Anne Meier
[Person] [Project]
Anne Meier, Dipl. Psych.
Short Vita
- 1979:
- Born in Münster (Germany).
- 1998-2005:
- Study of Psychology at the University of Freiburg (Germany)
- and (for one year) at the University of Michigan, USA.
- 10/2005:
- Graduation in Psychology from the University of Freiburg
- (Germany). Thesis: "Evaluating Collaboration: A Rating
- Scheme for Assessing the Quality of Net-Based
- Interdisciplinary Collaborative Problem-Solving"
- Since 11/2005:
- PhD student of the VGK with Prof. Spada, Freiburg.
Contact
Phone: ++49 (0) 761 / 203-2421
FAX: ++49 (0) 761 / 203-2496
email: anne.meier@psychologie.uni-freiburg.de
WWW: My homepageUniversität Freiburg
Institut für Psychologie, Abteilung Allgemeine Psychologie
Engelbergerstr. 41
D-79085 Freiburg (Germany)
Ph.D. Project
Topic: Instructional support for computer-supported collaborative problem-solving with shared and unshared information
Supervisors: Prof. Dr. Hans Spada (Freiburg), Prof. Dr. Michael Diehl (Tübingen)
Start of the Ph.D. project: 11/2005
Summary
In general, two heads are better than one in problem-solving. This is due to the fact that each person in a collaborating group holds unique knowledge. Only if this knowledge is pooled and integrated, the co-construction of new, shared knowledge and of advanced problem solutions becomes possible. However, there are at least four problems inherent in group information processing that hinder successful learning and problem-solving. First of all, groups tend to neglect the unique information individual members hold ("unshared knowledge") and instead focus on information that was known to all members from the beginning ("shared information"). Therefore, groups typically choose the inferior solution alternative if shared information points towards a suboptimal decision alternative while the best solution can only be found by integrating shared and unshared information (Stasser & Titus, 1985). Secondly, recalling relevant information is harder in a group setting than in an individual setting, due to the disruption of individual retrieval strategies in the group setting (Finlay, Hitch, & Meudell, 2000). In this way, valuable unshared information may not be recalled and is thus lost. A third challenge for many problem solving groups is to relate pieces of information from various sources to each other in a meaningful way, so that relevant inferences can be drawn and new, more integrated knowledge generated (Fraidin, 2004; Härder, 2003). Finally, group members tend to process information in accordance with their initial preferences and opinions, resulting in biased information pooling which may prevent the group from detecting the best solution to a problem (Greitemeyer & Schulz-Hardt, 2003). While these difficulties are well-studied, it is still an open question how support should be designed in order to overcome them.
The main goal of my PhD-project is to develop instructional support measures with the goal of improving group information processing and ensuring fruitful collaborative problem solving. In my experiment, dyads of university students collaborate via a desktop-videoconferencing system to solve a murder mystery story. This task requires them to generate new knowledge from both shared and unshared information. I selected a very intriguing class of problems originally designed for social psychological research on information processing in small groups. These so-called called "hidden profile" tasks (e.g. Stasser & Titus, 1985) in principle enable collaborators to reach significant synergy effects by pooling their knowledge and learning from one another, but usually result in severe process losses due to the above mentioned tendency of groups to neglect unshared information. For my study, I have developed a type of hidden profile that requires collaborators to draw inferences from both shared and unshared pieces of information in addition to information pooling. With the help of this paradigm, I will be able to study not only the exchange of information, but also the co-construction of new knowledge during discussion.
The process of pooling information and drawing inferences is supported by instructing dyad members to follow four basic rules of joint information processing in their collaboration: (1) pooling information thoroughly and in a systematic way, in order to heighten the chance that unshared information is contributed; (2) engaging in phases of individual recall, in order to ensure undisrupted retrieval of information items from memory; (3) looking for connections between information items, in order to facilitate the drawing of relevant inferences; and finally (4) separating the information gathering phase from the decision making phase, in order to ensure that information is pooled and inferences are drawn in an unbiased fashion. The instructional support is realized as a combination of a collaboration script with a pre-collaboration learning phase.
Collaboration scripts provide an external structure for students’ collaboration by assigning a certain sequence of activities and roles (Kollar, Fischer, & Hesse, to appear). However, scripting collaboration also bears the danger of substantial motivational losses (Dillenbourg, 2002; Rummel, Spada, & Hauser, accepted). Learning from observing a model collaboration and elaborating (i.e. self-explaining) the underlying principles prior to one’s own collaboration, on the other hand, is an effective instructional measure and does not produce such negative motivational effects (Rummel & Spada, 2005; Rummel et al., accepted). However, students may not always be able to directly transfer their observations to their own collaboration. In my study, I therefore use a combination of the two approaches in instructing students to follow the four collaboration rules given above. In a pre-collaboration learning phase, students are presented with a collaboration model together with instructional explanations and self-explanations prompts. Thus, they are given the opportunity to understand why the rules are important, and to integrate them with their previous knowledge and their internal collaboration scripts. During their own collaboration, students are then asked to follow a prescribed sequence of information processing activities. This collaboration script was designed to help students put into practice what they have learned about good collaboration. The effects of the instructional support on collaborative information processing, on solution quality, and on individual learning outcomes will be studied.
References
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.
Finlay, F., Hitch, G. J., & Meudell, P. R. (2000) Mutual inhibition in collective recall: evidence for a retrieval based account. Journal of Experimental Psychology: Learning, memory & Cognition, 26, 1556-1567.
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.
Greitemeyer, T., & Schultz-Hardt, S. (2003). Preference-consistent evaluation of information in the hidden profile paradigm: Beyond group-level explanations for the dominance of shared information in group decisions. Journal of Personality and Social Psychology, 84(2), 322-339.
Härder, J. (2003). Wissenskommunikation mit Desktop-Videokonferenzen: Strukturierungsangebote für den Wissensaustausch und gemeinsame Inferenzen. Doctoral dissertation, Albert-Ludwigs-Universität Freiburg, Germany. Retrieved May 13, 2005, from http://www.freidok.uni-freiburg.de/volltexte/1157
Kollar, I., Fischer, F., & Hesse, F. (to appear). Collaboration scripts – a conceptual analysis. Educational Psychology Review.
Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting problem-solving in computer-mediated settings. The Journal of the Learning Sciences, 14(2), 201-241.
Rummel, N., Spada, H., & Hauser, S. (accepted). Learning to collaborate in a computer-mediated setting: observing a model beats learning from being scripted. Paper accepted for the ICLS 2006 conference.
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, 6, 1467-1478.
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