Computer Supported Collaborative Learning
Course Number: 05-899 A
Day/Time: MonWed 1:30-2:50
Location: Porter Hall A19C
Units: 12
Books: None
Instructors:
Dr. Carolyn P. Rosé (LTI-HCII)
cprose@cs.cmu.edu
NSH 4531
Office Hours: By appointment
Dr. Susan Finger (CEE)
sfinger@ri.cmu.edu
Porter Hall 123B
Office Hours: By appointment
Prerequisites: None. Some familiarity with educational technology, linguistics, or machine
learning would be beneficial, but not required.
Software: TagHelper Tools http://www.cs.cmu.edu/~cprose/TagHelper.html
Course Description
The field of Computer Supported Collaborative Learning has as one of its foundational goals to
work towards understanding the pedagogical and technological features that make on-line
education in general, and collaborative learning in particular, effective. If we can understand the
causal connections between interaction and learning, then we can wield technology in ways that
achieve maximal cognitive and social benefits for on-line learners.
The purpose of this class is to expose students to the foundational theoretical and methodological
issues underlying previous work in collaborative learning, to introduce students to the wide range
of current approaches to collaborative learning support that exist within the field of Computer
Supported Collaborative Learning, and to offer students a vision of where the field is going
through review of recent articles as well as hands on experience with new technologies.
The field of Computer Supported Collaborative Learning is changing. Machine learning and text
processing technologies bring the potential to adapt support offered to students to the specific
needs that arise during their group interactions. Whereas the state of the art in collaborative
learning support is primarily composed of static, one-size-fits-all approaches, the ideal of
adaptive collaboration support is now seen as within our grasp. Nevertheless, important research
questions must be addressed, both on the technical side of extending and insightfully applying
existing technology that was originally developed for different purposes to this new research
area, and on the behavioral side of investigating the effect of alternative strategies and
approaches to responding to the events that are detected using that technology.
The course will be structured primarily around group discussions of weekly reading assignments
as well as a major term project in which students will work in small groups to design and
prototype a form of adaptive collaborative learning support.
Assignments
I. Each student will be responsible for leading the discussion for at least two class sessions. This
involves both offering a concise presentation at the beginning of class that outlines the key points
of the readings for the day (20-30 minutes) and moderating the class discussion.
II. Write a 1-2 page response to posted discussion questions each week before class, submitted to
the course Kiva as well as printed out and brought to class for the student’s reference during the
class discussion.
III. Major Project: Work in groups of 2 or 3 to design and prototype a form of adaptive
collaborative learning support. Below are individual assignments that are meant to cumulatively
result in the completion of the term project. The purpose of the project is to give students
experience with each part of the process of designing and prototyping this type of intervention
with the understanding that there is not sufficient time to perfect each step along the way.
(a) Identify an issue of interest and review at least 5 related articles (Due at the end of
week 5)
(b) Write a detailed critique of one article from (a) that describes a study addressing
issues related to the problem you want to address, then design a similar study addressing
more specifically the issue you selected for your term project and collect at least 1
session worth of data for each condition (Due at the end of week 7)
(d) Design a process analysis coding scheme related to your design (based on coding
schemes we will discuss in class), develop a coding manual, assess inter-rater reliability
within your group (Due at the end of week 9)
(c) Brainstorm about alternative designs for an adaptive support mechanism based on
observations in the collected and coded data (Due at the end of week 10)
(e) Prototype a simple automatic analysis method using the Weka toolkit (Due at the end
of week 12)
(f) Prototype an intervention, triggered by the automatic analysis approach developed in
(e) (Due at the end of week 15). Projects will be presented in a poster session during
Finals Week.
Grading
There will be no exams. The term project and its components (a-f above) are 70% of the grade.
In-class presentations are 20% of the grade, and classroom participation (including online
responses to other's postings) are 10% of the grade.
Syllabus
Week 1 Course Intro
Jan 17
Stahl, G., Koschmann, T., Suthers, D. (2006). Computer-supported collaborative learning: An historical
perspective. Cambridge Handbook of the Learning Sciences. Cambridge, UK: Cambridge University
Press
Week 2 Example from Problem-Based Learning: Towards Supporting Engineering Design Project
Based Learning
Jan 22
Hmelo-Silver, C. E. (2004). Problem-Based Learning: What and How Do Students Learn? Educational
Psychology Review, 16(3), pp235-266.
Hmelo-Silver, C. E. & Barrows, H. S. (2006). Goals and Strategies of a Problem-based Learning
Facilitator. The Interdisciplinary Journal of Problem Based Learning, 1(1), pp 21-39.
Hmelo-Silver, C. E. (2003). Analyzing collaborative knowledge construction: multiple methods for
integrated understanding, Computers and Education, 41, pp 397-420.
Jan 24
Rosé, C. P., Gweon, G., Arguello, J., Finger, S., Smailagic, A., Siewiorek, D. (submitted). Towards and
Interactive Assessment Framework for Engineering Design Project Based Learning, submitted to CSCL
2007.
Hmelo-Silver, C. E. (2002). Collaborative Ways of Knowing: Issues in Facilitation. In G. Stahl (ed.)
Proceedings of CSCL 2002 (pp. 199-208). Hillsdale, NJ: Erlbaum.
* Guest presentation from Gahgene Gweon
Week 3-4 Cognitive and Social Foundations of Collaborative Learning
Jan 29
De Lisi, R. & Golbeck, S. L. (1999). Implications of Piagetian Theory for Peer Learning, in O'Donnell &
King (Eds.) Cognitive Perspectives on Peer Learning, Lawrence Erlbaum Associates: New Jersey.
Jan 31
Hogan, D. M. & Tudge, R. H. (1999). Implications of Vygotsky’s Theory for Peer Learning, in O'Donnell
& King (Eds.) Cognitive Perspectives on Peer Learning, Lawrence Erlbaum Associates: New Jersey.
Feb 5
King, A. (1999). Discourse Patterns for Mediating Peer Learning, in O'Donnell & King (Eds.) Cognitive
Perspectives on Peer Learning, Lawrence Erlbaum Associates: New Jersey.
Feb 7
Suthers, D. (2006). Technology affordances for inter-subjective meaning making: A research agenda for
CSCL. International Journal of Computer Supported Collaborative Learning, 1:315-337.
Week 5-6 Techniques for Studying Collaborative Learning
Reference for experimental design issues:
Kerlinger, F & Lee, H. (2000). Foundations of Behavioral Research, Harcourt College Publishers, Fort
Worth, TX. Chapters 18, 19, 28
Reference for protocol analysis:
Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. The Journal of
the Learning Sciences, 63), 271-315.
Feb 12
Slavin, R. (1980). Cooperative Learning. Review of Educational Research 50(2), 99315-342.
Feb 14
Meier, A., Spada, H., Rummel, N. (submitted). A Rating Scheme for Assessing the Quality of ComputerSupported Collaboration Processes, Submitted to the International Journal of Computer Supported
Collaborative Learning
Sampson, V. & Clark, D. (2006). Assessment of Argumentation in Science Education: A Critical Review
of the Literature. Proceedings of the International Conference of the Learning Sciences.
Feb 19
Li, J. (2003). Exploring Collaborative Discovery, PhD thesis, Dept. of Psychology, Carnegie Mellon
University, Chapter 3.
Teasley, S. (1995). The Role of Talk in Children’s Peer Collaborations, Developmental Psychology
31(2), pp 207-220.
Feb 21
Strijbos, J. W. (2004). The effect of roles on computer supported collaborative learning, Open
Universiteit Nederland, Heerlen, The Netherlands (Chapters 3 and 4)
Week 7-8 Issues and Problems
Feb 26 – Process Losses
Wang, H. C., Rosé, C.P., Cui, Y., Chang, C. Y, Huang, C. C., Li, T. Y. (2007). Thinking Hard Together:
The Long and Short of Collaborative Idea Generation for Scientific Inquiry, submitted to CSCL 2007.
Brown, V. R., & Paulus, P. B. (2002). Making group brainstorming more effective: recommendations
from an associative memory perspective. Current Directions in Psychological Science. 11(6), 208-212.
Feb 28 – Trouble with Explanation Depth
Webb, N., Nemer, K., & Zuniga, S. (2002). Short Circuits or Superconductors? Effects of Group
Composition on High Achieving Students’ Science Assessment Performance, American Educational
Research Journal 39(4), pp943-989.
March 5 – Racial Stereotypes
Elbers, E., De Hann, M. (2004). Dialogic Learning in the Multi-Ethnic Classroom. Dialogic Learning:
Shifting Perspectives to learning, instruction and teaching, Kluwer Academic Publishers.
March 7 – Gender Stereotypes
Ten Dam, G., Voman, M. & Wardekker, W. (2004). Making sense through participation: Social
Differences in Learning and Identity Development. Dialogic Learning: Shifting Perspectives to learning,
instruction and teaching, Kluwer Academic Publishers.
Gweon, G., Rosé,C. P., Albright, E., Cui, Y. (submitted). Evaluating the Effect of Feedback from a
CSCL Problem Solving Environment on Learning, Interaction, and Perceived Interdependence, submitted
to CSCL 2007.
March 12-March 18 Spring Break
Week 9-10 Static Forms of Collaborative Learning Support
March 19 – Script Based Support
O’Donnell, A. M. (1999). Structuring dyadic interaction through scripted cooperation. In O’Donnell, A.
M., and King, A. (Eds.), Cognitive perspectives on peer learning, Erlbaum, Mahwah, NJ, pp. 179-196.
Kollar, I., Fischer, F. & Hesse, F. (2003). Cooperation scripts for computer-supported collaborative
learning. In B. Wasson, R. Baggetun, U. Hoppe, & S. Ludvigsen (Eds.), Proceedings of the International
Conference on Computer Support for Collaborative Learning - CSCL 2003, COMMUNITY EVENTS Communication and Interaction (pp. 59-61). Bergen, NO: InterMedia.
March 21- Structured Interfaces
Robertson, J., Good, J., Pain, H. (1998). BetterBlether: The design and evaluation of a discussion tool for
education. International Journal of Artificial Intelligence in Education, 9.
Baker, M., & Lund, K. (1997). Promoting reflective interactions in a CSCL environment. Journal of
Computer Assisted Learning, 13, 175-193.
March 26 – Learning to Collaborate
Webb, N. & Farivar, S. (1999). Developing Productive Group Interaction, in O'Donnell & King (Eds.)
Cognitive Perspectives on Peer Learning, Lawrence Erlbaum Associates: New Jersey.
Rummel, N., Spada, H. & Hauser, S. (2006). Learning to collaborate in a computer-mediated setting:
Observing a model beats learning from being scripted. In S. Barab, D. Hickey & K. Hay (Eds.)
Proceedings of the Seventh International Conference of the Learning Sciences. Mahwah, NJ: Lawrence
Erlbaum Associates.
March 28 – Roles and Prompts
Weinberger, A. & Fischer, F. (in press). A framework to analyze argumentative knowledge construction
in computer-supported collaborative learning. Computers & Education.
Stegmann, K., Weinberger, A., Fischer, F., & Mandl, H. (2004). Scripting Argumentation in computersupported learning environments. In P. Gerjets, P. A. Kirschner, J. Elen & R. Joiner (Eds.), Instructional
design for effective and enjoyable computer- supported learning. Proceedings of the first joint meeting of
the EARLI SIGs Instructional Design and Learning and Instruction with Computers (CD-ROM) (pp. 320330). Tuebingen: Knowledge Media Research Center.
Week 11-12 Tools and Techniques for Automatic Collaborative Learning Process Analysis
April 2
Donmez, P., Rosé, C. P., Stegmann, K., Weinberger, A., and Fischer, F. (2005). Supporting CSCL with
Automatic Corpus Analysis Technology, the Proceedings of Computer Supported Collaborative
Learning.
Wang, Y., Rosé, C. P., Joshi, M., Fischer, F., Weinberger, A., Stegmann, K. (submitted). TagHelper and
Beyond: Evaluating and Addressing Limitations of Isolated Segment Classification for Automatic
Collaborative Learning Process Analysis, Submitted to AIED 2007.
April 4
Chapters 1, 9, and 10 from Witten, I. H. & Frank, E. (2005). Data Mining: Practical Machine Learning
Tools and Techniques, second edition, Elsevier: San Francisco, ISBN 0-12-088407-0
April 9
Goodman, B. A., Linton, F., Gaimari, R. D., Hitzeman, J. M., Ross, H. J., & Zarella, J. (under review).
Using Dialogue Features to Predict Trouble During Collaborative Learning, submitted to the Journal of
User-Modeling and User-Adapted Interaction
Soller, A. L. (2002). A machine learning approach to assessing knowledge sharing during collaborative
learning activities. In G. Stahl (Ed.), Proceedings of Computer Supported Collaborative Learning.
April 11
Hill, A., Dong, A., Agogino, A.M., “Towards computational tools for supporting the reflective team,” AI
in Design 2002, Gero, J. (ed.) Kluwer, 2002, 305-325.
Dong, A., Hill, A., Agogino, A.M., “A document analysis technique for characterizing design team
performance. Journal of Mechanical Design,, 126(3), 2004, 378-385.
Agogino, A., Song, S., Hey, J., “Triangulation of Indicators of Successful Student Design Teams.
International Journal of Engineering Education, to appear.
Week 13-14 The Future of CSCL: Towards Adaptive Collaboration Support
April 16
Soller, A., Mones, A. M., Jermann, P., & Muehlenbrock, M. (2005). From Mirroring to Guiding: A
Review of State of the Art Technology for Supporting Collaborative Learning, International Journal of
Artificial Intelligence in Education
April 18
Kreijns, K. (2004). Sociable CSCL Environments: Social Affordances, sociability, and social presence.
Unpublished doctoral dissertation, Open Universiteit Nederland, Heerlen, The Netherlands (chapters 3-5)
April 23 Gweon, G., Rosé, C. P., Zaiss, Z., & Carey, R. (2006). Providing Support for Adaptive Scripting in an
On-Line Collaborative Learning Environment, Proceedings of CHI 06: ACM conference on human
factors in computer systems. New York: ACM Press.
April 25
Vizcaino, A. & du Boulay, B. (2002). Using a simulated student to repair difficulties in collaborative
learning. In Proceedings of ICCE'2002, New Zealand. IEEE, 2002.
Kumar, R., Rosé, C. P., Wang, Y. C., Joshi, M., Robinson, A. (submitted). Tutorial Dialogue as Adaptive
Collaborative Learning Support, Submitted to AIED 2007.
Week 15 CHI Week, no class, final report due at the end of this week
Finals Week Poster Session