The need for considering multilevel analysis in CSCL research-An appeal for the use of more advanced statistical methods

International Journal of Computer-Supported Collaborative Learning

Volumn 3, Issue 1, 2008, Pages 69-84

  Cress, Ulrike ^a  

^a KNOWLEDGE MEDIA RESEARCH CENTER   (Germany)

Author keywords

Hierarchical linear models; Multilevel models; Quantitative analysis for CSCL

Indexed keywords

EID: 38849180416     PISSN: 15561607     EISSN: 15561615     Source Type: Journal    
DOI: 10.1007/s11412-007-9032-2     Document Type: Article

References (32)

1. Bonito, J. A. (2002). The analysis of participation in small groups: Methodological and conceptual issues related to interdependence. Small Group Research, 33, 412-438.
2. Bonito, J. A., & Lambert, B. L. (2005). Information similarity as a moderator of the effect of gender on participation in small groups: A multilevel analysis. Small Group Research, 36, 139-165.
3. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models. Newbury Park, CA: Sage.
4. Burstein, L. (1978). Assessing differences between grouped and individual-level regression coefficients. Sociological Methods & Research, 7, 5-28.
5. Burstein, L. (1980). The analysis of multilevel data in educational research and evaluation. Review of Research in Education, 8, 158-232.
6. Burstein, L., Kim, S. S., & Delandshere, G. (1989). Multilevel investigations of systematically varying slopes: Issues, alternatives, and consequences. In D. Bock (Ed.) Multilevel analysis of educational data (pp. 233-279). San Diego: Academic.
7. Chiu, M. M., & Khoo, L. (2003). Rudeness and status effects during group problem solving: Do they bias evaluations and reduce the likelihood of correct solutions. Journal of Educational Psychology, 95, 506-523.
8. Chiu, M. M., & Khoo, L. (2005). A new method for analyzing sequential processes: Dynamic multilevel modeling. Small Group Research, 36, 600-631.
9. Cress, U. (2005). Ambivalent effect of member portraits in virtual groups. Journal of Computer-Assisted Learning, 21, 281-291.
10. De Wever, B., Van Keer, H., Schellens, T., & Valcke, M. (2007). Applying multilevel modelling to content analysis data: Methodological issues in the study of role assignment in asynchronous discussion groups. Leaning & Instruction, 17, 436-447.
11. Hox, J. J. (2002). Multilevel analysis: techniques and applications. Mahwah, NJ: Lawrence Erlbaum Associates.
12. Hron, A., Hesse, F. W., Cress, U., & Giovis, C. (2000). Implicit and explicit dialogue structuring in virtual learning groups. British Journal of Educational Psychology, 70, 53-64.
13. Kashy, D. A., & Kenny, D. A. (2000). The analysis of data from dyads and groups. In H. T. Reis, & C. M. Judd (Eds.) Handbook of research methods in social and personality psychology. Cambridge, UK: Cambridge University Press.
14. Kenney, D. A., & Judd, C. M. (1986). Consequences of violating the independence assumption in analysis of variance. Psychological Bulletin, 99, 422-431.
15. Kenny, D. A., Kashy, D. A., & Bolger, N. (1998). Data analysis in social psychology. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.) The handbook of social psychology (4th ed., Vol. 1, pp. 233-265). New York: McGraw Hill.
16. Kenny, D. A., Mannetti, L., Pierro, A., Livi, S., & Kashy, D. A. (2002). The statistical analysis of data from small groups. Journal of Personality and Social Psychology, 83, 126-137.
17. Kimmerle, J. & Cress (2008). Group Awareness and Self-Presentation in Computer-Supported Information Exchange. International Journal of Computer-Supported Collaborative Learning DOI 10.1007/s11412-007-9027-z.
18. Kreft, I. (1996). Are multilevel techniques necessary? An overview, including simulation studies. Retrieved March, 20, 2007 from http://www.calstatela.edu/faculty/ikreft/quarterly/quarterly.html.
19. Maas, C. J. M., & Hox, J. (2005). Sufficient samples sizes for multilevel modeling. Methodology, 1, 86-92.
20. Marsh, H. W., & Hau, K. T. (2003). Big-fish-little-pond effect on academic self-concept: A cross-cultural (26-Country) test of the negative effects of academically selective schools. American Psychologist, 58(5), 364-376.
21. McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, 30-46.
22. Paccagnella, O. (2006). Centering or not centering in multilevel models? The role of the group mean and the assessment of group effects. Evaluation Review, 30, 66-85.
23. Piontkowski, U., Keil, W., & Hartmann, J. (2006). Analyseebenen und Dateninterdependenz in der Kleingruppenforschung am Beispiel netzbasierter Wissensintegration. Zeitschrift für Sozialpsychologie, 37, 41-50.
24. Raudenbush, S., & Bryk, A. (2002). Hierarchical linear models: applications and data analysis methods. Thousand Oaks: Sage.
25. Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15, 351-357.
26. Schellens, T., Van Keer, H., & Valcke, M. (2005). The impact of role assignment on knowledge construction in asynchronous discussion groups: A multilevel analysis. Small Group Research, 36, 704-745.
27. Schellens, T., Van Keer, H., Valcke, M., & De Wever, B. (2007). Learning in asynchronous discussion groups: A multilevel approach to study the influence of student, group and task characteristics. Behaviour & Information Technology, 26, 55-71.
28. Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel analysis. London: Sage.
29. Stevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.
30. Strijbos, J. W., & Fischer, F. (2007). Methodological. challenges in collaborative learning research. Learning & Instruction, 17, 389-393.
31. Strijbos, J. W., Martens, R. L., Jochems, W. M. G., & Broers, N. J. (2004). The effect of functional roles on group efficiency: Using multilevel modeling and content analysis to investigate computer-supported collaboration in small groups. Small Group Research, 25, 195-229.
32. Strijbos, J. W., Martens, R. L., Jochems, W. M. G., & Broers, N. J. (2007). The effect of functional roles on perceived group efficiency during computer-supported collaborative learning: a matter of triangulation. Computers in Human Behavior, 23, 353-380.