Fall 2007 Outline
This class is being developed based on the course
User-Adaptive Systems and Intelligent Learning Environments by
Cristina Conati at UBC in Winter 2003-2004, and on the
Intelligent Tutoring Systems course taught by Neil Heffernan
AAAI's introduction to Intelligent Tutoring Systems. In particular:
- Eric Thomas's brief intro to
Intelligent Tutoring Systems
Applications of AI in Education
By Joseph Beck, Mia Stern, and Erik Haugsjaa. ACM Crossroads (student
magazine of the Association for Computing Machinery), 1996.
- See Bloom for a discussion of
tutoring as the most effective teaching method:
- Bloom, BS, "The 2 Sigma problem: The Search for Methods of
Group Instruction as
Effective as One-to-One Tutoring"  Educational Researcher 4-16.
How to Read a Research Paper, by Cristina Conati, 2000.
||Adaptive Support to Learning:
Model Tracing Coaches
- Anderson, J. R., Corbett, A. T., Koedinger,
K. R., & Pelletier, R. (1995).
Tutors: Lessons Learned. The Journal of the Learning Sciences
, 4(2), 167-207. Barnes slides
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark,
M. A. (1995).
Intelligent tutoring goes to school in the big city.
International Journal of Artificial Intelligence in
Education (1997), 8,30-43
(until p. 38, section 3 excluded. Reading the additionl
5 pages is highly recommended, but not required),
||Educational Data Mining Methods for Knowledge and Model Tracing
Barnes, T., & D. Bitzer,
Fault tolerant teaching and automated knowledge assessment.
Proceedings of the 40th Annual ACM Southeast Conference
(ACMSE'02), Raleigh, NC, April 27, 2002, pp. 125-132,
- Barnes, T. & J. Stamper, Toward the extraction of production rules for
solving logic proofs. In the Educational
Data Mining Workshop held at the
13th Conference on Artificial Intelligence in Education. Los Angeles. pp. 11-20,
- Discuss logic proof writing tutorials and data:
- Optional: My Discrete Math notes lectures are available online
(each lecture is 75 minutes):
Class intro & logic
Logical Equivalences, Implications
Formal Logic & Circuits
Formal Logic & Circuits
Compilation of Logic Software and Educational Tools
by Hans van Ditmarsch
||Using Think-Alouds to understand student thinking
Optional Further Background Reading:
- Koedinger, K.R., & Anderson, J.R. (1993a). Reifying implicit planning in geometry: Guidelines for
model-based intelligent tutoring system design. In Lajoie, S., & Derry, S. (Eds.) Hillsdale, NJ:
Koedinger, K. R., Aleven, V., Heffernan. T., McLaren, B. &
Hockenberry, M. (2004) Opening the Door to Non-Programmers: Authoring
Intelligent Tutor Behavior by Demonstration. Proceedings of 7th Annual
Intelligent Tutoring Systems Conference, Maceio, Brazil. page162-173.
- Cognitive Tutor Authoring Tool online
- Erickson and Simon.
Verbal Reports as Data.
- Gertner, A., Conati, C., & VanLehn, K. (1998). Procedural help in Andes:
Generating hints using a Bayesian network student model (pp. 106-111),
In Proceedings of the 15th national Conference on Artificial Intelligence,
Cambridge, MA: The MIT Press. [8 pgs.]
- Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.
Conati, Abigail S. Gertner, Kurt VanLehn, Marek J. Druzdzel (1997)
On-Line Student Modeling for Coached Problem Solving Using Bayesian
Networks In Anthony Jameson, Cécile Paris, and Carlo Tasso (Eds.), User
Modeling: Proceedings of the Sixth International Conference,UM97.
Vienna, New York: Springer Wien New York. © CISM, 1997. Available
online from http://um.org, or http://citeseer.nj.nec.com/conati97line.html
- Chabay, R. W., & Sherwood, B. A. (1992). A practical guide for the creation of educational software.
In Larkin, J. H. and Chabay, R. W. (Eds.), Computer-Assisted Instruction and Intelligent Tutoring Systems:
Shared Goals and Complementary Approaches. Hillsdale, NJ: Lawrence Erlbaum Associates.
V. J., & Psotka, J. (1996). Intelligent tutoring systems: Past,
Present and Future. In D. Jonassen (Ed.), Handbook of Research on
Educational Communications and Technology : Scholastic Publications.
[80 pages] - For a wider approach to ITS. See Slides
by Cristina Conati.
- Eberts, R. E. (1997). Computer-based instruction. In Helander, M. G., Landauer, T. K., & Prabhu, P. V. (Ed.s)
Handbook of Human-Computer Interaction, (pp. 825-847). Amsterdam, The Netherlands: Elsevier Science B. V.
- Wenger, E. (1987). Artificial intelligence and tutoring systems: Computational and cognitive approaches to the communication
of knowledge. Los Altos, CA: Morgan Kaufmann Publishers. Especially Chapter 1 and 2.
- Sleeman, D. H., & Brown, J. S. (1982). Intelligent Tutoring Systems. New York, NY: Academic Press.
M. S., Bransford, J. D., & Pellegrino, J.W. (1999). How people
learn: Bridging research and practice. Washington, D.C.: National
Academy Press. Chapter 1, 10 and 11.
- Bloom, B. S. (1984). The 2 sigma problem:
The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13, 4-16. [13 pgs.]
|09/24/07||Historical Background & Cognitive Modeling
- VanLehn, K. (2006).
The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in
Education. 16, pages not determined yet.
- du Boulay, Benedict (2006)
Commentary on Kurt VanLehn's The behaviour of tutoring systems.
International Journal of Artificial Intelligence in Education, 16 (3). pp. 267-270.
- Burton, R. R., & Brown, J. S. (1982). An
investigation of computer coaching for informal learning activities (pp.
79-98). In D. Sleeman and J. S. Brown (Ed.),
Intelligent Tutoring Systems. New York: Academic Press. [20 pgs.]
K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby,
L., Treacy, D., Weinstein, A., and Wintersgill, M. (2005). The
Andes Physics Tutoring System: Lessons Learned. International
Journal of Artificial Intelligence and Education, 15 (3).
Ritter, F. & Feurzeig, W. (1988). Teaching real-time
tactical thinking (pp. 285-301). In J. Psotka, L. D. Massey &
S. A. Mutter (Eds.) Intelligent Tutoring Systems:
Lessons Learned. Hillsdale, NJ: Erlbaum.
- Anderson,J. R. (1993). Rules of the mind. Hillsdale, NJ.
Parts to read: Chapter 1 (pages 1-10) “Production Systems and the
ACT-R Theory” and Chapter 2 (pages 17-20, 25-44) Knowledge Representation.
|Cognitive Modeling: Learning & Transfer
- Collins, A., Brown, J. S., & Newman, S.E.(1989).
Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics.
In L. B. Resnick (Ed.), Knowing, learning,
and instruction: Essays in honor of Robert Glaser.Hillsdale,NJ: Lawrence
- Hao Cen, Kenneth Koedinger, and Brian Junker.
Automating Cognitive Model Improvement by A*Search and Logistic Regression. In the AAAI
2005 Workshop on Educational
|ITS Design Principles
- Koedinger, K. R. (2002). Toward evidence for
instructional design principles: Examples
from Cognitive Tutor Math 6. Invited paper in Proceedings of PME-NA XXXIII
(the North American Chapter of the International Group for the Psychology of
D. C., & Reiser, B. J. (1994). Scaffolding effective problem
solving strategies in interactive learning environments. In A. Ram
& K. Eiselt (Eds.), Proceedings of the Sixteenth Annual Conference
of the Cognitive Science Society (pp. 629-634). Hillsdale, NJ: Erlbaum.
[5 pgs.][Handed out in class]
- Dugdale (1992). In Larkin, J. H. and Chabay, R. W. (Eds.),
Computer-Assisted Instruction and Intelligent Tutoring Systems: Shared Goals and
Complementary Approaches. Hillsdale, NJ: Lawrence Erlbaum Associates.
- Chabay, R. W., & Sherwood, B. A. (1992). A practical guide for the
creation of educational software. In Larkin, J. H. and Chabay, R. W. (Eds.),
Computer-Assisted Instruction and Intelligent Tutoring Systems:
Shared Goals and Complementary Approaches. Hillsdale, NJ:
Lawrence Erlbaum Associates.
D. C. & Reiser, B. J. (1993). Scaffolding the acquisition of
complex skills with reasoning-congruent learning environments. In
Proceedings of the Workshop in Graphical Representations, Reasoning and
Communication from the World Conference on Artificial Intelligence in
Education. 9-15. Edinburgh, Scotland: The University of Edinburgh.
|Cognitive Mastery Learning and Knowledge Tracing
Optional additional reading:
- Albert T. Corbett and Akshat Bhatnagar. Student modeling in the
ACT programming tutor: Adjusting a procedural learning model with
declarative knowledge. In Anthony Jameson, Ccile Paris, and Carlo
Tasso, editors, User Modeling: Proceedings of the Sixth International
Conference, UM97, pages 243--254. Springer, Vienna, New York, 1997.
Available from http://www.um.org and http://citeseer.ist.psu.edu/corbett97student.html
- Peter Pirolli, Mark Wilson (1998). A
Theory of the Measurement of Knowledge Content, Access, and Learning.
|Difficulty Factor Assessments
|Constraint Based Modeling
Suraweera, P. & Mitrovic, A. (2002) KERMIT: a Constraint-based Tutor for Database Modeling. in Intelligent Tutoring Systems 2002
T. (1999). Authoring intelligent tutoring systems: An analysis of the
state of the art. International Journal of Artificial Intelligence in
Education, 10, pp. 98-129. (right-click and "save target to" disk)
- Moreno, R., & Mayer, R. E. (2007). Interactive multimodal
learning environments. Educational Psychology Review, 19, 309-326. Get
it by searching for the EPR at library.uncc.edu.
- Moreno, R. (2006). Does the modality principle hold for different
media? A test of the method affects learning hypothesis. Journal of
Computer Assisted Learning. Get it by searching for the JCAL at
- Munro, A. (1994). RIDES Authoring Reference. Behavioral Technology Laboratories, USC (http://btl.usc.edu/rides/)
||Learning Styles & HCI
- Compare this learning style system to the ones in the Hermann and 4MAT
- How do we incorporate material for each kind of learner in an
- What are some ways we can adapt to learners in ITSs?
- How do we incorporate Norman's Design principles into ITS design?
- Howard Gardner, Multiple Intelligences: The Theory in
Practice. Chapter 1. New York: Basic Books, 1993.
Robert Ennis, "A Taxonomy of Critical Thinking Dispositions
and Abilities," in Teaching Thinking Skills.
Robert Stermberg, ed. New York: WH Freeman and Company, 1987.
Bernice McCarthy, The 4MAT System.
Barrington, IL: EXCEL, Inc., 1987.
||Adaptive Support to Learning: Student Modeling
VanLehn. K.(1988). Student Modeling. In M.C. Polson and
Foundations of Intelligent Tutoring Systems, (pp55-78).
- Self. , J. Bypassing the intractable problem of student
modeling. In C. Frasson and G. Gauthier (eds.).
Intelligent tutoring systems: at the
crossroad of artificial intelligence and education
Norwood, NJ: Ablex Publishing Corporation, Barnes slides
Conati C., Gertner A., VanLehn K. (2002).
Networks to Manage Uncertainty in Student Modeling.
User Modeling and User-Adapted Interaction. 12(4), Conati Slides,
|TBD||Pedagogical Agents & JESS
Production rule designs for logic proofs,
constructed using OmniGraffle:
Rete algorithm: How Jess works.
- Intro to Jess: The Java Expert System Shell by Federico Cabitza, available online
- Baylor, A.L. and Kim, Y. (2005). Simulating Instructional Roles through Pedagogical Agents. IJAIED, 15, 95-115.
- Johnson, W.L., J. Rickel, & J. Lester. (2000).
pedagogical agents: Face-to-face interaction in
interactive learning environments. Intl. Journal
of Artificial Intelligence in Education, 11, 47-78.
- Murray, R.C., VanLehn, K. & Mostow, J. (2001). A decision-theoretic approach for selecting tutorial discourse actions.
In E. Horvitz, T. Paek & C. Thompson (Eds.), Proceedings of the
NAACL Workshop on Adaptation in Dialogue Systems, Pittsburgh, PA, 4
June 2001, pp. 41-48. New Brunswick, NJ: Association for Computational