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Chapter 12 Learning Together Virtually

Chapter 12 Learning Together Virtually. Ruth Colvin Clark & Richard E Mayer E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning Summarized by Roderick Teh LHDT 548: Online Teaching and Evaluation November 17, 2007.

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Chapter 12 Learning Together Virtually

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  1. Chapter 12Learning Together Virtually Ruth Colvin Clark & Richard E Mayer E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning Summarized by Roderick Teh LHDT 548: Online Teaching and Evaluation November 17, 2007

  2. What is Computer-Supported Collaborative Learning (CSCL)? • The initial generations of e-learning were designed for solo learning. • There were few practical options available to integrate multiple learners or instructors into asynchronous self-study e-learning. • The emergence of social software has made synchronous and asynchronous connections practical and easy.

  3. Online Facilities for Social Learning Table 12.1 summarizes common social software and applications in e-learning: • Blogs • Breakout Rooms • Chats • E-mail • Message Boards • Online Conferencing • Wikis

  4. Types of Computer-Supported Collaborative Learning (CSCL) • What do we know about how various approaches to CSCL affect learning and performance? • CSCL refers to collaborative engagements among teams using synchronous and/or asynchronous tool facilities to support an instructional objective. • Other forms of CSCL include KM resources as a repository of community electronic documents.

  5. Individual vs. Group Outcomes • Research studies use different metrics to assess CSCL outcomes. • Individual outcomes measure achievements of each team member. • The metrics include satisfaction ratings, technology usage logs, analysis of participant statements, and learning evaluated by traditional tests or products.

  6. Group outcome metrics include group perceptions of learning, team test scores, team products or decisions, analysis of team dialog, and logs to assess technology use. • Lou, Abrami & d’Apollonia( 2001) found that group performance does not necessarily predict individual performance. • The factors that optimize individual performance are different from those that optimize team performance.

  7. We need to examine the performance metrics cited in claims regarding the effectiveness of CSCL. • Decide whether group performance or individual performance is more relevant to a specific objective. • Workplace performance focus on group outcomes, whereas learning goals suggest a focus on individual performance outcomes.

  8. Factors That Make a Difference • Early CSCL research compared outcomes from various forms of CSCL to outcomes from individual work. • Table 12.2 summarizes some of the elements that can affect outcomes, e.g., technology features, team assignments, performance evaluation plans, and team sizes.

  9. Optimizing Individual Outcomes • Lou, Abrami & d’Apollonia (2001) evaluated over 122 experiments that compared individual and/or group achievements. • The authors discovered that, under optimal conditions, individual learning is better in collaborative compared to individual settings.

  10. Recommendations for Positive Gains • Provide team skills training for people who lack previous collaborative experience. • Use specific collaborative learning structures that ensure team interdependence, and promote individual accountability. • Create teams of heterogeneous pairs that maximize participant involvement. • Use collaborative teams when the learning tasks are relatively near transfer.

  11. Optimizing Group Products from CSCL • When the goal is a performance product, groups can outperform individuals. • Lou, Abrami & d’Apollonia (2001) found that “when working together, the group is capable of doing more than any single member by comparing alternative interpretations and solutions, correcting each other’s misconceptions, and forming a more holistic picture of the problem.”

  12. Group performance can be optimized by: • Assigning challenging tasks that can benefit from the perspectives and expertise of the participant. • Establishing groups to provide sufficient expertise for confronting a difficult task.

  13. Is Problem-Solving Learning Better with CSCL or Solo? • Jonassen, Lee, Yang & Laffey (2005) found that CSCL is best suited to complex ill-defined tasks for which there is no single correct solution, and which can benefit from group collaboration. • Some examples include developing a patient treatment plan, designing a small business website, or troubleshooting a unique equipment failure.

  14. Uribe, Klein & Sullivan (2003) evaluated a learning process to solve ill-defined problems as a result of practice via CSCL compared to solo practice. • The authors compared individual learning of a problem-solving process from pairs solving an assessment problem collaboratively using synchronous chat to individuals solving the assessment problem on their own.

  15. Virtual vs. Face-to-Face Group Decisions • How can group decision making benefit from collaborative technology? • Campbell & Strauss (2006) compared the decisions of teams working face-to-face with decisions made in a collaborative virtual environment. • The decision task involved a fictional homicide investigation with three suspects.

  16. Software Representations to Support Collaborative Work • How can computer interfaces effectively represent and support collaborative work? • Suthers, Vatrapu, Joseph, Dwyer & Medina (2005) evaluated the effectiveness of three different interfaces to summarize and capture collaboration decisions • They compared a traditional discussion board, the graphic representation shown in Fig. 12.4, and a mix of the discussion board and graphic.

  17. Group Roles and Assignments in CSCL • The outcomes in face-to-face team learning assignments are affected by the structure of group process, including role assignments. • Two studies examine the influence of team role assignments on CSCL interactions. • DeWever, Van Winckle & Valcke (2006) evaluated the adaptation of a PBL program using asynchronous case discussions.

  18. The task involved the development of treatment plans for clinical pediatric cases. • There were no direct measures of learning in this study. • The study suggests that discussions will differ depending on assigned roles within a team.

  19. Nussbaum (2005) compared the quality of team arguments using synchronous chat. • The study evaluated the online debate concerning the relationship between watching television and violence in children. • The conclusion is that goals to persuade and generate reasons had the stronger effects, thereby resulting in more argumentation claims.

  20. Team-Building Skills and CSCL Outcomes • Lou, Abrami & d-Apollonia (2001) found that better individual achievement outcomes are associated with better teamwork skills. • Prichard, Bizo & Stratford (2006) studied a year-long face-to-face college course in which trained and untrained teams worked together to accomplish various course assignments. • The authors suggest that team skills may not transfer from one team to another.

  21. The findings revealed that prior team-skills training has produced superior collaborative group work compared with that of students merely placed in unfacilitated groups. • The study focused on face-to-face collaborative learning. • If specific elements of the teamwork training program could be translated into collaborative interfaces that supported those activities, perhaps the benefits of team training could be magnified in a collaborative environment.

  22. Collaborative Structures and CSCL Outcomes • Research suggests that under appropriate conditions students can learn more from collaborative settings than individually. • A structured collaborative assignment is a critical condition for maximizing benefits from group work. • Another condition is accountability for learning of each team member.

  23. Collaborative Group Techniques • Collaborative structures that promote team reliance and foster individual accountability have proven most effective in face-to-face environments. • Two structures used widely in face-to-face collaborative learning environments are structured controversy, and problem-based learning.

  24. Structured Controversy • Wiley & Voss (1999) showed that individual learners assigned to write a pro and con argument learned more than learners asked to write either a narration or a summary. • The deeper processing stimulated by synthesizing opposing aspects of an issue led to increased learning. • Johnson & Johnson (1992) developed a methodology for group argumentation called structured controversy (Fig. 12.5)

  25. Recommendations • Establish a cooperative context for understanding opposing views, followed by a synthesis of perspectives. • Structure groups to include learners of mixed background knowledge and ability. • Provide access to rich and relevant information about the issues. • Ensure social skills to manage conflict. • Focus group interactions on rational arguments.

  26. Final Words on Structured Controversy • Structured controversy can use a combination of asynchronous and synchronous facilities in a CSCL adaptation.

  27. Problem-Based Learning • Several universities have adopted a specialized form of collaborative learning called problem-based learning (PBL). • PBL teams follow a structured process whereby the team reviews a case together, each member works on it individually, and then the team reconvenes to apply the lessons learned from the case.

  28. Case of PBL: University of MaastrichtThe Miserable Life of a Stomach • Clarify unknown terms and concepts. • Define the problem in the case. • Brainstorm to analyze the problem by identifying plausible explanations. • Critique the explanations and work to draft a coherent description of the problem. • Define the learning issues. • Engage in self-directed study to fill gaps. • Meet with the team to share learning and develop a final problem solution.

  29. There is no clear evidence that PBL offers significant learning advantages over traditional instructional approaches. • PBL medical students report more positive attitudes than students using traditional courses.

  30. How can PBL be adapted to CSCL? • Valaitis, Sword, Jones & Hodges (2005) evaluated a PBL lesson for nursing students that used both asynchronous and synchronous chat sessions. • The focus of the lesson was fetal alcohol spectrum disorder (FASD).

  31. CSCL: The Bottom Line • Jonassen, Lee, Yang & Laffey (2005) believe that CSCL will constitute one of the pivotal issues of the next decade. • Under optimal conditions, collaborative learning can result in enhanced outcomes. • Work products and projects can benefit from a collaborative approach.

  32. Optimal conditions for a set of learners, desired outcomes and technology features is likely different from what is appropriate for a different set.

  33. Promote Better Outcomes From Collaborative Environments • Group process structures that foster the accountability and participation of each team member. • Assignment of far-transfer problems to small heterogeneous groups. • Use of synchronous facilities for outcomes that benefit from reflection and independent research.

  34. Use of representational mechanisms to maintain a record of communication, allow for parallel input, encode group agreements, and support anonymity of discussions. • Team-skill training for groups with no previous teamwork experience. • Group assignments and participant roles that promote deeper processing. • Clear guidance and objectives for team processes to avoid extraneous mental processing.

  35. Selected References • Campbell, J., & Stasser, G. (2006). The influence of time and task demonstrability on decision making in computer-mediated and face-to-face groups. Small Groups Research, 37(30), 271-294. • Jonassen, D. H., Lee, C. B., Yang, C-C, & Laffey, J. (2005). The collaboration principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning. New York: Cambridge University Press.

  36. Laboratory for Interactive Learning Technologies: lilt.ics.hawaii.edu/lilt/software/belvedere/index.html • Lou, Y., Abrami, P. C., & d’Apollonia, S. (2001). Small group and individual learning with technology: A meta-analysis. Review of Educational Research, 71(3), 449-521. • 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.

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