joint paper, ILO and ICA, 2014 ) track their various types and record their contributions. This research attempts to understand the prospects and possibilities of cooperative education and its ability to bring about broader social change.

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Effects of Online Cooperative Learning on Students’ Problem-Solving Ability and Learning Satisfaction

Yi-ping wang.

1 College of International Relations, Huaqiao University, Xiamen, China

2 School of Management, Harbin Institute of Technology (HIT), Harbin, China

Associated Data

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

As technology changes, it is becoming more common in education for students to acquire knowledge from sources other than just their teachers. In the face of a diverse student background, teachers have to make adjustments in their instruction so that students do not simply listen. Student-based educational philosophy aims to combine instructional methods with cooperative learning to allow students to change from passive learning to active knowledge construction, reinduce students’ learning motivation and passion, and enhance students’ self-learning effectiveness. Focusing on college students in Fujian Province as the research sample, 360 copies of a questionnaire were distributed for this study. After deducting invalid and incomplete ones, 298 copies remained, with a retrieval rate 83%. The research results showed significantly positive correlations between online cooperative learning and problem-solving ability, problem-solving ability and learning satisfaction, and online cooperative learning and learning satisfaction. According to the results, it is expected, in the digital era, to integrate information technology into the teaching environment and focus on learning objectives to create teaching software with a user-friendly interface, simple operation, learning process recording, and an interactive learning community in the teaching-learning process to develop the characteristics and effectiveness of digital teaching and learning.

Introduction

As times progress and technology improves, teachers are no longer the only channel for students acquiring knowledge. Students in this generation are stimulated by distinct and diverse cultures to show more active and flexible characters or responses than students before them, and are even brave enough to challenge existing values. Students in a traditional learning model with passive lectures will not concentrate in the classroom. Examinations have been a core part of education for a long time. It is the best time to practice cooperative learning. The curricula show that the ideas such as taking the initiative, engaging in the public, and seeking the common good are important. Engaging in the public and seeking the common good is a result of the characters of positive independence and face-to-face fostering of interactive and interpersonal skills mentioned in cooperative learning. In this respect, it can be stated that cooperative learning guides students to be well and develops various interactive abilities with ego, others, society, and nature. It also helps students in applying and practicing their knowledge, experiencing the meaning of life, being willing to devote to the sustainable development of society, nature, and culture, and seeking reciprocity of each other and common good. Information technologies are material tools that learners should actively and broadly apply to a the positive interaction channel between oneself and the environment to effectively engage the public with others and the environment ( Li et al., 2021 ).

In the face of diverse student background, teachers have to make adjustments in their instruction to stop students from simply listening. Educational philosophy should be student-based to promote each student’s thinking. In this case, cooperative learning allows students to change from passive learning into active knowledge construction, could reinduce students’ learning motivation and passion, and enhance students’ self-learning effectiveness. Most students are digital natives born after 1980, while most of their teachers are digital immigrants and even “digital refugees” escaping from technologies and being afraid of new knowledge. The overlap between such two generations is limited, meaning that their values and morality are distinct. Modern students are digital natives able to use mobile phones, televisions, computers, laptops, and tablets since childhood, and highly dependent on new technologies. Information-technology-integrated instruction with multimedia equipment and materials means teaching and learning is no longer restricted to dictation and paper-and-pencil ( Vaz et al., 2021 ); the class climate has changed to cooperative learning. The operation of cooperative learning is smoother through information technology, and a communication and interaction bridge can be built through information technology so that cooperative learning could cultivate students’ problem-solving ability to further promote learning satisfaction. As a result, the effects of online cooperative learning on students’ problem-solving ability and learning satisfaction are discussed in this study, expecting to integrate information technology into the teaching environment in the digital era, focus on learning objectives based on learning theory, have teaching software with a user-friendly interface, simple operation, learning process recording, and an interactive learning community in the teaching-learning process to develop the characteristics and effectiveness of digital teaching and learning.

Literature Review and Hypothesis

Constructivists regard gaining knowledge as a comprehensive and reflective thinking activity through students’ independent exploration and observation and highly praise learner-centered learning environments. Teachers’ roles of propagating the doctrine, imparting professional knowledge, and resolving doubts change into knowledge building facilitators. The superordinate-subordinate relationship of “Learning from Teacher” is changed into the equal relationship of “Learning with Teacher.” The learning perspective of constructivism facilitates the development of current learning technology ( Cortez et al., 2021 ).

Dozens of instructional strategies are developed for cooperative learning, and each grouping method presents the characteristics and applicable teaching situation. Teachers could flexibly apply the difference according to instructional objectives, student characteristics, and course attributes. Researchers, in the interview with collaborative teachers, also reveal not being restricted into a grouping method, but extracting the advantages of various methods, and making flexible adjustments in consideration of teachers’ personality traits and class attributes and characteristics ( Akdemir et al., 2020 ). Major cooperative learning strategies are classified into three types, including one suitable for leading sharing and discussion among students, another for assisting students in mastering learning content, and the last for leading teams for theme-based inquiry. Each type shows various strategies to cope with different teaching styles, or more than two strategies could be changed and applied depending on the demands ( Hafeez, 2021 ).

Li and Keller (2018) mentioned the significant effects of using web problem-based cooperative learning and on the problem-solving skills of the children. The results revealed the better performance of students compared to traditional problem-based learning. Del Gaudio et al. (2021) used online cooperative learning to discover the advantages and strengths, solve problems according to collaborative interaction, comprehend the roles, integrate the discussed ideas, clearly master the tasks, coordinate the allocation of team members’ reports, complete reports according to previous discussion results, discuss and modify successive measures together, inspect cooperation results, track back problem-solving processes, and reflect team organization and roles, problem-solving ability as to independently complete tasks with high-level thinking, and cooperative problem-solving ability as to create the value of synergy, solve problems and complete tasks together, and create good performance beyond the expectation ( Wu et al., 2019 , 2022 ). Ingrid (2019) explained that independent thinking and analysis ability allowed dealing with daily life and even life problems. Teachers applying information technology to cooperative learning to enrich students’ life experience, being good at asking questions, creating problem-solving teaching situations, applying technological tools to speculate and deduce problems, effectively solving problems with cooperative discussions, and enhancing adaptability to life could help students become problem-solving experts. For this reason, the following hypothesis is established in this study.

H1 : Online cooperative learning presents significantly positive correlations with problem-solving ability. H1-1 : Online cooperative learning shows significantly positive correlations with problem-solving ability. H1-2 : Online cooperative learning reveals remarkably negative correlations with problems-solving ability.

Oates and Ritók (2018) explained that learners being able to effectively enhance their problem-solving ability after going through the curriculum arranged by the school, course content of teachers, and effective promotion of knowledge acquisition in the learning process, with consistent expectation and anticipation, would appear satisfactory; on the contrary, dissatisfaction would be delivered. Metin-Orta and Demirtepe-Saygılı (2021) stated that education aimed to help individuals live their life; in real situations, an individual using critical thinking to solve complicated and messy dilemmas and problems was the core task of modern education. Teachers in the teaching process did not simply transmit knowledge, provide guidance for study, and dispel confusion, but had to help students associate old experience with new knowledge to further solve problems through tight cognition structure to form meaningful learning in order to effectively enhance learning satisfaction. Wu et al. (2021) regarded cooperative problem-solving ability as an individual with sufficient ability communicating and dialoging with more than two companions to share knowledge and skills, collaboratively and effectively participate in an activity, and develop teamwork ability to solve problems. Collaborative problem solving referred to several partners collaboratively completing a task where each partner had to positively participate ( Chiao and MacVaugh, 2021 ; Min et al., 2021 ), mutually coordinate, and pull together to solve problems in the task with teamwork so as to effectively enhance learning satisfaction. Accordingly, the following hypothesis is establishment in this study.

H2 : Problem-solving ability shows remarkably positive correlations with learning satisfaction. H2-1 : Problem-solving ability appears to have notably positive correlations with learning satisfaction. H2-2 : Problem-solving ability presents significantly negative correlations with learning satisfaction.

Wu et al. (2020) applied interactive APP to analyze learning satisfaction with idiom teaching; the students, regardless of gender and learning achievement, were satisfied with the use of interactive APP for idiom learning. The use of information-technology-integrated cooperative learning for the learning achievement of students in the experimental group did not outperform students in the control group, but the learning satisfaction was better than those in the control group. Kurilovas and Kubilinskiene (2020) mentioned that students in the experimental group with cooperative learning outperformed students with general cooperative learning on learning achievement and learning attitude and presented positive learning satisfaction. Haidar and Fang (2019) explained cooperative learning as teachers effectively applying information technology to smooth cooperative learning; for instance, dynamic information materials and real-time team performance could assist in students’ learning motivation, learning ambition, learning satisfaction, and learning effectiveness and create a quality learning environment with peer teamwork and teacher-student interaction. The following hypothesis is therefore established in this study.

H3 : online cooperative learning reveals notably positive correlations with learning satisfaction. H3-1 : Online cooperative learning shows remarkably positive correlations with learning satisfaction. H3-2 : Online cooperative learning reveals notably negative correlations with learning satisfaction.

Methodology

Operational definition, online cooperative learning.

Online cooperative learning, as the independent variable in this study, is measured with positive interdependence, promotive interaction, social skills, and group processing, according to the blended learning model proposed by Liao et al. (2019) .

• Positive interdependence: mutual dependence, mutual responsibility, mutual help, acceptance of assistance, and cheering up team members.
• Promotive interaction: mutual assistance, sharing information, and providing clear explanation in the team.
• Social skills: leadership and communication.
• Group processing: evaluating the cooperation effectiveness of each other.

Problem-Solving Ability

Problem-solving ability, as the dependent variable in this study, is measured with exploration and comprehension, planning and execution, and monitoring and reflection, according to the problem-solving ability model proposed by Lin et al. (2018) .

Learning Satisfaction

Learning satisfaction, as the dependent variable in this study, is measured with student aspects, teacher aspects, and school aspect, according to the blended learning model proposed by Travis and Bunde (2020) .

• Student aspects: including students’ interests, learning motivation, learning attitude, personality traits, gender, needs, experience, learning ability, learning effectiveness, and peer interpersonal relationship.
• Teacher aspects: covering teachers’ professional ability, traits, teaching methods, curriculum arrangement, teaching content, difficulty in material design, attitude towards students, and teacher-student interaction model.
• School aspects: containing school equipment, learning environment, environmental safety and health, teaching resources, and transportation.

Research Object and Analysis Method

College students in Fujian Province, as the research sample, were distributed 360 copies of a questionnaire for this study. After deducting invalid and incomplete ones, 298 copies were valid, with a retrieval rate 83%. After confirming the applicable online cooperative learning strategy, the actual teaching activity is practiced as planned. Four teachers practicing cooperative learning in the school were invited as the collaborative teachers to deliver the 10-week (total 50 sessions) teaching activity to 500 students in 10 classes of a university in Fujian Province. The questionnaire data collection is preceded after the end of the course.

Two-stage analysis in Structural Equation Modeling (SEM) is applied to analyze goodness-of-fit and test the model in this study. Confirmatory Factor Analysis (CFA) is first used, aiming to test the existence of independent variables in the model in order to delete dependent variables with bad effects on causal analysis. Path analysis is then preceded after the modification. Path analysis aims to estimate the relationship of model paths among variables. Without Confirmatory Factor Analysis to test independent variables, the use of path analysis might be affected by independent variables to result in bad goodness-of-fit or insignificant model paths. Goodness-of-fit test in Amos18.0 is utilized in this study. CMIN/DF of the measurement result being smaller than 5 is acceptable and being smaller than 3 is excellent; GFI, AGFI, NFI, IFI, TLI, and CFI are better higher than 0.9; and RMR, RMSEA, and SRMR are better when smaller and ideally smaller than 0.05.

Factor Analysis

The online cooperative learning scale in this study, with factor analysis, extracted four factors of “positive interdependence” (eigenvalue = 2.633, α  = 0.84), “promotive interaction” (eigenvalue = 1.875, α  = 0.86), “social skills” (eigenvalue = 2.236, α  = 0.81), and “group processing” (eigenvalue = 1.633, α  = 0.87). The cumulative covariance explained achieves 75.923%. The problem-solving ability scale, after factor analysis, extracted three factors of “exploration and comprehension” (eigenvalue = 3.251, α  = 0.86), “planning and execution” (eigenvalue = 2.407, α  = 0.88), and “monitoring and reflection” (eigenvalue = 2.716, α  = 0.83). The cumulative covariance explained reaches 77.493%. The learning satisfaction scale, with factor analysis, extracted three factors of “student aspects” (eigenvalue = 1.577, α  = 0.80), “teacher aspects” (eigenvalue = 2.281, α  = 0.85), and “school aspects” (eigenvalue = 2.388, α  = 0.90). The cumulative covariance explained achieves 80.762%.

Empirical Analysis Model of Structural Equation

Regarding the Confirmatory Factor Analysis (CFA) results, the convergent validity of the observation model could observe the reliability of individual observed variable, construct reliability (CR), and average variance extracted (AVE); the reliability of individual observed variable is better higher than 0.5. The factor loadings of observed items in this study are higher than the suggested value. The construct reliability is better higher than 0.6, while other researchers suggest higher than 0.5 being acceptable. The model calibration results reveal the construct reliability higher than 0.5. Average variance extracted is suggested higher than 0.5; the average variance extracted of the dimensions in this study is higher than 0.5, conforming to the suggested value.

In terms of the structural formula calibration results, χ 2 / df , RMSEA, GFI, AGFI, RMR, and NFI are suggested to be ≦5, ≦0.08, ≧0.9, ≧0.9, ≦0.05, and ≧0.9, respectively. This study shows χ 2 / df  = 3.142≦5, RMSEA = 0.032≦0.08, GFI = 0.967≧0.9, AGFI = 0.934≧0.9, RMR = 0.031≦0.05, and NFI = 0.918≧0.9, revealing good overall model fit. Under good overall model fit, the structural formula parameter calibration results are shown in Table 1 and Figure 1 . The research results present online cooperative learning → problem-solving ability 0.327 *** that H1 is supported, problem-solving ability → learning satisfaction 0.423 *** that H2 is supported, and online cooperative learning → learning satisfaction 0.386 *** that H3 is supported.

Structural equation modeling result.

Model path diagram. *** p  < 0.001.

The research results prove that, in the practice of online cooperative learning, information technology makes up for the insufficiency of cooperative learning, enriches courses, promotes students’ learning motivation, and drives learning effectiveness to form a positive cycle. Students’ learning motivation comes from the advancement of performance and the learning confidence comes from the ideal performance. Teachers use online cooperative learning to facilitate group discussion skills and the understanding of students. They also use Google Forms to conduct digitalized tests, and mind maps and tables to improve students’ problem-solving skills ( Simamora, 2017 ). In the teaching-learning process, instructional objectives are inspected to return the teaching profession. Teachers are good at asking questions to enhance students’ cooperation and encourage thinking. Especially in comprehension and analysis, the top-down relationship should be broken and the subjective consideration of teachers’ cognition, ideas, and interpretation as being better than students should be avoided so that it would not come out with teachers’ expected answers ( Phillips et al., 2014 ). Students’ answers could be typed with computers to respect the answers, enhance the confidence without losing students’ creativity, and present brainstorming; teachers ensure the focus and integration at the end. The application of online cooperative learning could reconstruct teachers’ teaching profession, and the experience and constant rolling correction could improve teaching skills to face changeable students and present the value of online cooperative learning. The intervention of information technology could change the resistance to the online cooperative learning process into assistance, helping it to become a powerful backup force of online cooperative learning, induce learning motivation, and promote problem-solving ability and learning satisfaction as the final instructional objectives.

Alves et al. (2019) explained collaborative problem solving as an individual or more than two companions with sufficient capability sharing knowledge and skills through communication and dialogue, collaboratively and effectively participating in activities, and developing teamwork to solve encountered problems. Collaborative problem solving referred to a task being collaboratively completed by several partners. Each partner had to positively participate, mutually coordinate, and help each other in the same situation to solve problems with teamwork so as to effectively enhance learning satisfaction. The intervention of information technology could make the best out of a bad situation in the online cooperative learning process to support online cooperative learning, induce learning motivation, and promote problem solving capability and learning satisfaction as the ultimate instructional objectives. The research result conforms to the points of view proposed by Munawar and Chaudhary (2019) and Haidar and Fang (2019) .

Teachers need full training to guide students with “stretching and jumping” opportunities in the “interactive relationship.” Meanwhile, teachers need full wisdom to help students move from conflict compromise to positive trust ( Ramdani et al., 2019 ). What is more, multiple evaluations outside the classroom, such as completion of team assignments, quiz performances, and sectional examination performance, help teams not to slack. Besides, each member is important that no-one is confident of the winning ( Hafeez, 2021 ). Students would search network data, discuss grounded arguments, focus on discussion through information technology, and save a lot of time for groupwork. Teachers, with statistics, would announce team performance with data at any time to induce competition and crisis awareness of teams. There might be conflict in a team, but a contest with multiple evaluations allows individuals to give up personal prejudice and unite to make effort for the team. It naturally reinforces the group process of cooperative learning ( Akdemir et al., 2020 ).

The research results show that the item of “ Teachers currently use the instructional method of online cooperative learning to make courses interesting and active ” receives the highest score in online cooperative learning strategies, revealing the acquisition of student identity. The item of “ I think the use of platform[s] for Internet communication media could help the communication and teamwork between team members and I in the cooperative learning course ” receives the highest score in problem solving capability, revealing the acquisition of student identity. The item of “ I think the application of online cooperative learning could enhance learning ability and confidence ” receives the highest score in learning satisfaction, revealing the acquisition of student identity.

The research results prove that students’ responses in class are a mirror reminding teachers of the need to adjust the instructional methods. In traditional didactic instruction, students’ academic achievement decides teachers’ success. In the use of online cooperative learning, students’ learning motivation awakes teachers’ passion. Teachers could continuously retain the original instructional methods; nevertheless, modern students are active and there are special students who are extroverts or introverts. These students may challenge teachers’ authority. Teachers can easily get tired if they do not adapt their instructional methods according to the diverse needs of students. The assistance of information technology in the practice allows seeking consensus from online resources in the team discussion. Under the situation with a well-grounded argument, students are convinced by each other to contribute to the successive discussions. The research result conforms to the points of view proposed by Weaver et al. (2019) and Ingrid (2019) . With online cooperative learning, teachers simply combine the original computer software with cooperative learning courses through the Internet, rather than re-learning brand new and strange computer software. Teachers who enjoy learning and self-growth could challenge themselves and activate teaching with advanced functions. However, it should be kept in mind that information technologies are only tools; using media can attract students’ attention in a short period, but having students internalize knowledge is the goal. Karakus Taysi (2019) mentioned the aims of education as helping individuals live their life. The development of individual critical thinking and problem-solving skills are the main aims of contemporary education. Teachers did not simply propagate the doctrine, impart professional knowledge, and resolve doubts in the teaching process, but had to help students link old experience with new knowledge, make tight cognitive structures for meaningful learning, and further solve problems to effectively promote learning satisfaction.

Online cooperation learning method is important for cultivating students’ independent thinking, interpersonal communication, competition awareness, and teamwork ( Cortez et al., 2021 ). Teachers and students are good at utilizing information technology to have students focus on discussion content and direction, instantaneously acquire the answers and feedback and correction, and improve team performance with data ( Mutua and Ong'ong'a, 2020 ). When making effort in the learning process, the learning result would not be lower than the expected performance and students would reflect this with their learning satisfaction.

Data Availability Statement

Ethics statement.

This study was reviewed and approved by the ethics committee of the Huaqiao University. Written informed consent was obtained from all participants for their participation in this study.

Author Contributions

Y-PW performed the initial analyses and wrote the manuscript. T-JW assisted in the data collection and data analysis. All authors revised and approved the submitted version of the manuscript.

This research was supported by the National Natural Science Foundation of China (71702059).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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3 Simple Strategies to Improve Students’ Problem-Solving Skills

These strategies are designed to make sure students have a good understanding of problems before attempting to solve them.

Research provides a striking revelation about problem solvers. The best problem solvers approach problems much differently than novices. For instance, one meta-study showed that when experts evaluate graphs , they tend to spend less time on tasks and answer choices and more time on evaluating the axes’ labels and the relationships of variables within the graphs. In other words, they spend more time up front making sense of the data before moving to addressing the task.

While slower in solving problems, experts use this additional up-front time to more efficiently and effectively solve the problem. In one study, researchers found that experts were much better at “information extraction” or pulling the information they needed to solve the problem later in the problem than novices. This was due to the fact that they started a problem-solving process by evaluating specific assumptions within problems, asking predictive questions, and then comparing and contrasting their predictions with results. For example, expert problem solvers look at the problem context and ask a number of questions:

• What do we know about the context of the problem?
• What assumptions are underlying the problem? What’s the story here?
• What qualitative and quantitative information is pertinent?
• What might the problem context be telling us? What questions arise from the information we are reading or reviewing?
• What are important trends and patterns?

As such, expert problem solvers don’t jump to the presented problem or rush to solutions. They invest the time necessary to make sense of the problem.

Now, think about your own students: Do they immediately jump to the question, or do they take time to understand the problem context? Do they identify the relevant variables, look for patterns, and then focus on the specific tasks?

If your students are struggling to develop the habit of sense-making in a problem- solving context, this is a perfect time to incorporate a few short and sharp strategies to support them.

3 Ways to Improve Student Problem-Solving

1. Slow reveal graphs: The brilliant strategy crafted by K–8 math specialist Jenna Laib and her colleagues provides teachers with an opportunity to gradually display complex graphical information and build students’ questioning, sense-making, and evaluating predictions.

For instance, in one third-grade class, students are given a bar graph without any labels or identifying information except for bars emerging from a horizontal line on the bottom of the slide. Over time, students learn about the categories on the x -axis (types of animals) and the quantities specified on the y -axis (number of baby teeth).

The graphs and the topics range in complexity from studying the standard deviation of temperatures in Antarctica to the use of scatterplots to compare working hours across OECD (Organization for Economic Cooperation and Development) countries. The website offers a number of graphs on Google Slides and suggests questions that teachers may ask students. Furthermore, this site allows teachers to search by type of graph (e.g., scatterplot) or topic (e.g., social justice).

2. Three reads: The three-reads strategy tasks students with evaluating a word problem in three different ways . First, students encounter a problem without having access to the question—for instance, “There are 20 kangaroos on the grassland. Three hop away.” Students are expected to discuss the context of the problem without emphasizing the quantities. For instance, a student may say, “We know that there are a total amount of kangaroos, and the total shrinks because some kangaroos hop away.”

Next, students discuss the important quantities and what questions may be generated. Finally, students receive and address the actual problem. Here they can both evaluate how close their predicted questions were from the actual questions and solve the actual problem.

To get started, consider using the numberless word problems on educator Brian Bushart’s site . For those teaching high school, consider using your own textbook word problems for this activity. Simply create three slides to present to students that include context (e.g., on the first slide state, “A salesman sold twice as much pears in the afternoon as in the morning”). The second slide would include quantities (e.g., “He sold 360 kilograms of pears”), and the third slide would include the actual question (e.g., “How many kilograms did he sell in the morning and how many in the afternoon?”). One additional suggestion for teams to consider is to have students solve the questions they generated before revealing the actual question.

3. Three-Act Tasks: Originally created by Dan Meyer, three-act tasks follow the three acts of a story . The first act is typically called the “setup,” followed by the “confrontation” and then the “resolution.”

This storyline process can be used in mathematics in which students encounter a contextual problem (e.g., a pool is being filled with soda). Here students work to identify the important aspects of the problem. During the second act, students build knowledge and skill to solve the problem (e.g., they learn how to calculate the volume of particular spaces). Finally, students solve the problem and evaluate their answers (e.g., how close were their calculations to the actual specifications of the pool and the amount of liquid that filled it).

Often, teachers add a fourth act (i.e., “the sequel”), in which students encounter a similar problem but in a different context (e.g., they have to estimate the volume of a lava lamp). There are also a number of elementary examples that have been developed by math teachers including GFletchy , which offers pre-kindergarten to middle school activities including counting squares , peas in a pod , and shark bait .

Students need to learn how to slow down and think through a problem context. The aforementioned strategies are quick ways teachers can begin to support students in developing the habits needed to effectively and efficiently tackle complex problem-solving.

• Need to solve an intractable problem? Collaboration is hard but worth it.

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Complex problems facing cities like homelessness and climate change can only be solved by multiple organizations collaborating across boundaries, say Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson. 

Featuring jorrit de jong and amy edmondson, november 9, 2023 42 minutes and 21 seconds.

Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson say the big, intractable challenges facing city leaders today are too complex to be addressed by any one agency or government department. Complex challenges like the shortage of economic opportunity and affordable housing, homelessness, the effects of the climate crisis, and crime, can only be solved by multiple organizations working together. But that’s easier said than done. Bringing together government agencies, nonprofits, private businesses, academia, and the public into successful collaborations can be a huge challenge. Different people bring different agendas and goals. They don’t necessarily trust each other. Sometimes they can’t even agree on what the problem actually is, and they fail before even getting started. In a recent study, de Jong and Edmondson found that the most successful problem-solving collaborations have a number of things in common, including building a culture of safety and trust and being empowered to try, fail, and learn from mistakes. Sometimes, they say, the key can be just finding a place to start. 

Episode Notes:

Martínez Orbegozo, E. F., de Jong, J., Bowles, H. R., Edmondson, A., Nahhal, A., & Cox, L. (2022).  Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations . The Journal of Applied Behavioral Science, 58(4), 595-645.  https://doi.org/10.1177/00218863221118418

Jorrit de Jong is the Emma Bloomberg Senior Lecturer in Public Policy and Management at Harvard Kennedy School. He is director of the Bloomberg Center for Cities at Harvard University. His research and teaching focus on the challenges of making the public sector more effective, efficient, equitable, and responsive to social needs. A specialist in experiential learning, he has taught strategic management and public problem-solving in degree and executive education programs at HKS and around the world. He is also faculty co-chair of the Bloomberg Harvard City Leadership Initiative, a joint program of Harvard Business School and Harvard Kennedy School, the world’s most comprehensive effort to advance effective problem-solving and innovation through executive education, research, curriculum development, and fieldwork in cities. 

He is also Academic Director of the Innovations in Government Program at the Kennedy School’s Ash Center for Democratic Governance and Innovation. In that capacity, he launched the  Innovation Field Lab , an experiential learning, executive education, and action-oriented research project working with 15 cities in Massachusetts and New York to help them leverage data, community engagement and innovation to revitalize distressed and underinvested neighborhoods. He holds a PhD in Public Policy and Management from Vrije Universiteit Amsterdam, as well as a master's in philosophy and a master's in public administration from Leiden University. He has written extensively, including the books “The State of Access: Success and Failure of Democracies to Create Equal Opportunities;” “Agents of Change: Strategy and Tactics for Social Innovation;” and “Dealing with Dysfunction: Innovative Problem Solving in the Public Sector.”  

Amy C. Edmondson is the Novartis Professor of Leadership and Management at the Harvard Business School, a chair established to support the study of human interactions that lead to the creation of successful enterprises that contribute to the betterment of society. Edmondson has been recognized by the biannual Thinkers50 global ranking of management thinkers since 2011, and most recently was ranked No. 1 in 2021. She also received that organization’s Breakthrough Idea Award in 2019, and Talent Award in 2017.   

She studies teaming, psychological safety, and organizational learning, and her articles have been published in numerous academic and management outlets. Her 2019 book, “The Fearless Organization: Creating Psychological Safety in the Workplace for Learning, Innovation and Growth,” has been translated into 15 languages. Her prior books: “Teaming: How organizations learn, innovate and compete in the knowledge economy;” “Teaming to Innovate;” and “Extreme Teaming” explore teamwork in dynamic organizational environments.  Edmondson’s latest book, “Right Kind of Wrong,” builds on her prior work on psychological safety and teaming to provide a framework for thinking about, discussing, and practicing the science of failing well. Edmondson received her PhD in organizational behavior, AM in psychology, and AB in engineering and design from Harvard University.  

Ralph Ranalli of the HKS Office of  Communications and Public Affairs is the host, producer, and editor of HKS PolicyCast. A former journalist, public television producer, and entrepreneur, he holds an AB in Political Science from UCLA and an MS in Journalism from Columbia University. 

The co-producer of PolicyCast is Susan Hughes . Design and graphics support is provided by Lydia Rosenberg , Delane Meadows , and the OCPA Design Team. Social media promotion and support is provided by Natalie Montaner and the OCPA Digital Team.  

For more information please visit our webpage or contact us at [email protected] .

This episode is available on Apple Podcasts, Spotify, and wherever you get your podcasts.

Preroll: (Ralph Ranalli): PolicyCast explores evidence-based policy solutions to the big problems we’re facing in our society and our world. This podcast is a production of the Kennedy School of Government at Harvard University. 

Jorrit de Jong (Intro): Let me give you one example, homelessness. You can think of that as one big problem, but if you break it down into smaller subsets of problems, you see that some people experiencing homelessness are dealing with mental illness and others are the victims of domestic violence, and yet others are experiencing substance abuse issues and others may have lost their house and are living below the poverty line. When you disaggregate a problem, you see a variety of different causes and consequences, but also it becomes very clear that, for some parts of the problem, you need the social services department, for another part of the problem, you need affordable housing, and for another part of the problem, you may need law enforcement or addiction help.  

Amy Edmondson (Intro): The problems can be roughly referred to as wicked problems, which are the kinds of problems that have incomplete, contradictory, and shifting requirements. They do not have easy answers and they impact different groups in different ways. They're just by their very nature hard to solve, and so you need the different perspectives both for the innovation and the creative problem solving that that allows, but also for the acceptability of the solution. If people aren't participating, then they're unlikely to appreciate and effectively use or implement solutions that just came in from outside and, "Here, we think this is going to fix your problem for you." 

Ralph Ranalli (Intro): Cities, like our world, are complex and interconnected places. So it’s hardly a surprise that our most intractable problems—lack of economic opportunity and affordable housing, homelessness, the effects of the climate crisis, crime—are that way too, complicated and seemingly hopelessly tangled, like that box of extensions cords you’re too afraid to bring up from the basement. Harvard Kennedy School faculty member Jorrit de Jong and Harvard Business School Professor Amy Edmondson say the big challenges facing city leaders today have another thing in common: they’re too tough to be addressed by any one agency or government department and can only be solved by multiple organizations working together. But that’s easier said than done. Bringing together city departments, nonprofits, private business, academia, and the public into successful collaborations can be a huge challenge. Different people bring different agendas and goals. They don’t necessarily trust each other. Sometimes they can’t even agree on what the problem actually is and they fail before even getting started. In a recent study, de Jong and Edmondson found that the most successful problem-solving collaborations have a number of things in common, including building a culture of safety and trust and being willing to try, fail, and learn from mistakes. Sometimes it's even just finding a place to start. Jorrit de Jong is the director of the Bloomberg Center for Cities at Harvard University and academic director of the Innovations in Government Program at the Ash Center for Democratic Governance and Innovation at HKS. Edmondson is the Novartis Professor of Leadership and Management at the Harvard Business School, whose books and writings on teamwork in successful organizations have been translated into 15 languages. They’re here with me today. 

Ralph Ranalli: Amy, Jorrit, welcome to PolicyCast. 

Jorrit de Jong: Thanks for having us. 

Amy Edmondson: Great to be here. 

Ralph Ranalli: We're talking today about cross-boundary collaboration, which I think is a term that a lot of people aren’t familiar with. Well maybe they're more familiar with the general concept, but can we start with a little bit about its origins in the context of solving intractable problems in cities and why it's important? Jorrit do you want to start us off? 

Jorrit de Jong: Sure. Well, the main thing about cross-boundary collaboration is that it is something that is necessary because the problems that we face in society today are multifaceted, they're complex, they're volatile and no single organization, unfortunately, is able to tackle them. When we talk about homelessness or climate change or poverty or crime, we need multiple organizations to work together to come up with a good diagnosis of what the problem is and then to generate ideas for action and then to implement those ideas. 

Ralph Ranalli: Amy? 

Amy Edmondson: Let me just even say something more basic, which is what's a boundary? I mean, a boundary is a line between groups. The kinds of groups that Jorrit and I studied include expertise groups, different sectors, different employers, different organizations, even different levels on a hierarchy. Having people come across those boundaries to do something together is what we studied. 

Ralph Ranalli: Right. The stakeholders are usually government, nonprofits and NGOs, the business community, and academia. Is there anything else on that list? 

Amy Edmondson: Well, I think, occasionally, citizens, community. 

Ralph Ranalli: Amy, you've written four books on the subject of teamwork including one where you said: "The work done in the modern organization is less and less about looking inward and creating strong teams inside a company and more about teaming across boundaries that are often in flux. What’s causing that shift to companies and organizations needing to look outwards? 

Amy Edmondson: Organizations are more and more dependent on the cooperation of and the contributions of people from other organizations. That can be as simple as suppliers and customer organizations where the degree to which you can collaborate effectively across those boundaries matters for the effective delivery of services and goods in supply chains of all kinds. That's just one ordinary way of doing business that involves that. Beyond that, there's a real interest for companies and government organizations and others to be working together to solve some of the more thorny problems that society faces. These are the kinds of problems that cannot be solved by one organization alone or even one sector working alone, so there's just more need for that kind of reaching out, reaching across, and collaborating. 

Ralph Ranalli: Jorrit, you're a leading scholar on collective governance to address multi-stakeholder problems. What are some examples of the problems that either can only be solved by or addressed or best addressed with cross-boundary collaboration? 

Jorrit de Jong: Yeah. I would say that there's almost no significant problem facing cities today that can be solved by a single organization. Local government obviously offers a variety of basic services and is responsible for law enforcement in a variety of different areas, but most of the problems— whether it's crime or economic development or homelessness—require multiple types of expertise, multiple skill sets, resources that cannot be offered by one organization alone and, therefore, if you really want to make progress on these issues, you can't go it alone. 

It makes sense that we have silos within government agencies. Division of labor is, of course, a very basic principle of organizational design. You can't do everything all at once, and therefore we've created departments, a department for buildings, a department for parks and recreation, a department of police, fire department and so forth, human services, but those departments are focused on the types of activities, types of services that they're responsible for. What we increasingly find is that the way problems manifest themselves in the real world requires interventions, actions and resources from multiple departments. Even within governments, you need cross-boundary collaboration where the boundaries are the departmental boundaries. 

Let me give you one example, homelessness. You can think of that as one big problem, but if you break it down into smaller subsets of problems, you see that some people experiencing homelessness are dealing with mental illness and others are the victims of domestic violence, and yet others are experiencing substance abuse issues and others may have lost their house and are living below the poverty line. When you disaggregate a problem, you see a variety of different causes and consequences, but also it becomes very clear that, for some parts of the problem, you need the social services department, for another part of the problem, you need affordable housing, and for another part of the problem, you may need law enforcement or addiction help.  

The way problems manifest themselves in cities, it's very varied. It varies from city to city. It varies from time to time. And it definitely depends on how you look at it. The way you look at it can inform the way you try to solve it. What we're claiming in this study is that the nature of these problems requires a more comprehensive, a broader, more holistic look and, therefore, it requires multiple organizations to look at it together and then to solve it together. 

Amy Edmondson: Right, and I'll just double down on that idea, the nature of the problems. I mean, the nature of the problems can be roughly referred to as wicked problems, which are the kinds of problems that have incomplete, contradictory, and shifting requirements. They do not have easy answers and they impact different groups in different ways. They're just by their very nature hard to solve, and so you need the different perspectives both for the innovation and the creative problem solving that that allows, but also for the acceptability of the solution. If people aren't participating, then they're unlikely to appreciate and effectively use or implement solutions that just came in from outside and, "Here, we think this is going to fix your problem for you." 

Ralph Ranalli: Right. I think we all have this lovely ideal of what collaboration looks like, right? But one of the things that struck me when I was reading your study is how difficult it is and how significant the barriers are that need to be broken down. On the one hand, we have a nice picture in your mind of people holding hands and singing kumbaya and everyone bringing their own expertise to bear on a problem in this lovely holistic way, but on the other you identified the process of just getting started as something that's difficult to the point where you used the term "disorientation" to talk about early phase of trying different groups together. Can you talk a bit about that notion of disorientation and why it's so difficult to get traction with cross-boundary collaborations? 

Jorrit de Jong: Absolutely. You may know the expression, "If you have a hammer, everything looks like a nail." If you are the Department of, let's say, Parks and Recreation, you look at a problem from that perspective and you think, "Oh, the problem to solve is to get this park clean and safe, and you may look at the people experiencing homelessness in that park as people that need to be removed, but if you are from the Department of Social Services, you look at the people in the park and you think, "Hey, we need to help these individuals," get them into housing, stabilize their condition and so forth, and you don't care as much about the park. Both are very legitimate perspectives, but very often—and this is what we found in a number of different studies that we conducted over the past 10 years—is that there are, in almost every cross-boundary collaboration phases, three major barriers.  

The very first one is how to define the problem. How do we define the problem in a way that generates sufficient consensus, not full consensus, but sufficient consensus to actually start working on it, because, if you don't see yourself in that problem definition, you're like, "What am I doing here?" It needs to be sufficiently inclusive to get the right parties on board and to get started. The second barrier is actually team building. Amy is, of course, an expert on this. It requires a certain kind of psychological safety—and maybe Amy you can say a little bit more about that—to actually engage in work where you don't know the problem yet and where you don't know the solution yet and where you don't maybe trust each other or understand each other enough yet to work together. 

The final barrier that we always find is multiple accountability challenges. You're committed to solving the problem and to working together, yet you're also on the payroll of your organization and, at the end of the day, your boss or your constituents will hold you accountable for the siloed organizational task and not the work that you did with other parties, and so there's this natural tension that occurs. 

Amy Edmondson: Yes. I mean, I'll build on that by saying, you mentioned psychological safety, and that's something that research, including my own, has shown is a really important factor in teamwork in general. And it's because it's not easy to be candid, it's not easy to speak up with a wild idea that people might laugh at, and it's not easy to ask for help if you don't understand something. Nobody likes to admit their ignorance or advertise their incompetence. I use those terms almost tongue in cheek, but we can naturally think, "Oh, someone will think I'm an idiot because I don't know something." It's much easier to hold back, wait and see. And so there's that challenge of speaking up. 

Roughly speaking, there's psychological, I mean, there's many psychological barriers, and you alluded to several, but just, "I don't maybe trust you because you come from a different department or a different background. I don't feel safe speaking up, honestly, candidly." There are so many things that get in the way of the innovation we're talking about, so it's much, much easier to fail than to succeed in this domain, and then layered on top of that are what I would call technological or logistical hurdles related to the jargon, different expertise areas, and different sectors have different jargon. The alphabet soup is a really big deal in the public sector and private sector, and so you can have people talking right by each other and really just struggling to have the effortless collaboration that you envision in this kumbaya moment that you recalled. You can't underestimate both the logistical, technological challenges and the psychological, sociological challenges. 

Ralph Ranalli: Sure. If you just think about the groups that you're talking about who are trying to collaborate with each other. One example is you've got nonprofits who are probably distrustful of for-profits. A lot of the time, that's a common nonprofit worldview. Then you've got for-profit businesses who are often distrustful of government, and … 

Amy Edmondson: ... and vice versa. 

Ralph Ranalli: Exactly, and vice versa. You talked about in the study about finding an entry point. Can you talk about that, Amy, maybe starting out with what is an entry point and how does one help you break through those initial difficulties and get a collaborative process moving? 

Amy Edmondson: Yeah. I guess what I will have to admit is that this is more descriptive, and I think it makes good sense theoretically and practically, but I'll tell you what we found. What we found was, as I alluded to earlier, that most, all the teams struggle, but the ones that end up making traction in their wicked problems and their challenging problems are the ones, now this will sound almost tautological, but they're the ones who found an entry point. There's a point at which, if you find an entry point, you get enough momentum to keep going through the hard work of teaming up across boundaries and making progress in new territory, and it's easy not to find one. 

What is an entry point? It took different forms in different projects, but we created this acronym, M-A-A-P. It means they found some way to get started that was meaningful. People could agree that this was connected to our broader goal even though it isn't a solution to our broader goal. It was meaningful. It was acceptable, meaning, different constituents would find it an okay thing to be working on. It was actionable, right? Again, not a magic wand or big solution to everything, but it was something you could go try, and it was provisional. I mean, it was almost deliberately seen by all as a starting point that, as we learn more together, we will get more clear, we will get better at making progress. 

Ralph Ranalli: At this point, I'd really like to if we can get into some concrete examples. In your study, you used the example of Manchester, New Hampshire. There were 10 other groups that were a big part of your study. Can you talk about how the group in Manchester, New Hampshire, found its entry point and what problem they were tackling? 

Jorrit de Jong: Absolutely. It's a great story, and I have to say it's not a story that is finished. It's a work in progress. I think it's fair to say that most of these problems are not solved. You can make progress. You can mitigate the problem, but there's only one way, as Amy suggested, to get started, which is to get started, but then you have to figure out and agree with this whole group, "Where do we start and how do we start?" There's often a theme that we see around the ideal is the enemy of good, right? We think we know enough about the problem to say that any tiny step in the right direction is not sufficient, because it will not solve the problem or it will not make progress fast enough, but what we've found in this study is that, if you start and focus on something small but meaningful, and if you make sure that you learn from that first step, you will see the next step and the next step and the next step. 

In Manchester, New Hampshire, they were facing multiple crises, homelessness on one the hand and opioid abuse on the other. There was overlap, but the city did not have data on how exactly these problems were intertwined, who was experiencing what problem or what condition and how to intervene as a city. Now, the parties in Manchester included social service providers, caregiving organizations, the police, fire departments, the Department of Public Works, but also the business community, especially downtown where business owners were complaining about people sleeping on the streets and panhandling. 

The mayor, Joyce Craig, really was worried about the situation and did not have necessarily enough resources for affordable housing or for the help, but she did know that just banning panhandling wasn't going to solve the problem. It's like fighting a symptom and not addressing the underlying problems. However, the business community was primarily interested in addressing that part of the problem because it mattered most to them and to their customers. What they agreed to do is to say, "Okay, we are going to think of panhandling as an entry point, but under one condition, that if we discourage panhandling, then we will make sure that the individuals that are being removed from the downtown area will be directed to treatment, to shelter, to social workers and so forth, and we will learn from what they're experiencing, what their needs are, and then we will use that to generate new funding and additional services so that we can make progress on the larger issue and the underlying problems."

Even though it looks like fighting a symptom to some and solving a problem to others, it allowed the group to start to work together, to look at the problem together, to learn from what works and what doesn't work together. And because they formed a coalition as such, they had a much better case to make to the state and to other funders. A few years later, they changed the structure in their governments. They have much more cross-silo collaboration in their government because they did find out that about 50% of the people who were homeless also were struggling with addiction problems. They changed their approach to helping the individuals, but they also helped create better conditions in downtown at the same time. 

Now, has it been solved? Absolutely not, but is the city in a better place to tackle the problem? Absolutely, and that is basically what we're seeing in all of those teams that are making progress. How they're getting traction is they start somewhere that is imperfect, but they learn, and as they learn they get to a better place. 

Amy Edmondson: One thing to just underline strongly here is that we've talked about, in a sense, to get started, you have to get started. And that might sound at first glance like a willpower problem where we just have to take the first step. I don't want to underplay how creative the first step was. 

This isn't a matter of: "It's obvious what the first step is. Let's just do it." This is truly a matter of: "We don't have a clue what the first step is because it's a wicked problem with multi-dimensional, multifaceted challenges." It's actually a team creative project to figure out an entry point, something that we can do that's meaningfully connected to our broader, ambitious goal that again is acceptable and something fundamentally we can learn from together. 

Jorrit de Jong: One other example that I really love, and not just because it's from my home country, the Netherlands, is the problem that they had in the City of Breda with illegal grow houses. They were growing marijuana. 

The idea was, or the suspicion was, that organized crime was exploiting or coercing low-income residents to use their attics and basements for this illegal activity. The police and the prosecutor's office had been trying the traditional law enforcement approach, but the community wouldn't want to work with them because they were afraid or didn't trust law enforcement.  

Then they started working within a utility company that had been experiencing electricity theft because grow houses take a lot of electricity. They also worked with the City of Breda, which was interested in community engagement, and they worked with a tax office who was interested in money laundering related to organized crime. They came up with a very different approach, and they found their entry points were focused on fire safety, because everybody cares about fire safety because your family needs to be safe, and so- 

Amy Edmondson: Neighbor could be- 

Jorrit de Jong: Your neighbors could be having a grow house and create that risk for you because they're using the electricity and the wiring catches fire because of the overuse, the overload. They started knocking on doors and said , "Hey, here's what you need to know about fire safety. If you smell this smell," and they had a sample with them, "then you might be at risk, and so you need to report that." That was a way to build trust with the community. Well, did it solve organized crime? Did it end illegal grow houses? No, but at least they found a way, literally, into the houses, an entry point, but also into the problem and, from there, they learned and adjusted their approach. I think that's another example of not giving up on the goal, the ultimate goal, but just structuring the process of learning. 

Ralph Ranalli: It's wonderful when these things succeed, but they don't all succeed. What have you found about when they fail, why they fail? 

Amy Edmondson: In a way, I mean, this is a bit tautological, but they fail because they fail to overcome the very real hurdles. These challenges are both creative challenges, they're political, they're effortful. There's lots and lots of pushback and barriers. They're overwhelming, so it's almost the assumed outcome that they will struggle anyway. 

Ralph Ranalli: You talk in the study about inherent paradoxes. Can you expound on that a little bit? 

Jorrit de Jong: Sure. There's a chicken-and-egg issue which is interesting to think about. For busy people and organizations with limited resources to commit to a collaboration, they need to know what's in it for them or why it would be important for them to participate. But you don't know that until you actually start looking at the problem together.  

For example, the growing house case did not include the fire department at first. It did include the tax office. Now, when you would have asked the fire department, "Hey, do you want to go chase organized crime in this neighborhood?" They're like, "Why would we do that?" They're like, "We got fires to put out. Organized crime is not in our job description," but because they learned more about the problem, and one part of it was the fire risk, then it became more relevant for the fire to be included. 

Here's the other thing. The tax office was less relevant, and you can imagine this poor tax inspector who would go to you about like, "What have you been doing lately, John?" and then, "Well, I've been finding illegal grow houses and detecting fire risk." Well, that's not your job description either, so you can see that, because all these problems were multifaceted, that a case has to be made for involvement and inclusion and participation. The inherent paradox there is that you need to have a broader group to work and look at the problem, but in order to get that group to look at the problem, you need to have a sufficient idea of what you're doing. That cannot be resolved one way or the other, other than just getting started and trying something out. 

Amy Edmondson: Yeah, and people who are willing to just be operating slightly outside their normal job description and willing to be creative and not worry so much about: "Is this my boss' number one priority right now?" because they glimpse an opportunity to make a real difference in something that speaks to them and matters to the community. 

Ralph Ranalli: Right, and you go back to the trust issue, too. You need to trust enough to have collaboration, but you also build trust through collaboration, so we're back to chickens and eggs. 

Amy Edmondson: It's chickens and eggs for sure. I'm not sure it's paradoxes. To me, the word paradox is overused. I shouldn't maybe say that, but it technically means two things that can't both be true at the same time, versus I think what we're talking about is a little bit more interesting and subtle, which is it's hard to get started and it's hard to know which comes first, the chicken or the egg. 

Ralph Ranalli: I love that you quoted the philosopher John Dewey and his saying that: “A problem well put is a problem half solved.” But that's not necessarily easy either. What happens when you can't even agree on the problem? I live in a suburb of Boston and our local political dividing line basically breaks down along the issue of affordable housing. One group identifies the lack of affordable housing as the problem, where the other basically views the impulse to build more affordable housing as the problem. What happens when you can’t agree on  whether a problem actually exists?  

Amy Edmondson: In a way, it's everything. It's the frame. With that frame, if you get stuck and stay in that frame, you will get nowhere. That is a guarantee because neither side is going to willingly change their view of the problem. What's needed is something that both sides care about, the future, the children and the future, or things along those lines, access to our schools, what have you.  

I won't try to solve that particular problem in your particular area, but the only way to break out and go forward is by finding an overarching shared goal or value that we both care about and then we get to start to take baby, creative steps toward what might this look like to help us resolve some of that very real tension. 

Jorrit de Jong: I would also say that a lot of this work was informed by Bloomberg Harvard City leadership program that Amy and I both teach in. It's a program for mayors and their senior teams. Mayors are often the ones nominating a problem for action. They run on a campaign platform, and they want to do something about inclusive growth or climate resilience or crime, and then, when they create a task force or try to build a coalition around that problem, it is important for them to know that, yes, they need to say, "This is the problem that I care about."  

But they also, as authorizers of this work, need to keep an open mind and be flexible because, if they're not flexible, the group will be reluctant to zoom in on one particular entry point that doesn't immediately make sense. Knowing what the nature is of this work—going back to Amy's notion earlier about the wicked problem—acknowledging and being explicit that you expect the group to learn rather than to deliver on the specific thing you're asking them to do.  What we've seen is that the role of authorizers is often understudied. One of the things that we see in the groups is those groups that felt like they had agency—they had the license to innovate and the permission to learn and develop as they went along—those groups were more successful in making progress. In our executive education program for mayors, both Amy and I spent a lot of time like, "How can leaders create the conditions for these diverse teams to do their work and to make meaningful progress?" 

Ralph Ranalli: I was interested in the personal aspect of when these collaborations start achieving success. What have you seen in terms of transformations in people's attitudes and outlooks when all of a sudden things start clicking and positive things start happening? What have you seen in terms of changes in the participants once this cross-boundary collaboration starts working? 

Amy Edmondson: I'll just say more abstractly, and then maybe Jorrit can give more concrete observations, but more abstractly, they start to feel like a "we" rather than, "I'm here. I'm from tax," or, "I'm from fire," or, "I'm from city hall.” They start to be part of the homelessness task force. They start to feel like each other as a mighty resource and that they start to care about each other, they start to care about their work together. 

Jorrit de Jong: Yeah. A colleague of ours, Ronnie Heifetz, uses the metaphor of a vegetable soup where you can throw different types of vegetables in a pan and add cold water, and then these vegetables will remain the same thing and there's no blending. You can also turn up the heat and cook them to pieces, and it's like one ratatouille, but the idea is to raise the temperature enough so that the individual vegetables still keep their taste and their shape, but they also start to form like a vegetable soup. Very often, we think of these processes of cross-boundary collaboration as pressure cookers. Without heat, there will be no dinner, but with too much heat, there will also be no dinner or it won't taste very well. Getting the temperature right, raising the pressure, creating a holding environment if you like around a group, which is what we do in our Executive Education programs, we bring people together and support them as they engage with the work and with each other and regulate the temperature so that they get to a level of productivity and trust that is required to make progress. 

Ralph Ranalli: You also teach this in the Executive Education program. Why is it important to connect with that audience? 

Amy Edmondson: I mean, I think, in professional schools, certainly in the Kennedy School and the Business School at Harvard, our goal is knowledge for action. Our research is always in the back of our minds. Sometimes, in the very front of our minds is how would this work? What can we learn about how to help people in tough jobs, tough leadership roles? How can we help them do a better job in achieving their results? 

One of the ways that we both share, but also develop our insights is in the executive classroom. We are teaching there, but we are also learning from them, from their feedback, from their examples, from their stories. We use the case method quite deliberately so that we have some principles that we're trying to convey and make them memorable and sticky through the stories, but we also want to hear their stories and how they've seen this work in practice, so that allows us to learn, that allows them to learn. 

Jorrit de Jong: Yeah, I would say I fully agree with that. A lot of the research questions come from practice and come from our interactions with mayors and their senior leaders and others. The work that we do at Harvard is  only good if it's both rigorous and relevant. If it's only rigorous and not relevant, we wouldn't want to do it because why? 

Amy Edmondson: If it's only relevant and not rigorous, then we don't feel so good either. 

Jorrit de Jong: Exactly, because you don't want to be sharing just ideas that are not rooted in research, right? That's why Amy and I and the whole group of authors, when we learned early on that mayors were struggling with cross-boundary collaboration and forming coalitions and task forces, we said like, "That's a really interesting research question." Amy had done research for many years on teaming and increasingly on wicked problem solving. I had been doing a lot of work on collaborative governance, but mostly at national or even international levels. We felt like, if we could combine our expertise and bring in some other colleagues, Hannah Riley Bowles, Eva Flavia Martinez Orbegozo, Jan Rivkin, and Mark Moore, then we could actually fill that gap. 

The studies that we've recently published are the first fruits of that labor, and we immediately bring it back to the classroom. When we teach now, we refer to these studies and we say, "Well, we don't have the definitive answer to the question how to do this, but we have some ideas that may help you guide the work as you go along." 

Amy Edmondson: We see if it resonates. Does it resonate? 

Ralph Ranalli: We've been talking about using this approach at the city level, but a lot of the problems that cities are facing are national and international in scope: climate readiness, the green energy transition, migration. Does the cross-boundary collaboration approach scale up? 

Jorrit de Jong: Well, we haven't done that research yet, but I think what we are seeing in the cross-sector collaborations in cities, those themes are not necessarily only happening in cities. It's much more about different professions, disciplines, organizational realities trying to work together than that it is about city-specific issues. Obviously, at the national level and at the international level, you have many more wicked problems, and some are the same, climate change, poverty, drugs, crime. Anywhere where people try to make progress on wicked problems, you will see the same types of mechanisms, barriers and patterns. Therefore, our hypothesis is that this applies to other contexts as well, but we haven't done that research yet. 

Amy Edmondson: We haven't done that research, but I think, if you look to any effective body that has trudged, made a dent in something, maybe child labor or human trafficking at a more global scale versus a local city scale, you will always find the requirement of different areas of expertise more often than not coming from multiple organizations, the NGOs, governments, business, large business players. Obviously, not all of these efforts are successful, but if they're serious, they will nearly always involve cross-boundary collaboration. 

Ralph Ranalli: We've reached the point in the podcast where we put the policy in PolicyCast, which is where I'm going to ask you for some specific recommendations, and in this case I think policy recommendations. Do you have any  policies that would encourage or make it easier to create successful cross-boundary collaborations or to help them along the road to success? What policies could turbocharge this process, which has shown that it can make a dent in big and intractable problems? 

Amy Edmondson: This is where I'm not a policy person, so I could just have a free ride here, but I will say one thing. I mean, one policy thing that occurs to me is making funding available. I think, oftentimes, funding is only available for things that are really clear cut and proven and have been done before. Making seed funding available for this kind of exploratory work is something that I think could be a policy issue. 

Jorrit de Jong: I don't think it is a policy question. I think it's a leadership question and a management question. What is helpful for creating and sustaining cross-boundary collaboration is for authorizers to be supportive of the process of, as Amy calls it, execution as learning, so try something out, come back and hold teams accountable for learning.  

What I always tell authorizers is that, if you say, "Well, have you fixed the problem?" then everybody is going to be very fixed on delivering exactly what they think the authorizer expects. And that may not be the best thing for solving the problem. What you have to do as an authorizer is to say, "Well, I expect you to do something" and whether it works or not … 

Amy Edmondson:  … learn from it … 

Jorrit de Jong:  ... it doesn't matter, but you have to come back and tell me, "This is what I've done. This is what worked. This is what didn't work. This is what I've learned or what we have learned, and this is the next step that we're thinking of taking, and we want authorization for that next iteration."  

I think that is a very different way of providing guidance and support and sponsorship than many authorizers are used to. I would say, if that's something, if you're a mayor or if you're a secretary, the national government or if you're a CEO even, then that's the difference in how you create the conditions for this type of work to be successful. 

Ralph Ranalli: Great. Well, I would just like to thank you both. This was a really interesting conversation that I enjoyed very much. Thanks for your time. 

Amy Edmondson: Thanks for having us. 

Ralph Ranalli (Outro) : Thanks for listening. Please join us for our next episode, when Harvard Kennedy School Professor David Deming and Harvard University Economics Professor Raj Chetty will discuss their research on how legacy preference affects college admissions.  

And please subscribe to PolicyCast on your favorite podcasting app so you don’t miss any of our great upcoming episodes. If you have a comment or a suggestion for the team here at PolicyCast, please drop us an email at [email protected]—we’d love to hear from you. And until next time, remember to speak bravely, and listen generously. 

More from PolicyCast

GP Essay #25: Can education solve all problems? 

The myth that education is the magic bullet to solve the problems that plague the modern world is one that is rooted in Lyndon B. Johnson’s Great Society, which pivoted away from economic redistribution policies towards viewing education as the panacea to income inequality. While education empowers individuals and provides them access to more opportunities, and that in this respect, it is indeed a key tool and the answer to some of the many challenges which we face today, it cannot stand alone or solve all problems. Given the complexity of the issues and its inherent flaws and limitations, education alone cannot solve all the issues within our world today.

At first glance, it appears that education can catalyse positive social change through enlightening and empowering individuals and by broadening their horizons. Through formal education, individuals gain a better understanding of the world around them and their place in the world. Besides enlightening individuals, an education can empower one to improve one’s community, or to surmount one’s unique challenges. For instance, with respect to gender inequality, studies have revealed that women in developing countries who have been educated are half as likely to undergo harmful cultural practices such as female genital mutilation, and four times more likely to protect their daughters from it. Educated women are put in a better position to realize that they have the right to speak up and defend themselves from any abuse or harm. Besides empowering individual victims of gender inequality, education also ensures that whole communities are enlightened, and are able to solve social issues together. International efforts to combat racism and intolerance in schools have been introduced by the United Nations Educational, Scientific, and Cultural Organization (UNESCO). This project, titled ‘Teaching Respect for All’ was designed to develop curriculum for use across the globe to promote tolerance and respect for all people. It is evident that education is one of the most effective ways to help individuals adopt new mindsets and perspectives, in order to efficiently solve problems. 

In addition, education levels the playing field of the disadvantaged by providing them access to opportunities to improve their standard of living and overcome the problems their communities might face. It does so by equipping people with the necessary knowledge and skills which are needed to seek employment. This understanding underpins many humanitarian projects such as the Thailand Hilltribe Education Project (THEP), which provides scholarships to needy students from Thailand’s relatively impoverished hilltribes. One of their beneficiaries is a living testament to the effectiveness of education in lifting individuals out of poverty; a recipient of the THEP scholarship, Ms Kanokwan, who was born into a family of farmers, managed to attain her bachelor’s degree in English, and is now a teacher and a contributor to their sponsorship programme. Besides uplifting individuals and their families, societies which benefit from formal education seem to enjoy higher standards of living. According to the Education Transforms booklet released by the EFA Global Monitoring Report, this is because an educated populace is also a more productive populace, and productivity gains fuel economic development, which collectively raises the standard of living for a society. Hence, it can be argued that with education, people are more likely to enjoy a better life and hence, education is indeed the key to solving problems like poverty.

Yet, notwithstanding the fact that education has been effective in solving problems like discrimination and poverty, education should not be seen as a panacea to all problems. This is because there are many obstacles and aggravating factors which might limit the effectiveness of education. Education can only begin to tackle a problem if education is possible in the first place, for instance. The poor and impoverished cannot afford tuition fees, much less other learning tools and resources. Besides tangible barriers, intangible barriers include attitudinal factors: for many living in rural areas, education is sometimes seen as unnecessary or secondary, and comes at a higher opportunity cost as children are unable to help out as manual labour or farm help. A survey conducted by the child labour showed that 75% of the parents in Bangaladesh are unwilling to send their children to school because school expenses are a heavy burden. If the masses are unable to access education due to poverty and destitution, children will continue to be deprived of education, rendering it ineffective in solving problems. 

In addition, there are certain problems which education would be unable to resolve alone. Although environmentalist movements like the Youth for Climate movement have been gaining traction in recent years, the United Nations noted that in 2018, carbon dioxide emissions were on the rise for the first time in four years. A report released by the United Nations Environment Programme indicates that a tipping point has already been reached in the Artic and Greenland, where permafrost has started melting more than 70 years before it was expected to. Even as Canada announces a ‘climate emergency’, its political leaders approved of a new pipeline deal for natural gas. This is because of the sheer complexity of problems like climate change and environmental degradation; most of the time, the education of consumers alone is inadequate and ineffective in halting environmental destruction that has been ongoing for decades. In such cases, strong political will and corporate-sector leadership will be more effective. Siemens, the world’s largest manufacturer, has devoted more than 100 million euros to reducing its carbon emissions by half by 2030. Morocco, for instance, has introduced – and is set to meet – ambitious goals, such as targeting to have 42% of installed electricity production capacity from renewable energy by 2020. These examples illustrate the fact that political will and leadership would be more effective in mitigating climate change, especially because domestic energy consumption forms a remarkably negligible percentage of carbon emissions. Some of the problems which we face require a multidimensional and a multi-pronged approach, in which education can only form one pillar.

Finally, education has its own inherent limitations, which may render it ineffective and even counterproductive in solving social problems. On the surface, it may seem that education is a social leveller that empowers individuals and improves lives. This, however, does not seem to hold true in increasingly stratified developed countries, where the presence of generational wealth is a critical determinant of academic success. In Singapore, which claims to uphold meritocracy, children from more affluent family backgrounds grossly outperform those who come from humbler backgrounds, primarily because affluent parents pass on advantages such as better learning resources and additional help like enrichment classes to their offspring. A research study conducted in 2016 found that nearly 41% of students in schools which offer the prestigious Integrated Programme were from families with a monthly household income of at least $10,000. Conversely, only 7% had similar backgrounds in government schools which did not offer the programme.  Students in the Integrated Programme enjoy opportunities and resources which their peers in government schools do not have access to, such as leadership programmes and education and career guidance mentorship. Given that the education system ultimately feeds into the job market, particularly in Singapore, the differences in access to educational opportunities since young inevitably result in severely hampered social mobility. 

In summary, education can act as a catalyst to solve problems like poverty and discrimination. However, education is not the panacea to all the problems of the modern world because of the fact that there are people who cannot afford education; because of the multi-dimensional and multi-faceted nature of today’s challenges; and the inherent limitations unique to education. Ultimately, education can make the hopeless image of our future more vibrant and colourful, but that image will still be left incomplete if other aspects of society do not reform and complement education.