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Assessing and promoting computer-supported collaborative learning

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Anne Meier

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Assessing and promoting computer-supported collaborative learning

  1. 1. Assessing and promoting computer-supported collaborative learning Anne Meier University of Freiburg, Institute of Psychology [email_address]
  2. 2. <ul><li>Introduction to CSCL (computer-supported collaborative learning) </li></ul><ul><li>Assessing CSCL learning processes </li></ul><ul><li>Supporting CSCL learning processes </li></ul><ul><li>Example study: adaptive support for knowledge co-construction </li></ul>Overview
  3. 3. The CSCL community <ul><li>a short history of CSCL… </li></ul><ul><ul><li>“ seeds” in the 1980s, e.g. 1989 NATO-sponsored workshop “computer-supported collaborative learning” (Maratea, Italy) </li></ul></ul><ul><ul><li>since 1995: bi-annual CSCL conferences </li></ul></ul><ul><ul><li>since 2003: CSCL community part of International Society of the Learning Sciences (ISLS) </li></ul></ul><ul><li>own journal: International Journal of CSCL (ijCSCL) published by Springer since 2006 </li></ul><ul><li>highly interdisciplinary community </li></ul>
  4. 4. Introduction to CSCL <ul><li>CSCL researchers study: </li></ul><ul><ul><li>How people can learn together with the help of computers (Stahl, Koschmann, & Suthers, 2007) </li></ul></ul><ul><ul><li>How technology can facilitate the sharing and creation of knowledge and expertise through peer interaction and group learning processes (Restra & Laferrière, 2007) </li></ul></ul>
  5. 5. <ul><li>advantages/strengths </li></ul><ul><li>challenges/pitfalls </li></ul>What is your experience with (computer-supported) collaborative learning?
  6. 6. <ul><li>Neo-Piagetian perspective </li></ul><ul><ul><li>learning = cognitive restructuring </li></ul></ul><ul><ul><li>resolving socio-cognitive conflict arising from peer collaboration </li></ul></ul><ul><li>Cognitive elaboration perspective </li></ul><ul><ul><li>learning = elaboration and integration of knowledge </li></ul></ul><ul><ul><li>very important: constructing explanations </li></ul></ul><ul><li>Neo-Vygotskian perspective </li></ul><ul><ul><li>learning = appropriation, internalization </li></ul></ul><ul><ul><li>knowledge co-construction; scaffolding and fading </li></ul></ul><ul><li>Situated learning perspective </li></ul><ul><ul><li>learning = increasingly “central” participation in a community of practice </li></ul></ul><ul><ul><li>distributed cognition: persons, tools, symbols, artefacts,… </li></ul></ul>What makes collaborative learning effective? See for example: Cohen, 1994; Dillenbourg et al., 1995; Fischer, 2002; Webb & Palincsar, 1996)
  7. 7. <ul><li>Motivational process loss (e.g. Salomon & Globerson, 1989) </li></ul><ul><ul><li>Free-rider effect (“social loafing”) </li></ul></ul><ul><ul><li>Sucker effect </li></ul></ul><ul><li>Production blocking </li></ul><ul><ul><li>having to wait for others to finish their turn </li></ul></ul><ul><ul><li>e.g. in brainstorming (Diehl & Stroebe, 1987) </li></ul></ul><ul><li>Biased information sampling (e.g. Brodbeck et al., 2007; Stasser & Titus, 1985)) </li></ul><ul><ul><li>neglecting individuals’ unique knowledge </li></ul></ul><ul><ul><li>striving for consensus rather than understanding </li></ul></ul><ul><li> Putting people in a (computer-supported) group does not mean that they will collaborate well! </li></ul>Pitfalls of collaborative learning
  8. 8. <ul><li>Introduction to CSCL (computer-supported collaborative learning) </li></ul><ul><li>Assessing CSCL learning processes </li></ul><ul><ul><li> What characterizes “good” computer-supported collaborative learning? </li></ul></ul><ul><li>Supporting CSCL learning processes </li></ul><ul><li>Example study: adaptive support for knowledge co-construction </li></ul>Overview
  9. 9. Cognitive, social, and affective aspects of collaboration quality in CSCL <ul><li>Communication (Clark & Brennan, 1991) </li></ul><ul><li>Grounding </li></ul><ul><ul><li>adapting utterances to the amount of shared knowledge/ perspective/ experience </li></ul></ul><ul><ul><li>establishing referential identity (e.g. of objects in a shared whiteboard, of previous messages/ contributions) </li></ul></ul><ul><ul><li>establishing a shared terminology </li></ul></ul><ul><li>Conversation management </li></ul><ul><ul><li>initiating conversations </li></ul></ul><ul><ul><li>managing turn-taking </li></ul></ul><ul><ul><li>ensuring that contributions are taken up </li></ul></ul>For additional literature/ references, please see Meier, Spada, & Rummel, 2007
  10. 10. Cognitive, social, and affective aspects of collaboration quality in CSCL <ul><li>Joint information-processing </li></ul><ul><li>Elaborative information-processing </li></ul><ul><ul><li>eliciting and providing elaborated explanations </li></ul></ul><ul><ul><li>using the partner as a resource </li></ul></ul><ul><ul><li>elaborating on partners’ contributions </li></ul></ul><ul><li>Argumentative information-processing </li></ul><ul><ul><li>constructing justified arguments and counterarguments </li></ul></ul><ul><ul><li>engaging in a critical discussion: avoiding an illusion of consensus </li></ul></ul>
  11. 11. Cognitive, social, and affective aspects of collaboration quality in CSCL <ul><li>Coordination (explicit or tacit) (e.g. Malone & Crowstone, 1994) </li></ul><ul><li>Task division </li></ul><ul><ul><li>identifying interdependent subtasks </li></ul></ul><ul><ul><li>blending individual and collaborative work </li></ul></ul><ul><li>Time management </li></ul><ul><ul><li>agreeing on a realistic time schedule </li></ul></ul><ul><ul><li>monitoring the remaining time during the work process </li></ul></ul><ul><li>Resource management </li></ul><ul><ul><li>handling the available tools efficiently </li></ul></ul><ul><ul><li>agreeing on who may use a technical feature at what time </li></ul></ul>
  12. 12. Cognitive, social, and affective aspects of collaboration quality in CSCL <ul><li>Relationship management </li></ul><ul><li>maintaining equal participation </li></ul><ul><ul><li>symmetric or complementary, depending on role structure </li></ul></ul><ul><li>solving conflicts constructively </li></ul><ul><ul><li>epistemic vs. social conflicts </li></ul></ul>
  13. 13. Cognitive, social, and affective aspects of collaboration quality in CSCL <ul><li>Motivation </li></ul><ul><li>individual task orientation </li></ul><ul><ul><li>keeping up a high level of expended effort </li></ul></ul><ul><ul><li>volitional processes: focusing attention, exerting motivation control </li></ul></ul><ul><li>mutual self-regulation </li></ul><ul><ul><li>mutual encouragement </li></ul></ul><ul><ul><li>monitoring performance and giving feedback </li></ul></ul>
  14. 14. Example: Collaboration quality rating-scheme <ul><li>Development </li></ul><ul><ul><li>sample from study on interdisciplinary collaboration : students of psychology and medicine solving complex patient cases (Rummel & Spada, 2005) </li></ul></ul>Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2 , 63-86.
  15. 15. Example: Collaboration quality rating-scheme Control Room Experimental Room I Experimental Room II
  16. 16. Example: Collaboration quality rating-scheme <ul><li>Development </li></ul><ul><ul><li>sample from study on interdisciplinary collaboration : students of psychology and medicine solving complex patient case (Rummel & Spada, 2005) </li></ul></ul><ul><ul><li>data- and theory-driven analyses  5 aspects/ 9 dimensions </li></ul></ul><ul><ul><li>for each dimension: </li></ul></ul><ul><ul><ul><li>collaboration “standard” defined and illustrated in rating handbook </li></ul></ul></ul><ul><ul><ul><li>collaboration quality rated on 5-point scales </li></ul></ul></ul>
  17. 17. Example: Collaboration quality rating-scheme model / script > control model-plus > model Information pooling Task division Time management Technical coordination model > control > script model-plus > model Individual task orientation Quality of joint solution (Rummel, Spada, & Hauser, 2009) Rummel rummele
  18. 18. Example: Collaboration quality rating-scheme <ul><li>adaptation to new CSCL setting (Synergo) (Voyiatzaki et al., 2008) </li></ul><ul><ul><li>descriptive framework valid in this setting as well </li></ul></ul><ul><ul><li>But: changed operationalization of dimensions and re-anchoring of scales necessary </li></ul></ul><ul><ul><li>… .. work in progress: </li></ul></ul><ul><ul><li>providing adaptive feedback to students based on ratings of their collaboration quality </li></ul></ul><ul><ul><li>(Meier, Voyiatzaki, Kahrimanis, Rummel, Spada, Avouris, 2008) </li></ul></ul>
  19. 19. <ul><li>Introduction to CSCL (computer-supported collaborative learning) </li></ul><ul><li>Assessing CSCL learning processes </li></ul><ul><li>Supporting CSCL learning processes </li></ul><ul><ul><li> How can beneficial collaboration processes be facilitated? </li></ul></ul><ul><li>Example study: adaptive support for knowledge co-construction </li></ul>Overview
  20. 20. Supporting CSCL learning processes <ul><li>Earlier approaches: support “around” collaboration </li></ul><ul><li>Collaboration scripts: support during collaboration </li></ul><ul><li>Adaptivity: from fixed to flexible support </li></ul>
  21. 21. Supporting CSCL learning processes <ul><li>Earlier approaches: support “around” collaboration </li></ul><ul><ul><li>Support prior to collaboration, e.g. training for strategic questioning (King, 1991) </li></ul></ul><ul><ul><li>Support after collaboration, e.g. group processing approaches (Yager, Johnson, Johnson, & Snider, 1986) </li></ul></ul><ul><li>Collaboration scripts: support during collaboration </li></ul><ul><li>Adaptivity: from fixed to flexible support </li></ul>after: Diziol & Rummel, accepted
  22. 22. Supporting CSCL learning processes <ul><li>Earlier approaches: support “around” collaboration </li></ul><ul><li>Collaboration scripts: support during collaboration </li></ul><ul><ul><li>provide specific instructions about task-related interaction (Kollar et al., 2006) </li></ul></ul><ul><ul><ul><li>Sequencing work phases </li></ul></ul></ul><ul><ul><ul><li>Distributing roles </li></ul></ul></ul><ul><ul><ul><li>Specifying activities </li></ul></ul></ul><ul><ul><li> goal: enhance cognitive, meta-cognitive and social learning processes </li></ul></ul><ul><li>Adaptivity: from fixed to flexible support </li></ul>after: Diziol & Rummel, accepted
  23. 23. Collaboration Scripts <ul><li>S plit W here I nteraction S hould H appen (SWISH) ( Dillenbourg & Jermann, 2007) </li></ul>Schema Split Compensation mutual regulation cognitive & metacognitive tasks (e.g. recaller & detector) Reciprocal argumentation conflicting opinions (e.g. pro & contra-roles) Conflict exchange of information distribution of knowledge (e.g. expert groups & teams) Jigsaw
  24. 24. Supporting CSCL learning processes <ul><li>Earlier approaches: support “around” collaboration </li></ul><ul><li>Collaboration scripts: support during collaboration </li></ul><ul><li>Adaptivity: from fixed scripts to flexible support </li></ul><ul><ul><li>Danger of “overscripting” collaboration (Dillenbourg, 2002); instead: taking into account students’ prior knowledge and “internal collaboration scripts” </li></ul></ul><ul><ul><li>realizing flexible, adaptive support: </li></ul></ul><ul><ul><ul><li>“ Wizard of Oz” studies </li></ul></ul></ul><ul><ul><ul><li>adaptive feedback based on automated analyses of interaction (e.g. Dönmez et al, 2005) </li></ul></ul></ul>after: Diziol & Rummel, accepted
  25. 25. <ul><li>Introduction to CSCL (computer-supported collaborative learning) </li></ul><ul><li>Assessing CSCL learning processes </li></ul><ul><li>Supporting CSCL learning processes </li></ul><ul><li>Example study: adaptive support for knowledge co-construction </li></ul>Overview
  26. 26. Example: Supporting Collaborative Inferences F - I - R - E ! Figure from: Bauer, K., & Hesse, F. (2006). Von Kopf zu Kopf. [From head to head]. Gerhirn und Geist [Brain & Mind], 5/2006, 34-39.
  27. 27. Example: Supporting Collaborative Inferences Wolfgang‘s fingerprints are on the gun. Wolfgang showed the guns to his guests in the afternoon. A B
  28. 28. Example: Supporting Collaborative Inferences Wolfgang‘s fingerprints are on the gun. Wolfgang showed the guns to his guests in the afternoon. A B
  29. 29. Example: Supporting Collaborative Inferences Wolfgang left his fingerprints on the weapon when he showed it to his guests. A B
  30. 30. Example: Supporting Collaborative Inferences Meier & Spada, 2007 Person B Person A shared individual collaborative Inference type Information distribution ** *
  31. 31. Example: Supporting Collaborative Inferences <ul><li>Why is it so difficult to draw collaborative inferences? </li></ul><ul><li>individual group member holds “unconnected” information </li></ul><ul><ul><li>seen as less relevant and therefore less likely to be brought up during discussion (Fraidin, 2004) </li></ul></ul><ul><li>inference must be drawn on the basis of newly learned information and recalled information </li></ul><ul><ul><li>people tend to focus on old rather than new information (Wittenbaum, Hubbel & Zuckermann, 1999) </li></ul></ul><ul><ul><li>recall vulnerable to disruptions in group discussion (Finlay, Hitch & Meudell, 2000) </li></ul></ul><ul><li>Training Experiment: train collaboration strategies for </li></ul><ul><ul><li>drawing inferences </li></ul></ul><ul><ul><li>pooling “unconnected” information </li></ul></ul><ul><ul><li>taking up new information </li></ul></ul>
  32. 32. Example: Supporting Collaborative Inferences Meier & Spada, 2008 Test task (murder mystery) No Training (n=9 ) Testing phase collaborative reflection ... with inference tutoring tool discussion & solution Training task (medical diagnosis): individual reading phase read text on collaboration strategies Training phase Training Task + Text + Tutoring (n=9) Training Task+ Text (n=9) Training Task (n=9)
  33. 33. Example: Supporting Collaborative Inferences 6 7 5 8 4 2 ... 3 1 inference patient information disease information New Information! ANJA has matching information.
  34. 34. Example: Supporting Collaborative Inferences 6 7 5 8 4 2 ... 3 1 inference patient information disease information Well done! You have drawn an important inference!
  35. 35. Example: Supporting Collaborative Inferences Meier & Spada, 2008 Test task (murder mystery) No Training (n=9 ) Testing phase collaborative reflection ... with inference tutoring tool discussion & solution Training task (medical diagnosis): individual reading phase read text on collaboration strategies Training phase Training Task + Text + Tutoring (n=9) Training Task+ Text (n=9) Training Task (n=9)
  36. 36. Example: Supporting Collaborative Inferences ** ** performance during testing (without tutoring tool) Meier & Spada, 2008
  37. 37. In a nutshell… <ul><li>Introduction to CSCL (computer-supported collaborative learning) </li></ul><ul><ul><li>diverse perspectives on collaborative learning within field of CSCL </li></ul></ul><ul><ul><li>successful collaboration does not occur spontaneously! </li></ul></ul><ul><li>Assessing CSCL learning processes </li></ul><ul><ul><li>focus here was on processes, rather than outcomes or preconditions </li></ul></ul><ul><ul><li>many relevant aspects: communication, information-processing, coordination, relationship management, motivation </li></ul></ul><ul><li>Supporting CSCL learning processes </li></ul><ul><ul><li>collaboration scripts: (computer-)support during collaboration </li></ul></ul><ul><ul><li>moving towards more flexible, more adaptive support </li></ul></ul><ul><li>Example study: adaptive support for knowledge co-construction </li></ul><ul><ul><li>collaborative inferences are important but difficult </li></ul></ul><ul><ul><li>adaptive support yields best training results </li></ul></ul>
  38. 38. Many thanks to the CoEmCo-Team: Hans Spada, Nikol Rummel Dejana Diziol, Sabine Hauser Eva Zerpies, Malte Jansen This work was funded by Thank you for your attention!
  39. 39. <ul><li>Brodbeck, F., Kerschreiter, R., Mojzisch, A., & Schulz-Hardt, S. (2007). Improving group decision making under conditions of distributed knowledge: The information asymmetries model. Academy of Management Review, 32, 459-479. </li></ul><ul><li>Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–148). Washington, DC: American Psychological Association. </li></ul><ul><li>Cohen,E.G.:Restructuring the classroom: Conditions for productive small groups. Review of Educational Research,64,1-35.1994 </li></ul><ul><li>Diehl, M., & Stroebe, W. (1987). Productivity loss in brainstorming groups: Toward the solution of a riddle. Journal of Personality and Social Psychology, 53, 497-509 </li></ul><ul><li>Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In P. A. Kirschner (Ed.), Three worlds of CSCL. Can we support CSCL? (pp. 61-91). Heerlen: Open Universiteit Nederland. </li></ul><ul><li>Dillenbourg, P., Baker, M., Blaye, A., & O’Malley, C. (1995). The evolution of research on collaborative learning. In P. Reimann & H. Spada (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science (pp. 189–211). Oxford: Pergamon.Dillenbourg, P. & Jermann, P. (2007). Designing integrative scripts. In F. Fischer, I. Kollar, H. Mandl &, J. Haake, Scripting computer-supported communication of knowledge. Cognitive, computational, and educational perspectives (pp. 259-288). New York: Springer. </li></ul><ul><li>Diziol, D., & Rummel, N. (to appear). How to design support for collaborative e-learning: A framework of relevant dimensions. In: Ertl, B. (Ed.): E-Collaborative knowledge construction: learning from computer-supported and virtual environments. </li></ul><ul><li>Dönmez, P., Rose, C., Stegmann, K., Weinberger, A., & Fischer, F. (2005). Supporting CSCL with automated corpus analysis technology. In T. Koschmann, D. Suthers, & T. W. Chan (Eds.), Proceedings of the CSCL 2005 (pp. 125–134). Mahwah, NJ: Lawrence Erlbaum Associates.Kollar, I., Fischer, F., & Hesse, F. W. (2006). Collaboration scripts - a conceptual analysis. Educational Psychology Review. Springer. </li></ul><ul><li>Fischer, F. (2002). Gemeinsame Wissenskonstruktion - theoretische und methodologische Aspekte. Psychologische Rundschau, 53 (3), 119-134. </li></ul><ul><li>Fraidin, S. N. (2004). When is one head better than two? Interdependent information in group decision making. Organizational Behavior and Human Decision Processes, 93, 102-113. </li></ul><ul><li>Kollar, I., Fischer, F., & Hesse, F. W. (2006). Collaboration scripts - a conceptual analysis. Educational Psychology Review, 18, 159-185. </li></ul><ul><li>Koschmann, T. (Ed.). (1996). CSCL: Theory and practice of an emerging paradigm. Mahwah, NJ: Lawrence Erlbaum Associates. </li></ul><ul><li>Koschmann, T., Hall, R., & Miyake, N. (Eds.). (2002). CSCL 2: Carrying forward the conversation. Mahwah, NJ: Lawrence Erlbaum Associates. </li></ul><ul><li>Kraut, R. (2003). Applying social psychological theory to the problems of group work. In: J. M. Carroll (ed.), HCI models, theories, and frameworks. Towards a multidisciplinary science (pp. 325-356). Amsterdam: Morgan Kaufmann. </li></ul><ul><li>Malone, T. W., & Crowston, K. (1994). The interdisciplinary study of coordination. ACM Computing </li></ul><ul><li>Meier, A., & Spada, H. (2007). Information pooling and processing in group problem solving: analysis and promotion of collaborative inferences from distributed information. In D. S. McNamara & J. G. Trafton (Eds.), Proceedings of the 29th Annual Cognitive Science Society (pp. 473-479). Austin, TX: Cognitive Science Society. </li></ul><ul><li>Meier, A., & Spada, H. (2008). Promoting the drawing of inferences in collaboration: insights from two experimental studies. Proceedings of the International Conference of the Learning Sciences, Utrecht, The Netherlands, 2008 . </li></ul><ul><li>Meier, A., Spada, H., & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2 , 63-86. </li></ul><ul><li>Meier, A., Voyatzaki, E., Kahrimanis, G., Rummel, N., Spada, H., & Avouris, N. (2008). Teaching students how to improve their collaboration: Assessing collaboration quality and providing adaptive feedback in a CSCL setting. Symposium New Challenges in CSCL: Towards adaptive script support (N. Rummel & A. Weinberger), ICLS 2008, Utrecht, The Netherlands. </li></ul><ul><li>Resta, P. & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19, 65-83. </li></ul><ul><li>Rummel, N., Hauser, S., & Spada, H. (2007). How does net-based interdisciplinary collaboration change with growing domain expertise? In C. A. Chinn, G. Erkens & S. Puntambekar (Eds.), Mice, minds and sociecty. Proceedings of the Computer Supported Collaborative Learning (CSCL) Conference 2007, Vol 8, II (pp. 611-620). International Society of the Learning Sciences, Inc. ISSN 1819-0146 </li></ul><ul><li>Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem-solving in computer-mediated settings. Journal of the Learning Sciences, 14(2), 201-241. </li></ul><ul><li>Rummel, N., Spada, H., & Hauser, S. (2009). Learning to collaborate while being scripted or by observing a model. International Journal of Computer-Supported Collaborative Learning, 4(1), 69-92. </li></ul><ul><li>Salomon, G./Globerson, T.: When teams do not function the way they ought to. Internationnal Journal of Educational Research,11, 623-637. 1989. </li></ul><ul><li>Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. Journal of the Learning Sciences, 3(3), 265-283. </li></ul><ul><li>Stahl, G., Koschmann, T. & Suthers, D. (2007). Computer-supported collaborative learning: An historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409-426). Cambridge, UK: Cambridge University Press. </li></ul><ul><li>Stasser, G. & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48, 1467-1478. </li></ul><ul><li>Voyiatzaki, E., Meier, A., Kahrimanis, G., Rummel, N., Spada, H., & Avouris, N. (2008). Rating the quality of collaboration during networked problem solving activities, Proceedings of the 6th International Conference on Networked Learning, pp. 409-416, Halkidiki, May 2008. </li></ul><ul><li>Webb, N.M., & Palincsar, A.S. (1996). Group processes in the classroom. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 841-873). New York: Macmillan </li></ul><ul><li>Wittenbaum, G., Hubbell, A, & Zuckermann, C. (1999). Mutual enhancement: Toward an understanding of the collective preference for shared information. Journal of Personality and Social Psychology, 77 (5), 967-978. </li></ul>References / Readings
  40. 40. Example: Collaboration quality rating-scheme Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2 , 63-86. <ul><ul><li>Time management </li></ul></ul><ul><ul><li>Information pooling </li></ul></ul><ul><ul><li>Joint information processing </li></ul></ul><ul><ul><li>Reaching consensus </li></ul></ul><ul><ul><li>Sustaining mutual understanding </li></ul></ul><ul><ul><li>Communication </li></ul></ul><ul><ul><li>Task division </li></ul></ul><ul><ul><li>Coordination </li></ul></ul><ul><ul><li>Technical coordination </li></ul></ul><ul><ul><li>Individual task orientation </li></ul></ul><ul><ul><li>Motivation </li></ul></ul><ul><ul><li>Reciprocal interaction </li></ul></ul><ul><ul><li>Relationship management </li></ul></ul><ul><ul><li>Dialog management </li></ul></ul>
  41. 41. Outcomes of collaborative learning <ul><li>When are groups better than individuals? insights from social psychology (Kraut, 2003) </li></ul><ul><li>Aggregation: combining the unique resources of individual group members </li></ul><ul><ul><li>Making use of members’ complementary knowledge, perspectives, skills etc. </li></ul></ul><ul><ul><li>e.g. a cross-functional marketing team making strategic decisions based on members’ complementary expertise </li></ul></ul><ul><li>Synergy: going beyond the resources contributed by group members </li></ul><ul><ul><li>building on each others’ contributions, creating innovative ideas & solutions </li></ul></ul><ul><ul><li>e.g. a product-design team developing a new product </li></ul></ul><ul><li>“ assembly bonus” </li></ul><ul><li>however: groups tend to neglect members’ unique knowledge and focus instead on shared knowledge (Stasser & Titus, 1985) </li></ul>
  42. 42. Measuring the success of computer-supported collaborative learning <ul><li>Individual learning </li></ul><ul><ul><li>types of knowledge and skills </li></ul></ul><ul><ul><ul><li>conceptual vs. procedural </li></ul></ul></ul><ul><ul><ul><li>skills: domain, collaboration, self-regulation, computer-literacy </li></ul></ul></ul><ul><ul><li>level of evaluation: subjective evaluation - retention – transfer </li></ul></ul><ul><li>Group-level learning </li></ul><ul><ul><li>transactive memory, shared mental models </li></ul></ul><ul><ul><li> facilitates future collaboration in the same group </li></ul></ul><ul><li>Interpersonal and motivational outcomes </li></ul><ul><ul><li>trust, liking, friendships,… </li></ul></ul><ul><ul><li>self- and group-efficacy </li></ul></ul><ul><ul><li>interest </li></ul></ul><ul><ul><li> motivation for future collaboration </li></ul></ul>
  43. 43. Measuring the success of computer-supported collaborative learning <ul><li>What characterizes “success” in the TEL-environment you study? How do you assess it? </li></ul>
  44. 44. Assessing collaboration quality cognitive, social, and affective processes process gain: assembly bonus, synergy effects process loss: motivation and coordination problems group size & composition task type technical & informational resources goal structure Group learning, e.g. transactive memory, shared mental models Individual learning - domain knowledge and problem-solving skills - collaboration skills - technical skills Interpersonal & motivational outcomes, e.g. trust, liking, self-efficacy, group-efficacy institutional context Input

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