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Collaborative Learning

Principle · All principles
Evidence · 79 claims (27 for, 48 mixed, 4 against) · 82 studies (19 causal, 15 review, 15 theoretical, 10 quant-synthesis, 10 associational, 9 qualitative, 4 design), q1–q4 · 11 of 82 report an effect size · 73 claims rest on one study

Conditional relationship

For learners who can already take part in the target task, and for goals that gain from explaining, comparing and reconciling ideas (concepts, principles and complex skills more than verbal associations), working jointly on a task, so that each member has to engage with and respond to the others' reasoning, is expected to raise individually measured understanding compared with working alone on the same task. Co-presence is not this relationship. The expectation attaches to what the joint work makes learners do, and it is weakened by three things: an individual measure that the group product stands in for, equal or enthusiastic participation that does not change each member's own understanding, and a delayed check on which shared understanding has not held. The synthesis evidence comes from school and undergraduate classrooms, on general or course achievement, at the end of multi-week programmes. It does not forecast a single session, an adult workplace team, an online group or a particular learner.

Cooperative learning sits inside this relationship. It is its most structured form, in which positive interdependence and individual accountability are built in, and its conditional model concerns that structure against individualistic and competitive arrangements. This page owns the broader question of when joint work of any structure changes what each learner can do, and what to observe when it does not. The collaborative learning pattern describes a reusable design. It has not yet been rewritten against this model.

Fitting the design to a situation

Ask for three facts when the brief omits them: is the target each member's own understanding, a shared product, or collaboration itself?, is the group work synchronous in a room or asynchronous online?, and is this one session or recurring work over several weeks?

If the brief says… Then change… Basis
The goal is understanding of concepts or principles, in a school or undergraduate course running several weeks Put small-group work on tasks that need explaining and comparing alongside instruction, rather than instruction alone; expect a programme-level gain, not one for every learner Collaborative learning improves outcomes [+M]; Small-group learning improves undergraduate STEM achievement [+M]
The target is each member's understanding at a later test After the group task, ask each member alone for the explanation, straight away and again later, on changed wording; do not let the group's answer stand for it Co-construction needs personal construction for stable change [~W]; Equal, mutual engagement did not ensure change [~W]
The goal is a written text Have learners plan, draft or revise together; then set an individual piece to see whether the gain carries to each writer Collaborative writing improves text quality [+M]
Success will be judged by learners' satisfaction or their report that the group worked well Add an individual knowledge check; read the self-report as an observation of the group's process only Aligned problem perceptions predict self-reported, not measured, outcomes [~M]
The setting is online-self-paced or asynchronous online groups Plan the interaction explicitly (shared task, deadlines for responding to each other); do not expect a role or reward scheme alone to raise achievement Structuring interdependence did not change achievement online [~M]; Students rated collaboration worse online [~W]
Group size is open, or groups of four or more share limited equipment or one hands-on procedure Default to pairs or threes; in groups of four or more, rotate who does each step so every member does every step. Expect the gain to shrink as groups grow Effects on critical thinking were largest in groups of 2–3 and fell below ES 0.5 above seven [~M]; Large groups limited individual participation [~W]; in discussion forums, small groups were needed for students to relate deeply to the discussion [~W]
The goal is critical thinking or problem solving Set real, open problems that the group must solve together, with an individual critical-thinking measure; expect a programme-level average with wide spread across studies Collaborative problem solving improves critical thinking (ES 0.82, 36 studies, I² = 86%) [+M]
The group works in a computer-supported environment with a collaboration script Script one or two named activities (coordinating the work, or negotiating while sharing information) rather than prompting every collaborative activity at once; plan the teacher's rounds of the groups as part of the script; judge the script by an individual knowledge measure, because a script that visibly changes the talk may leave learning gains unchanged Scripts targeting coordination, or negotiation with information sharing, gave the largest domain-learning effects; three-way combinations smaller [~M]; Two transactivity scripts each helped, combined they interfered [~W]; Teacher orchestration matters as much as script design [~W]; A script raised partner-evidence integration in a pre-study [+W] but not learning gains in the main study [-W]
Groups will work together over several sessions or weeks Give the first session's opening to agreeing shared goals and common ground before the task itself, and keep a short planning step at the start of later sessions Prolonged early planning facilitated later co-regulation [~W] (two medical-student samples, reported in a discussion article; process outcome only)
Online groups mix students whose first languages differ Keep the groups mixed but support the interaction (time to respond in writing, an agreed glossary for the task; untested), and check members' confidence in taking part online, not only the product Mixed-first-language groups gained slightly less online-interaction self-efficacy (η² = .004) [~W] (associational; a very small difference in self-efficacy, not in learning)
Pairs work remotely through screens on a task that needs pooling what each knows Give each member a view of where the partner is looking or working (shared gaze, live shared editing), and still check each member's learning; these tools are evidenced on the collaboration process, not on what each learner learned Visible gaze feedback increased information pooling [+M]; Real-time shared programming produced joint revision loops absent in individual work [+M]; How well partners model each other emerged through the task and depended on awareness tools [~W]
The task is independent reading (extensive reading) Add regular peer sharing about what each has read, and check that members are reading before relying on it Extensive reading with peer interaction beat reading without it, no reading, or teacher conferences [+M]; Group activities are not a guarantee when students have not read [~W]
Groups are made of strong or high-attaining students Do not assume they will collaborate; watch whether each member's proposals are discussed before being accepted or dismissed, and give feedback on that High-performing groups often failed when they did not take up each other's ideas [~M]
Learners have generative AI tools available during the group work Bound how the AI may be used and check each member's independent work without it; open use was associated with offloading and lower later higher-order thinking, and teachers report groups handing in AI-done work with no real collaboration behind it. Ask each member to say what they contributed and how Open collaboration with AI, offloading and lower independent thinking [-W]; Teachers report "collaborative hollowing" and mistrust from secret AI use [-W] (teachers' perceptions, online higher education)
Pair work might be done with an AI assistant instead of a human partner Keep a human partner where the aim includes collaboration or social presence; if an AI assistant is used, still check each learner's own performance Human pairs reported the most collaboration and social presence, above AI-assisted pairs and individuals [+W] (self-reported perceptions in one quasi-experiment)
An AI agent takes part in the group as a partner Leave the reasoning and the reasoned coordination to the learners (for example, the AI asks and the learners justify), and look at who gives reasons in the transcript; in recorded human-AI problem solving the AI supplied most reasoning and agreement while students mostly invited and regulated Human and AI discourse differ functionally [~M]
The task is open-ended or ill-defined, with young adolescents Start with a well-defined subtask and familiar materials, so that influence in the group rests on reasons rather than on who dominates Well-defined tasks support shared creative influence [~W]
The task is building a concept map or similar diagram Have learners build it with a partner rather than alone Concept mapping with a peer beat mapping alone [+W]
Second-language learners of mixed proficiency do speaking tasks in pairs Pair a stronger with a weaker speaker for tasks meant to produce negotiation of meaning; this is evidence about talk, not about later proficiency Mixed-proficiency dyads negotiate meaning more [~W]
The brief allows only one short session Keep the joint task to one question with an individual answer before and after; do not expect the multi-week effect untested proposal

Observation, state and explanation

Record what happens under stated conditions: the task and whether one person could complete it alone, group size and composition, any roles or scripts, the talk and actions the group produced, and each member's individual response before and after. A group product, a group's report of its own success and a member's satisfaction are observations about the group or about feelings. None of them is an observation of any member's understanding. "Co-constructs", "is engaged", "agrees" and "understands" are inferences. Equal turn-taking can be seen. Whether it changed anyone's thinking cannot.

Response Plausible explanations Observation that could change the interpretation
The group reaches a correct shared explanation; some members later revert to their earlier idea Shared understanding was carried by one member; the member followed the talk but did not reconstruct it personally; the later probe is worded differently from the group task Ask each member individually, straight after the group task and again later, for the explanation on matched and changed wording; record who proposed each step in the group.
Talk is balanced and on task, but individual gains are uneven Participation was equal but not about the same reasoning; members differed in prerequisite knowledge; one member's gain came from explaining, another's loss from deferring Compare each member's pre- and post-task individual response; probe prerequisite knowledge individually; note who explained and who accepted explanations. The speaker who builds an explanation may learn more than the partner who only agrees with it (dominant speaker learns more [~W], a theoretical reading). Equal participation in monitoring predicted the group's later task performance (equality and positive monitoring [~W]), which is not each member's learning.
Members quickly settle on the same answer They were convinced by reasons; they deferred to a partner to agree; they converged on the same sources without weighing them Ask each member for an answer, a confidence rating and a reason alone before and after the exchange; record whether a change followed a reason. Learners changed their assumptions to agree with a partner about twice as often as to disagree (changes more often to agree [~W]), and partners converged strongly in which resources they used (convergence in resource use [~W]).
Members post or report information, but nobody interprets, evaluates or builds on it The task asks for collecting rather than explaining; members assume information explains itself; one member leads while the others work separately Code a sample of the talk or posts for interpretation and building on others' ideas; give a synthesis step that requires reconciling members' contributions. Groups in the wiki's studies mostly shared knowledge rather than constructing or creating it (information shared without interpretation [~W]; no knowledge creation in fixed or opportunistic groups [~W]), and three groups on one task showed a leader-centred, a loosely coordinated and a balanced, regulated form (three collaboration forms [~W]).
Members report a satisfying, successful collaboration Aligned perceptions of the task; real coordinated regulation; general goodwill that inflates every self-report; learning that a knowledge check would also show Set an individual knowledge check beside the self-report; ask each member separately what problems the group met and how it dealt with them.
A member notices the group disagrees but the disagreement is never taken up Uncertainty how to raise it; lower status in the group; no time or task structure for resolving it; the disagreement does not matter to the task Ask the member privately what they would have said; give the group a prompt that requires the disagreement to be stated and settled, and see whether it is. Noticing alone was not associated with better regulation or knowledge (Awareness of heterogeneous problem perceptions does not by itself predict successful regulation [~M]).
A group of capable members fails the task Proposals were dismissed or ignored rather than discussed; one member's idea won on status rather than reasons; the task was beyond the group Record whether each proposal was discussed, by whom, and why it was accepted or dropped (High-performing groups often failed without collaborating [~M]); on an open task, see whether influence followed reasons or dominance (Well-defined tasks support shared creative influence [~M]).
Individual scores rise after collaborative work Peer explanation and comparison; the individual checks and feedback themselves; more time on task; the teacher's monitoring Only a comparison holding the task, checks, time and teaching constant can credit the joint work. Record all of them.

These rows are proposals and have not been tested with learners. A single probe shifts confidence among explanations; it does not identify a cause, and the probe itself is a learning exposure.

Evidence and qualifications

  • Structured collaboration against individualistic instruction [+M]: a meta-analysis of 148 studies of early adolescents associates cooperative goal structures with higher achievement than competitive or individualistic ones (direction only; the abstract gave no magnitude). A meta-analysis of 39 North American undergraduate STEM classroom studies finds small-group work raised achievement over instruction without group work (d = 0.51), with smaller effects where the investigator did not teach (0.41), in single-group pre/post designs (0.30) and a non-significant 0.21 at two-year colleges. Partly checked (1 of 2 entries pass, abstract). The claim page reads it as about structured collaboration, but the undergraduate synthesis compared group work with no group work, not structured with unstructured. It overlaps heavily with the evidence under cooperative learning and does not separate which feature of the joint work matters.
  • Collaborative against individual concept mapping [+W]: an article on the ICAP framework reports, second-hand, a study in which concept mapping with a peer enhanced learning more than concept mapping alone. This is the comparison this page states, with the task held constant. The study's learners, design, outcome and horizon are not reported on the claim page, and it has not been checked against its source.
  • Structuring interdependence in asynchronous online groups [~M]: in a randomised experiment, triads given role, reward, role-plus-reward or no structured interdependence did not differ significantly on an individual posttest (about 71% overall; no effect size printed). Not yet checked against its source. A non-significant difference does not establish equivalence, and the study has no individual-work comparison. Note that the claim's title says adult reentry students while its evidence entry says 280 undergraduate business majors. It predicts that adding a structure to online group work need not change achievement; it does not test collaboration against individual work.
  • Aligned problem perceptions and regulation in online groups [~M]: in a cross-sectional path-modelling study of 311 pre-service teachers in 112 online groups on a single case-analysis task, groups whose members saw their collaboration problems similarly reported higher satisfaction, perceived regulation success and subjective learning gain (β = .31–.57), but homogeneity was unrelated to objectively measured knowledge. There was no pretest, and all the associated outcomes are self-reports. Not yet checked against its source. It limits the model: how well a group feels it worked is not evidence of what its members learned.
  • Personal construction alongside co-construction [~M]: across seven case studies of student dyads in computer-based force-and-motion lessons (learners not described on the claim page), conceptual change visible in the pairs' talk often did not hold when students were probed later. The authors report that it was stable only when shared construction was accompanied by each student's personal sense-making. This is qualitative, with no comparison condition, and it has been checked by the judge (full text). It predicts that the group's talk overstates each member's delayed understanding; it does not say how to bring about personal construction.
  • Equal, mutual engagement and individual change [~M]: from the same study, in two dyads whose on-task engagement was high in equality and mutuality, one student changed substantially and the other did not. Two case dyads, with no effect size, and not yet checked against its source. It predicts that balanced participation is not a sufficient observation of each member's learning.
  • Collaborative problem solving and critical thinking [+M]: a random-effects meta-analysis of 79 effects from 36 experimental and quasi-experimental studies (2000–2021) reports ES = 0.82 (95% CI 0.69–0.95) on students' critical thinking, with very high heterogeneity (I² = 86%). The claim page does not say what the comparison conditions were or how critical thinking was measured, and the synthesis is coded r2. Its group-size subgroups [~M] were ES 0.99 for 2–3 members (17 effects), 0.71 for 4–6 (14), 0.42 for 7–10 (7) and 0.48 above ten (10), with 31 effects not reporting group size. These are between-study subgroups, not a manipulated group size, so they suggest rather than establish that smaller groups gain more.
  • Which activities a collaboration script targets [~M]: in a meta-analysis of computer-supported collaboration scripts, scripts prompting coordination alone (k = 3, g = 0.46) or negotiation with information sharing (k = 4, g = 0.43) raised domain learning, information sharing alone was marginal (g = 0.34), and three-way combinations were smaller (g = 0.20). The cells rest on three or four studies each. It qualifies the model's structure: more scripted activity is not more learning. Two other entries report the same meta-analysis second-hand, as scripts improving domain knowledge and collaboration skills over unstructured computer-supported collaboration (scripts improve learning outcomes [+W]; an editorial's summary [+W]). Its own moderator analysis bears directly on this page's outcome: studies measuring individual outcomes found d = 0.31, those measuring group outcomes d = −0.02 [~W], a difference that was not significant (p = .11) and is exploratory, so it does not show that group measures hide gains, only that the individual-level estimate is the one this page needs. A single wiki-script study shows the gap between process and learning: in a small laboratory pre-study a script made dyads far more likely to integrate the partner's evidence (odds 10.8 times higher [+W]), but in the main study it did not change knowledge gains (d = 0.08, CI −0.39 to 0.56), though both script groups gained (no direct script effect [-W]).
  • Joint against solo practice on the same task, measured individually [+W]: a review reports an experiment in which participants who discussed their confidence with a partner on a perceptual odd-one-out task improved quickly and performed better individually than participants doing the same task without interacting. It is the page's comparison with the task held constant and an individual measure, but it is a perceptual judgement task with adults, reported second-hand with no effect size, so it says little about concepts in a classroom.
  • Human partner, AI-assisted pair or working alone [+W]: in a 234-student programming quasi-experiment, human–human pairs rated collaboration (ηp² = .23) and social presence higher than AI-assisted pairs, who rated them higher than students working alone. These are perceptions; the claim page does not report the programming-performance comparison, so it does not show that human partners raised what each student could do.
  • Dyad composition [~W]: in a secondary-school web-based inquiry study with self-chosen partners, adding the dyads' gender and achievement composition did not improve the model of knowledge acquisition (p = .71). A non-significant result in self-selected pairs; it does not show composition is irrelevant, and the wiki has no study that assigns composition for individual learning.
  • Peer interaction added to extensive reading [+M]: a conference paper reports, second-hand, a pretest-posttest study of 415 US fourth graders randomly assigned to four conditions, in which reading with peer interaction gave larger reading-achievement gains than reading without it, no extensive reading, or reading with teacher conferences; no effect size is printed and it rests on an ERIC document. It is one of the few entries here that holds the task constant and varies only whether learners engage with each other. The same author cautions that peer activities do not help students who have not read [~W].
  • Awareness of disagreement in online groups [~M]: in the 136 members of groups whose problem perceptions differed (from the 311-member study above), recognising the difference was not associated with satisfaction, perceived regulation, subjective learning or measured knowledge; a case example shows a member who saw the disagreement but did not know how to raise it. Associational, r?. It predicts that the group needs a structure for settling disagreement, not only for surfacing it.
  • Process evidence from computer-mediated pairs [+M]: in a 2×2 experiment with 80 students in dyads on a jigsaw explanation task, showing each partner's gaze increased information pooling (ηp² = .55). The claim page reports the process outcome only, not learning. A log study of 13 adult cases (real-time collaborative programming [+M]) found two-way revision loops and joint interface work in shared editing that individual programming did not show; it reports no learning outcome either. Both show that a tool can change how members coordinate; neither shows that it changes what each member can do.
  • Who reasons when an AI is a partner [~M]: across 2,831 dialogue turns of students solving problems with AI agents, the agents produced significantly more reasoning, coordination and agreement moves and the students more invitations, connections and shared regulation (associational, r1, no learning outcome). It qualifies the AI row above: if the AI does the reasoning, the joint work this page credits may not be happening in the learners.
  • Naming perceptual insights during joint construction [+W]: a microgenetic case study of four graduate students building an icosahedron found that insights one member named in speech, gesture and material action became shared terms the group later used to reason formally. A single case, with no comparison, from a JLS article; a mechanism to look for, not evidence of an effect.

Keep each study's learners, task, comparator, setting, duration and outcome when transporting these observations. A pooled d is a programme-level average, not a learner's probability of benefit. Self-reported learning and objectively measured knowledge are different outcomes and should not be read for each other.

The evidence by question

Each question below links a general claim that gathers the studies behind it into one table, one row per distinct study, with each study's design and effect as recorded and no averaged verdict (eval/synthesis/collaborative-learning.json, scripts/synthesize_claim.py). The count is of distinct studies across the claim and the narrower claims that bear on it.

Further evidence, not yet read against this model

Claims this page cites that do not change the model above. Each was read against it on 2026-10-19 (the claims linked since the rewrite, including those from the journal sweep, were read the same day and those that bear on the model moved into it); each note says why it stays here.

Objective and learner-valued goal

Ask what each learner wants from working with others and why, separately from the designer's objective. A learner may value hearing other views, being heard, working with friends, finishing the shared product or avoiding the exposure of working alone. In focus groups, high-school students said group work helped them learn because they heard others' perspectives, and many wanted more of it (students report peer collaboration supports learning [+W]); that is evidence of what learners value, not of what they learned. The designer may want each member to be able to explain the idea independently a week later. These can diverge without anyone noticing, because a pleasant, well-coordinated group can satisfy the learner's goal and still leave the designer's unmet. Record agreement or divergence as an observation, and negotiate the task, the individual checks or the group's purpose when they conflict.

For example, a secondary-school physics student working in a pair at a simulation may value agreeing with her partner and producing a shared answer the teacher accepts. The designer wants each student to predict, a fortnight later and alone, how a moving object behaves when the force on it changes. The pair's agreed answer cannot show that the objective was met. A short individual prediction, agreed in advance, given straight after the task and again later, can. Keeping both aims in view also tells the designer whether the student's own goal is being met.

What would revise this model?

The expectation should weaken if comparable learners doing a task jointly fail to outperform matched learners doing the same task alone, on individually measured, independent outcomes at the horizon that matters. If gains turn out to be carried by the individual checks, feedback, extra time or teacher monitoring rather than by learners engaging with each other's reasoning, the model should credit those components instead. If group self-reports and individual knowledge keep coming apart, as the online-group study above found, treat self-reports as observations of the group's process only. Do not protect the model by relabelling every failure as "not real collaboration" after the fact; record the task and structure in advance.

Group performance during the task, individual understanding straight after it, delayed retention, collaboration skill and satisfaction are separate claims. The present evidence in the wiki does not establish an optimal group size (the one synthesis that breaks effects down by size does so across studies, not by manipulating it), composition (one study with self-chosen pairs found no difference by composition, which is not evidence of none) or script (the script meta-analysis rests on three or four studies per combination, and the one script study here with a learning outcome changed the talk but not the gains), whether coordination tools such as shared gaze change learning rather than process, effects for adult workplace teams or online groups in general, or benefit for every learner in a group.

Claims

  • Conditions for Productive Group Creativity — specializes collaborative learning's general quality-control problem for open-ended creative tasks specifically
  • Peer Discussion — structured talk is one of the main mechanisms through which collaborative learning produces understanding
  • Perspective-Seeking/Multiple Perspectives — collaboration is especially valuable when disagreement and comparison sharpen thinking
  • Social Learning — provides the broader explanation for why interaction can itself be instructional
  • Trialogical Pedagogical Scenarios

Examples

Illustrative

Collaborative Learning — A shared-work pattern in which learners are jointly responsible for meaning-making rather than simply co-located.

Jigsaw Method — Learners build distributed expertise and then teach one another, making interdependence explicit.

Collaborative Inquiry — Groups investigate a question together and synthesize evidence, requiring reasoning to be externalized and coordinated.

Key Sources

  • Johnson, D. W., Johnson, R. T., & Smith, K. A. (2014). Cooperative learning. Journal on Excellence in College Teaching, 25(3-4), 85-118.
  • Webb, N. M. (2009). The teacher’s role in promoting collaborative dialogue in the classroom. British Journal of Educational Psychology, 79(1), 1-28. https://doi.org/10.1348/000709908X380772
  • Loper, Paul. (2000). Chormmunity: Co-Creating Embodied Community. ERIC Document ED443009. https://eric.ed.gov/?id=ED443009
  • Jim Reynolds. (2006). Learning-Centered Learning: A Mindset Shift for Educators. Inquiry, Volume 11, Number 1, Spring 2006, 55-64. http://www.vccaedu.org/inquiry/inquiry-spring2006/i-11-reynolds.html
  • Mercer, N., & Howe, C. (2012). Explaining the dialogic processes of teaching and learning: The value and potential of sociocultural theory. Learning, Culture and Social Interaction, 1(1), 12-21. https://doi.org/10.1016/j.lcsi.2012.03.001
  • Resnick, L. B., Asterhan, C. S. C., & Clarke, S. N. (Eds.). (2015). Socializing intelligence through academic talk and dialogue. AERA. doi:10.3102/978-0-935302-43-1
  • McAndrew, P., Goodyear, P., & Dalziel, J. (2006). Patterns, designs and activities: Unifying descriptions of learning structures. International Journal of Learning Technology, 2(2-3), 216-242. https://doi.org/10.1504/IJLT.2006.010632
  • Biesta, Gert J. J. (1997). George Herbert Mead's Lectures on Philosophy of Education at the University of Chicago (1910-1911). Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL. https://eric.ed.gov/?id=ED422199
  • Reynolds, S., & Camilleri, A. F. (2010). KP-LAB: Breaking New Ground on How to Create Knowledge Through Learning. EDEN 2010 Conference, Valencia.
  • Jacobs, George M. (2000). Reading Alone Together: Enhancing Extensive Reading via Student-Student Cooperation in Second Language Instruction. Paper presented at the Malaysian International Conference on English Language Teaching, Malacca, Malaysia. https://eric.ed.gov/?id=ED444377
  • Xu, E., Wang, W., & Wang, Q. (2023). The effectiveness of collaborative problem solving in promoting students' critical thinking: A meta-analysis based on empirical literature. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-023-01508-1
  • Radkowitsch, A., Vogel, F., & Fischer, F. (2020). Good for learning, bad for motivation? A meta-analysis on the effects of computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning, 15, 5–47. https://doi.org/10.1007/s11412-020-09316-4
  • Hayashi, Y. (2020). Gaze awareness and metacognitive suggestions by a pedagogical conversational agent: an experimental investigation on interventions to support collaborative learning process and performance. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-020-09333-3
  • Hsu, T.-C., Abelson, H., Patton, E., Chen, S.-C., & Chang, H.-N. (2021). Self-efficacy and behavior patterns of learners using a real-time collaboration system developed for group programming. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-021-09357-3
  • Spang, L., Greisel, M., & Kollar, I. (2026). Great minds think alike—how homogeneous problem perceptions are associated with successful regulation in collaborative learning groups. Journal of the Learning Sciences, 35(2), 277-318. https://doi.org/10.1080/10508406.2025.2553543
  • Pierroux, P., Steier, R., & Ludvigsen, S. R. (2022). Group creativity in adolescence: Relational, material and institutional dimensions of creative collaboration. Journal of the Learning Sciences, 31(1), 107-137. https://doi.org/10.1080/10508406.2022.2025813
  • Palatnik, A., & Abrahamson, D. (2026). Building knowledge: The ecological dynamics of co-operative action in collaborative construction of body-scale geometric structures. Journal of the Learning Sciences. https://doi.org/10.1080/10508406.2026.2622059
  • Hao, Z., Liu, X., Fan, J., Long, Y., Yu, J., Chen, W., & Zhang, Y. (2026). Unpacking Interaction Profiles and Strategies in Human-AI Collaborative Problem Solving: A Cognitive Distribution and Regulation Perspective. arXiv. doi:10.48550/arxiv.2603.21288
  • Fusco, J., DiMaria, S., Yeadon, B., Kolodner, J., & Shell, A. (2025). Assessment During Collaborative Learning. Digital Promise. https://doi.org/10.51388/20.500.12265/252
  • Vogel, F., Wecker, C., Kollar, I., & Fischer, F. (2016). Socio-cognitive scaffolding with computer-supported collaboration scripts: A meta-analysis. Educational Psychology Review. https://doi.org/10.1007/s10648-016-9361-7
  • Heimbuch, S., Ollesch, L., & Bodemer, D. (2018). Comparing effects of two collaboration scripts on learning activities for wiki-based environments. University of Duisburg-Essen. https://doi.org/10.1007/s11412-018-9283-0
  • Fan, G., Liu, D., Zhang, R., & Pan, L. (2025). The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance. International Journal of STEM Education. https://doi.org/10.1186/s40594-025-00537-3
  • Raes, A., Schellens, T., & De Wever, B. (2013). Web-based collaborative inquiry to bridge gaps in secondary science education. Journal of the Learning Sciences. https://doi.org/10.1080/10508406.2013.836656
  • Reich-Stiebert, N., Voltmer, J.-B., Raimann, J., & Stürmer, S. (2023). The role of first-language heterogeneity in the acquisition of online interaction self-efficacy in CSCL. International Journal of Computer-Supported Collaborative Learning, 18, 513–530. https://doi.org/10.1007/s11412-023-09411-2
  • Schnaubert, L., Krukowski, S., & Bodemer, D. (2021). Assumptions and confidence of others: the impact of socio-cognitive information on metacognitive self-regulation. Metacognition and Learning. https://doi.org/10.1007/s11409-021-09269-5
  • Haataja, E., Malmberg, J., Dindar, M., & Järvelä, S. (2021). The pivotal role of monitoring for collaborative problem solving seen in interaction, performance, and interpersonal physiology. Metacognition and Learning, 17, 241–268. https://doi.org/10.1007/s11409-021-09279-3
  • Chan, C. K. K. (2012). Co-regulation of learning in computer-supported collaborative learning environments: a discussion. Metacognition and Learning, 7, 63–73. https://doi.org/10.1007/s11409-012-9086-z
  • van Aalst, J. (2009). Distinguishing knowledge-sharing, knowledge-construction, and knowledge-creation discourses. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-009-9069-5
  • Frith, C. D. (2012). The role of metacognition in human social interactions. Philosophical Transactions of the Royal Society B. https://doi.org/10.1098/rstb.2012.0123
  • Baoyi, W., & Khan, F. U. (2026). AI and higher education: teachers' perceptions of students' ethical tensions in online pedagogical methods. Frontiers in Psychology, 17, 1881032. https://doi.org/10.3389/fpsyg.2026.1881032
Page metadata
Field Value
type principle
id collaborative-learning
aliases collaboration-paramount-pedagogy-collectivity, learners-as-learning-resources-principle, create-social-situations-for-meaning, delegate-knowledge-creation-responsibility-to-learners
title Collaborative Learning
description For learners who can take part in the task, working jointly so that each member must engage with the others' reasoning is expected to raise individually measured understanding over working alone on the same task, for goals that gain from explaining and reconciling ideas; co-presence, equal participation or group satisfaction alone are not expected to show it.
status review
moved_from pattern/discussion-based-learning, pattern/literature-circles-rotating-collaborative-roles
canonical True
generated by claude/unspecified on 2026-10-19
trust unverified — no one has confirmed this page's content
sources 8 — webb-2009, loper-2000, jim-reynolds-2006, mercer-2012, mcandrew-2006, biesta-1997, reynolds-2010, jacobs-2000

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