Kurt A. VanLehn

School of Computing, Informatics and Decision Science Engineering (CIDSE)

Arizona State University, Room M1-01, The Brickyard, 699 S. Mill Ave, Tempe, AZ 85287

http://www.public.asu.edu/~kvanlehn

My email is <my first name> <dot> <my last name> <at> asu <dot> edu

480-727-6348

Last Updated: August 8, 2020

Education

B. S. Mathematics, Stanford University, 1974.

M. S. Computer Science, Massachusetts Institute of Technology, 1978.

Ph. D. Computer Science, Massachusetts Institute of Technology, 1983.

Positions

National Science Foundation Graduate Fellow, 1974-1977.

Research Assistant, M.I.T. Artificial Intelligence Laboratory, 1977.

Research Associate, Bolt Beranek and Newman Inc., 1978 (January-October).

Research Associate, Xerox Palo Alto Research Center, November 1978 to August 1985.

Assistant Professor, Depts. of Psychology and Computer Science, Carnegie-Mellon University, September 1985 to August 1990.

Associate Professor, Dept. of Computer Science, University of Pittsburgh, September 1990 to July 1998

Senior Scientist, Learning Research and Development Center, University of Pittsburgh, September 1990 to present.

Co-director, Intelligent Systems Program, University of Pittsburgh, September, 1994 to August, 1996.

Director, Center for Interdisciplinary Research on Constructive Learning Environments (CIRCLE), University of Pittsburgh, January, 1998 to December 2003.

Professor, Department of Computer Science, University of Pittsburgh, July 1998 to August, 2008.

Co-director, Pittsburgh Science of Learning Center (PSLC), September 2004 to August, 2008.

Professor, School of Computing, Informatics and Decision Systems Engineering, Arizona State University, August 2008 to present.

The Diane and Gary Tooker Chair for Effective Education in Science, Technology, Engineering and Math, School of Computing, Informatics and Decision Systems Engineering, Arizona State University, March 2013 to present.

Awards and Honors

National Science Foundation Graduate Fellow, 1974-1977.

Spencer Foundation Research Fellow, October 1986 to August 1988.

Resident Fellow, Center for Philosophy of Science, University of Pittsburgh, 1990 to 2004.

Keynote speaker, Artificial Intelligence in Education, Edinburgh, Scotland, 1993

Best Paper (with Joel Martin), Artificial Intelligence in Education, 1993.

Keynote Speaker, Intelligent Tutoring Systems: 3rd International Conference, Montreal, Canada, 1996.

Fellow, Center for Advanced Study in the Behavioral Sciences, 1996-1997.

Best Paper (with Cristina Conati, Abigail Gertner, & Marek Druzdzel),  UM97: Sixth International Conference on User Modeling, 1997.

Awarded an NSF center (CIRCLE), one of only three awarded in the highly competitive multidisciplinary Learning and Intelligent Systems program. 1997.

Keynote Speaker, European Science Foundation’s final conference on Learning in Humans and Machines, Mannheim, Germany, October, 1997

Best Paper Award (with Cristina Conati). Artificial Intelligence and Education, 1999.

Best Paper Nominee (with R. Charles Murray). Intelligent Tutoring Systems: 5th International Conference, July, 2000.

Identified as individual who has made a significant and positive impact on students’ lives. Commended for positive interaction with students. Spring 2000 survey conducted by Office of Student Affairs, University of Pittsburgh.

Best Paper Nominee (with Carolyn Rosé). Artificial Intelligence in Education, 2001.

James Chen Annual Award for best paper (with C. Conati & A. Gertner) in the 2002 volume of the journal User Modeling and User Adapted Interaction.

Keynote Speaker, UM03: Ninth International Conference on User Modeling, 2003.

Fellow, Cognitive Science Society, elected May, 2003.

Best Paper Award (with C. Lynch, K. Schulze, J. A. Shapiro, R. Shelby, L. Taylor, D. Treacy, A. Weinstein, & M. Wintersgill). Artificial Intelligence and Education Conference, 2005.

Best Student Paper Award (with Michael Ringenberg) Intelligent Tutoring Systems Conference, 2006.

Best Paper Award (with Robert Hausmann), Artificial Intelligence and Education Conference, 2007.

Keynote Speaker, Intelligent Tutoring Systems conference, 2008.

Best Poster Award (with Min Chi), Educational Data Mining Conference, 2008

Best Student Paper Award (with Min Chi), Intelligent Tutoring Systems conference, 2008.

Plenary Speaker, International Conference on Cognitive Modeling, 2010.

Best Student Paper Award (with Min Chi), User Modeling, Adaptation and Personalization conference, 2010.

Best Paper Award (with Min Chi), Intelligent Tutoring Systems conference, 2010.

Keynote Speaker, International Conference on Computers in Education, 2011.

James Chen Award for best paper (with K. Muldner, W. Burlson & B. van de Sande) in the 2011 volume of the journal User Modeling and User Adapted Interaction.

Plenary Speaker, Cognitive Science Conference, 2012.

Honorary Doctorate, Utrecht University, Utrecht, NL, 2015.

Keynote Speaker, The Sixth Computational Behavior Science Summit, Wuhan, China, 2018

Dissertations

VanLehn, K. (1978). Determining the scope of English quantifiers. Cambridge, MA: MIT. Artificial Intelligence laboratory technical report 483. M. S. Dissertation.

VanLehn, K. (1983). Felicity conditions for human skill acquisition: Validating an AI-based theory. Palo Alto, CA: Xerox PARC technical report CIS-21. (Out of print, but available as publication number 9018167 from University Microfilms, Ann Arbor, MI) Ph. D. Dissertation.

Books

VanLehn, K. (1990). Mind bugs: The origins of procedural misconceptions. Cambridge, MA: MIT Press.

VanLehn, K. (1991). (Ed.) Architectures for Intelligence. Hillsdale, NJ: Erlbaum.

Journal articles and papers in stringently reviewed conferences

1980

Brown, J. S., & VanLehn, K. (1980). Repair theory: A generative theory of bugs in procedural skills. Cognitive Science, 4, 379-426. [Abstract & PDF]

1982

VanLehn, K. (1982). Bugs are not enough: An analysis of systematic subtraction errors. Journal of Mathematical Behavior, 3(2), 3-71. [PDF 6 Mb]

1983

VanLehn, K. (1983). Human procedural skill acquisition: Theory, model and psychological validation. In Proceedings of the 1983 Conference of the American Association for Artificial Intelligence (pp. 420-423). Los Altos, CA: Morgan Kaufmann.

VanLehn, K. (1983). Validating a theory of human skill acquisition. In Proceedings of the 1983 International Machine Learning Workshop (p. 234). Urbana: University of Illinois Computer Science Dept.

1984

VanLehn, K. (1984). A critique of the connectionist hypothesis that recognition uses templates, and not rules. In Proceedings of the Sixth Annual Conference of the Cognitive Science Society (pp. 74-81). Hillsdale, NJ: Erlbaum.

1987

VanLehn, K. (1987). Learning one subprocedure per lesson. Artificial Intelligence, 31, 1-40. [Abstract & PDF]

VanLehn, K., & Ball, W. (1987). A version space approach to learning context-free grammars. Machine Learning, 2, 39-74.[Abstract & PDF]

VanLehn, K., & Garlick, S. (1987). Cirrus: an automated protocol analysis tool. In P. Langley (Ed.), Proceedings of the Fourth International Workshop on Machine Learning (pp. 205-217). Los Altos, CA: Morgan Kaufmann. [Abstract & PDF]

1988

Brown, J. S., & VanLehn, K. (1988). Repair theory: A generative theory of bugs in procedural skills. In A. Collins & E. E. Smith (Eds.), Readings in Cognitive Science (pp. 338-361). Los Altos, CA: Morgan Kaufmann. (Reprinted from Cognitive Science, 4, 379-426, 1980).

Gray, W. D., Corbett, A. T., & VanLehn, K. (1988). Planning and implementation errors in algorithm design. In V. Patel (Ed.), Proceedings of the Tenth Annual Conference of the Cognitive Science Society (pp. 594-600). Hillsdale, NJ: Erlbaum.

Kowalski, B., & VanLehn, K. (1988). Cirrus: Inducing subject models from protocol data. In V. Patel (Ed.), Proceedings of the Tenth Annual Conference of the Cognitive Science Society (pp. 623-629). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

1989

VanLehn, K. (1989). Discovering problem solving strategies: What humans do and machines don’t (yet). In A. Segre (Ed.), Proceedings of the Sixth International Workshop on Machine Learning (pp. 215-217). Los Altos, CA: Morgan Kaufmann. [Abstract & PDF]

VanLehn, K. (1989). Efficient specialization of relational concepts. Machine Learning, 4, 99-106. [Abstract & PDF]

VanLehn, K. (1989). Learning events in the acquisition of three skills. In G. Olson & E. Smith (Eds.), Proceedings of the Eleventh Annual Conference of the Cognitive Science Society (pp. 434-441). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

VanLehn, K., Ball, W., & Kowalski, B. (1989). Non-LIFO execution of cognitive procedures. Cognitive Science, 13, 415-465.[Abstract & PDF]

1990

VanLehn, K. (1990). Learning one subprocedure per lesson. In J. W. Shavlik & T. G. Dietterich (Eds.), Readings in Machine Learning (pp. 754-773). Palo Alto, CA: Morgan Kaufmann. (Reprinted from Artificial Intelligence, 31, 1-40, 1987).

VanLehn, K., Ball, W., & Kowalski, B. (1990). Explanation-based learning of correctness: Towards a model of the self-explanation effect. In M. Piatelli-Palmarini (Ed.), Proceedings of the Twelfth Annual Conference of the Cognitive Science Society (pp. 717-724). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

1991

Chi, M. T. H., & VanLehn, K. (1991). The content of physics self-explanations. Journal of the Learning Sciences, 1(1), 69-106. [Abstract & PDF]

Jones, R., & VanLehn, K. (1991). A computational model of acquisition for children’s addition strategies. In L. Birnbaum & G. Collins (Eds.), Machine Learning: Proceedings of the Eighth International Workshop (pp. 65-69). San Mateo, CA: Morgan Kaufmann. [abstract]

Jones, R., & VanLehn, K. (1991). Strategy shifts without impasses: A computational model of the sum to min transition. In K. Hammond & D. Gentner (Eds.), Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society (pp. 358-363). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

VanLehn, K. (1991). Rule acquisition events in the discovery of problem solving strategies. Cognitive Science, 15(1), 1-48. [abstract]

 VanLehn, K., & Jones, R. M. (1991). Learning physics via explanation-based learning of correctness and analogical search control. In L. Birnbaum & G. Collins (Eds.), Machine Learning: Proceedings of the Eighth International Workshop (pp. 132-137). San Mateo, CA: Morgan Kaufmann. [abstract & PDF]

VanLehn, K., Jones, R. M., & Chi, M. T. H. (1991). Modeling the self- explanation effect with Cascade 3. In K. Hammond & D. Gentner (Eds.), Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society (pp. 137-142). Hillsdale, NJ: Erlbaum. [abstract & PDF]

1992

Jones, R., & VanLehn, K. (1992). A fine-grained model of skill acquisition: Fitting Cascade to individual subjects. In J. Kruschke (Ed.), Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society (pp. 873-878). Hillsdale, NJ: Erlbaum. [abstract & PDF]

VanLehn, K., Jones, R. M., & Chi, M. T. H. (1992). A model of the self-explanation effect. Journal of the Learning Sciences, 2(1), 1-60. [abstract & PDF]

1993

Martin, J. & VanLehn, K. (1993). OLAE: Progress toward a multi-activity, Bayesian student modeller. In S. P. Brna, S. Ohlsson, & H. Pain (Eds.), Artificial Intelligence in Education  (pp. 410-417). Charlottesville, VA: Association for the Advancement of Computing in Education. Winner of Best Paper award for the conference. [abstract & PS]

VanLehn, K., & Jones, R. M. (1993). Better learners use analogical problem solving sparingly. In R. S. Michalski & G. Tecuci (Eds.), Proceedings of the Second International Workshop on Multistrategy Learning (pp. 19-30). Fairfax, VA: Center for Artificial Intelligence. [abstract & PDF]

VanLehn, K., & Jones, R. M. (1993). Better learners use analogical problem solving sparingly. In P. E. Utgoff (Ed.), Proceedings of the Tenth International Conference on Machine Learning (pp. 338-345). San Mateo, CA: Morgan Kaufmann. [abstract & PDF]

VanLehn, K., & Jones, R. M. (1993). What mediates the self-explanation effect? Knowledge gaps, schemas or analogies? In M. Polson (Ed.), Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society (pp. 1034-1039). Hillsdale, NJ: Erlbaum. [abstract & PDF]

1994

Jones, R. M., & VanLehn, K. (1994). Acquisition of children’s addition strategies: A model of impasse-free, knowledge-level learning. Machine Learning, 15 (1 & 2), 11-36. [1.7 MB PDF]

Ur, S., & VanLehn, K. (1994). STEPS: A preliminary model of learning from a tutor. In K. Eiselt & A. Ram (Eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society (pp. 893-898). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

VanLehn, K., Ohlsson, S., & Nason, R. (1994). Applications of simulated students: An exploration. Journal of Artificial Intelligence in Education, 5(2), 135-175. [abstract & PDF]

1995

Conati, C., & VanLehn, K. (1995). A student modeling technique for problem solving in domains with large solution spaces. In J. Greer (Ed.), Artificial Intelligence in Education (p. 573). Charlottesville, VA: Association for the Advancement of Computing in Education. [abstract & PDF]

Martin, J., & VanLehn, K. (1995). Student assessment using Bayesian nets. International Journal of Human-Computer Studies, 42, 575-591. [abstract & PDF]

Ur, S., & VanLehn, K. (1995). STEPS: A simulated, tutorable physics student. Journal of Artificial Intelligence in Education, 6(4), 405-437. [abstract & PS]

1996

Conati, C., & VanLehn, K. (1996). POLA: a student modeling framework for Probabilistic On-Line Assessment of problem solving performance. In UM-96: Fifth International Conference on User Modeling  (pp. 75-82). Kailua-Kona, HI: User Modeling, Inc. [abstract & PDF]

Conati, C., & VanLehn, K. (1996). Probabilistic plan recognition for cognitive apprenticeship. In G. W. Cottrell (Ed.), Proceedings of the Eighteenth Annual Meeting of the Cognitive Science Society (pp. 403-408). New York, NY: Erlbaum. [abstract & PDF]

1997

Conati, C., Gertner, A., VanLehn, K., & Druzdzel, M. (1997). On-line student modeling for coached problem solving using Bayesian networks. In A. Jameson, C. Paris, & C. Tasso (Eds.), UM97: Sixth International Conference on User Modeling  (pp. 231-242). Vienna: Springer. Winner of Best Paper award. [abstract & PDF]

Conati, C., Larkin, J., & VanLehn, K. (1997). A computer framework to support self-explanation. In R. du Boulay & R. Mizoguchi (Eds.), Artificial Intelligence in Education (pp. 279-286). Amsterdam: IOS Press. [abstract & PDF]

Ploetzner, R., & VanLehn, K. (1997). The acquisition of informal physics knowledge during formal physics training. Cognition and Instruction, 15(2), 169-205. [abstract & PDF]

VanLehn, K., & Martin, J. (1997). Evaluation of an assessment system based on Bayesian student modeling. International Journal of Artificial Intelligence and Education, 8(2), 179-221. [abstract & PDF]

1998

Gertner, A., Conati, C., & VanLehn, K. (1998). Procedural help in Andes: Generating hints using a Bayesian network student model. In Proceedings of the Fifteenth National Conference on Artificial Intelligence AAAI-98 (pp. 106-111). Cambridge, MA: The MIT Press. [abstract & PDF]

VanLehn, K. (1998). Analogy events: How examples are used during problem solving. Cognitive Science, 22(3), 347-388. [abstract & PDF]

VanLehn, K., Niu, Z., Siler, S., & Gertner A. (1998). Student modeling from conventional test data: A Bayesian approach without priors. In Intelligent Tutoring Systems:4th International Conference (pp. 434-443). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

VanLehn, K., Siler, S., Murray, R. C., & Baggett, W. (1998). What makes a tutorial event effective? In M. A. Gernsbacher & S. Derry (Eds.), Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 1084-1089). Hillsdale, NJ: Erlbaum. [abstract & PDF]

1999

Conati C., & VanLehn, K. (1999). A student model to assess self-explanation while learning from examples. In UM‘99, Seventh International Conference on User Modeling. Banff, Canada. [abstract & PDF]

Conati C., & VanLehn, K. (1999). Teaching meta-cognitive skills: Implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. In S. P. Lajoie & M. Vivet (Eds.), Artificial Intelligence in Education (pp. 297-304), Amsterdam: IOS Press. Winner of a Best Paper Award of this conference. [abstract & PDF]

Ferrari, M., Taylor, R., & VanLehn, K. (1999). Adapting work simulations for schools. Journal of Educational Computing Research, 21(1), 25-53. [abstract & PDF]

VanLehn, K. (1999). Rule learning events in the acquisition of a complex skill: An evaluation of Cascade. Journal of the Learning Sciences, 8(1), 71-125. [abstract & PDF]

2000

Albacete, P. L., & VanLehn, K. (2000). Evaluating the effectiveness of a cognitive tutor for fundamental physics concepts. In L. R. Gleitman & A. K. Joshi (Eds.), Proceedings of the 22nd Annual Meeting of the Cognitive Science Society (pp. 25-30). New York, NY: Erlbaum. [abstract & PDF]

Albacete, P. L., & VanLehn, K. (2000). The conceptual helper: An intelligent tutoring system for teaching fundamental physics concepts. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (pp. 564-573). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Conati, C., & VanLehn, K. (2000). Further results from the evaluation of an intelligent computer tutor to coach self-explanation. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference  (pp. 304-313). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Conati, C., & VanLehn, K. (2000). Toward computer-based support of meta-cognitive skills: A computational framework to coach self-explanation. International Journal of Artificial Intelligence in Education, 11, 389-415. [abstract & PDF]  

Freedman, R. C., Rosé, C. P., Ringenberg, M. A., & VanLehn, K. (2000). ITS Tools for natural language dialogue: A domain-independent parser and planner. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (pp. 433-442). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Gertner, A., & VanLehn, K. (2000). Andes: A coached problem solving environment for physics. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (pp. 133-142). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K [abstract & PDF]

Matsuda, N., & VanLehn, K. (2000). A reification of a strategy for geometry theorem proving. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (p. 660). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Murray, R. C., & VanLehn, K. (2000). DT Tutor: A decision-theoretic, dynamic approach for optimal selection of tutorial actions. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (pp. 153-162). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. Winner of 2nd Best Paper award of the conference. [abstract & PDF]

Rosé C., Moore, J. D., Albritton, D., & VanLehn, K. (2000). A comparative evaluation of Socratic versus didactic tutoring. In J.D. Moore & K. Stenning (Eds.), Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society (pp. 897-902). New York, NY: Erlbaum.

Schulze, K. G., Shelby, R. N., Treacy, D. J., Wintersgill, M. C., VanLehn, K., & Gertner, A. (2000) Andes: An active learning, intelligent tutoring system for Newtonian physics. Themes in Education, 1(2), 115-136. [abstract & PDF]

Schulze, K. G., Shelby, R. N., Treacy, D. J., Wintersgill, M. C., VanLehn, K., & Gertner, A. (2000). Andes: An intelligent tutor for classical physics, The Journal of Electronic Publishing, 6(1). Ann Arbor, MI. http://www.press.umich.edu/jep/06-01/schulze.html

VanLehn, K., Freedman, R., Jordan, P., Murray, R. C., Rosé, C. P., Schulze, K., Shelby, R., Treacy, D., Weinstein, A., & Wintersgill, M. (2000). Fading and deepening: The next steps for Andes and other model-tracing tutors. In G. Gauthier, C. Frasson, K. VanLehn (Eds.), Intelligent Tutoring Systems: 5th International Conference (pp. 474-483). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

2001

Conati, C. & VanLehn, K., (2001). Providing adaptive support to the understanding of instructional material. In Proceedings of IUI 2001, International Conference on Intelligent User Interfaces (pp. 41-47). Santa Fe, NM. [abstract & PDF]

Graesser, A., VanLehn, K., Rosé, C., Jordan, P., & Harter, D. (2001). Intelligent Tutoring Systems with Conversational Dialogue. AI Magazine, 22(4) 39-51. [abstract & PDF]

Jordan, P., Rosé, C., & VanLehn, K. (2001) Tools for authoring tutorial dialogue knowledge. In J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.). Artificial Intelligence in Education (pp. 222-233). Amsterdam: IOS Press. [abstract & PDF]

Rosé, C., Jordan, P., Ringenberg, M., Siler, S., VanLehn, K., & Weinstein, A. (2001). Interactive conceptual tutoring in Atlas-Andes. In J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.). Artificial Intelligence in Education  (pp. 256-266). Amsterdam: IOS Press. Winner of the 2001 Second Best Paper award. [abstract & PDF]

Rosé, C. P., Moore, J. D., VanLehn, K., & Allbritton, D. (2001). A comparative evaluation of Socratic versus didactic tutoring. In J.D. Moore & K. Stenning (Eds.), Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society (pp. 897-902). New York, NY: Erlbaum. [abstract & PDF]

Shelby, R., Schulze, K., Treacy, D., Wintersgill, M., VanLehn, K., & Weinstein, A. (2001). An assessment of the Andes tutor. In Proceedings of the Physics Education Research Conference. Rochester, NY.  [abstract & PDF]

VanLehn, K., & Niu, Z. (2001). Bayesian student modeling, user interfaces and feedback: A sensitivity analysis. International Journal of Artificial Intelligence in Education, 12(2), 154-184. [abstract & PDF]

2002

Conati, C., Gertner, A., & VanLehn, K. (2002). Using Bayesian networks to manage uncertainly in student modeling. User Modeling & User-Adapted Interaction. 12(4), 371-417. Winner of the 2002 James R. Chen Award. [abstract & PDF]

Rosé, C., Bhembe, D., Roque, A., Siler, S., Srivastava, R., & VanLehn, K. A. (2002). Hybrid Language understanding approach for robust selection of tutoring goals. In S. A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Intelligent Tutoring System: 6th International Conference (pp. 552-561).  Berlin: Springer. [abstract & PDF]

Rosé, C. P., Roque, A., Bhembe, D., & VanLehn, K. (2002). An efficient incremental architecture for robust interpretation. Human Languages Technologies Conference. San Diego, CA. [Abstract & PDF]

Siler, S., Rosé, C. P., Frost, T., & VanLehn, K. (2002). Evaluating knowledge construction dialogs (KCDs) versus minilessons within Andes2 and alone. In S. A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Intelligent Tutoring Systems: 6th International Conference (pp. 9-15). Berlin: Springer.

VanLehn, K., Jordan, P., Rosé, C. P., et al. (2002). The architecture of Why2-Atlas:A coach for qualitative physics essay writing. In S. A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Intelligent Tutoring Systems: 6th International Conference  (pp. 158-167). Berlin: Springer. [abstract & PDF]

VanLehn, K., Lynch, C., Taylor, L., Weinstein, A., Shelby, R., Schulze, K., Treacy, D., & Wintersgill, M. (2002). Minimally invasive tutoring of complex physics problem solving. In S. A. Cerri, G. Gouarderes, & F. Paraguacu, (Eds.), Intelligent Tutoring Systems: 6th International Conference (pp. 367-376). Berlin: Springer. [abstract & PDF]

2003

Jordan, P., Makatchev, M., & VanLehn, K. (2003). Abductive Theorem Proving for Analyzing Student Explanations. In H. U. Hoppe, F. Verdejo and J. Kay (Eds.), Artificial Intelligence in Education  (pp. 73-80). Amsterdam: IOS Press [abstract]

Lane, H. C., & VanLehn, K. (2003). Coached program planning: Dialogue-based support for novice program design. Proceedings of the 34th ACM SIGCSE Technical Symposium on Computer Science Education (pp. 148-152). New York, New York: ACM Press. [abstract & PDF]

Matsuda, N., & VanLehn, K. (2003). Modeling Hinting Strategies for Geometry Theorem Proving. In UM03: Proceedings of the 9th International Conference on User Modeling (pp. 373-377) Berlin: Springer. [abstract & PDF]

Rosé, C. P., Bhembe, D., Siler, S., Srivastava, R., & VanLehn, K. (2003). Exploring the Effectiveness of Knowledge Construction Dialogues. In H. U. Hoppe, F. Verdejo and J. Kay (Eds.),Artificial Intelligence in Education. Amsterdam: IOS Press. [abstract & PDF]

Rosé, C. P., Bhembe, D., Siler, S., Srivastava, R., & VanLehn, K. (2003). The Role of Why questions in effective human tutoring. In In H. U. Hoppe, F. Verdejo and J. Kay (Eds.), Artificial Intelligence  in Education. Amsterdam: IOS Press. [abstract & PDF]

Rosé, C. P., Gaydos, A., Hall, B.S., Roque, A., & VanLehn, K. (2003). Overcoming the Knowledge Engineering Bottleneck for Understanding Student Language Input. In In H. U. Hoppe, F. Verdejo and J. Kay (Eds.), Artificial Intelligence in Education. Amsterdam: IOS Press. [abstract & PDF]

Rosé, C. P., Litman, D., Bhembe, D., Forbes, K., Silliman, S., Srivastava, R., & VanLehn, K. A. (2003). Comparison of tutor and student behavior in speech versus text based tutoring. Proceedings of the HLT-NAACL Workshop on Building Educational Applications Using Natural Language Processing. [abstract & PDF]

Siler, S. A., & VanLehn, K. (2003). Accuracy of Tutors’ Assessments of their Students by Tutoring Context. In R. Alterman & D. Hirsch, (Eds.), Proceedings of the Twenty-Fifth Annual meeting of the Cognitive Science Society. New York, NY: Lawrence Erlbaum Associates. [abstract & PDF]

VanLehn, K., Siler, S., Murray, R. C., Yamauchi, T., & Baggett, W.B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21(3), 209-249. [abstract & PDF]

2004

Jordan, P. W., Makatchev, M., & VanLehn, K. (2004). Combining competing language understanding approaches in an intelligent tutoring system. In J. C. Lester, R. M. Vicari, & F. Paraguacu, (Eds.), Intelligent Tutoring Systems: 7th International Conference  (pp. 346-357). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Lane, H. C., & VanLehn, K. (2004). A dialogue-based tutoring system for beginning programming. In V. Barr & Z. Markov (Eds.), Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS) (pp. 449-454). Menlo Park, CA: AAAI Press. [abstract & PDF]

 Litman, D. J., Rosé, C. P, Robes-Riley, K., VanLehn, K., Bhembe, D., & Silliman, S. (2004) Spoken versus typed human and computer dialogue tutoring. In J. C. Lester, R. M. Vicari, & F. Paraguacu, (Eds.), Intelligent Tutoring Systems: 7th International Conference  (pp. 368-379). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Makatchev, M., Jordan, P., & VanLehn, K. (2004). Abductive theorem proving for analyzing student explanations and guiding feedback in intelligent tutoring systems. Journal of Automated Reasoning. 32(3), 187-226. [abstract & PDF]

Makatchev, M., Jordan, P. W., & VanLehn, K. (2004). Modeling student’s reasoning about qualitative physics: Heuristics for abductive proof search. In J. C. Lester, R. M. Vicari, & F. Paraguacu, (Eds.), Intelligent Tutoring Systems: 7th International Conference (pp. 699-709). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Makatchev, M., Jordan, P., Pappuswamy, U., & VanLehn, K. (2004). Abductive proofs as models of qualitative reasoning. In J. de Kleer & K. Forbus (Eds.), Proceedings of Workshop on Qualitative Reasoning (pp. 11-18). Evanston, IL. [abstract & PDF]

Makatchev, M., Jordan, P. W., Pappuswamy, U., & VanLehn, K. (2004). Abductive proofs as models of students’ reasoning about qualitative physics. In Sixth International Conference on Cognitive Modeling (pp. 166-171). New York, NY: Erlbaum. [abstract & PDF]

Matsuda, N., & VanLehn, K. (2004). GRAMY: A geometry theorem prover capable of construction. Journal of Automated Reasoning, 32(1), 3-33. [abstract & PDF]

Murray, R.C., VanLehn, K., & Mostow, J. (2004). Looking ahead to select tutorial actions: A decision-theoretic approach. International Journal of Artificial Intelligence and Education, 14(3-4), 235-278. [abstract & PDF]

VanLehn, K., Bhembe, D., Chi, M., Lynch, C., Schulze, K., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., & Wintersgill, M. (2004). Implicit versus explicit learning of strategies in a non-procedural cognitive skill. In J. C. Lester, R. M. Vicari, & F. Paraguacu, (Eds.), Intelligent Tutoring Systems: 7th International Conference (pp. 521-530). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

2005

Graesser, A. G., McNamara, D. S., & VanLehn, K. (2005).  Scaffolding deep comprehension strategies through Point&Query, AutoTutor, and iSTART.  Educational Psychologist, 40, 225-234. [abstract & PDF]

Jordan, P. W., Albacete, P., & VanLehn, K. (2005). Taking control of redundancy in scripted tutorial dialogue. In G. McCalla, C. K. Looi, B. Bredeweg & J. Breuker (Eds.), Artificial Intelligence in Education.  (pp. 314-321) Amsterdam: IOS Press. [abstract & PDF]

Lane, H. C., & VanLehn, K. (2005). Intention-based scoring: An approach to measuring success at solving the composition problem. In W. Dann, P. T. Tymann, & D. Baldwin (Eds.), Proceedings of the 36th ACM Technical Symposium on Computer Science Education (SIGCSE). New York, New York: ACM Press. [abstract & PDF]

Lane, H. C., & VanLehn, K. (2005) Teaching program planning skills to novices with natural language tutoring. Computer Science Education, 15(3), 183-201.  [Abstract & PDF]

Matsuda, N., & VanLehn, K. (2005). Advanced geometry tutor: An intelligent tutor that teaches proof-writing with construction. In G. McCalla, C. K. Looi, B. Bredeweg & J. Breuker (Eds.), Artificial Intelligence in Education (pp.443-450). Amsterdam: IOS Press. [abstract & PDF]

Makatchev, M. & VanLehn, K. (2005). Analyzing completeness and correctness of utterances using an ATMS. In G. McCalla, C. K. Looi, B. Bredeweg & J. Breuker (Eds.), Artificial Intelligence in Education (pp. 403-410). Amsterdam, Netherlands: IOS Press. [abstract & PDF]

Murray, R. C., & VanLehn, K. (2005). Effects of dissuading unnecessary help requests while providing proactive help. In G. McCalla, C. K. Looi, B. Bredeweg & J. Breuker (Eds.), Artificial Intelligence in Education (pp. 887-889). Amsterdam, Netherlands: IOS Press. [abstract & PDF]

Pappuswamy, U., Bhembe, D., Jordan, P. W., & VanLehn, K. (2005). A multi-tier NL-knowledge clustering for classifying students’ essays. In I. Russell & Z. Markov (Eds.), Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS05) (pp. 566-571). Menlo Park, CA: AAAI Press. [abstract & PDF]

Pappuswamy, U., Bhembe, D., Jordan, P. W., & VanLehn, K. (2005). A supervised clustering method for text classification. In A. Gelbukh (Ed.), Proceedings of Computational Linguistics and Intelligent Text Processing: 6th International Conference, CICLing: Vol. 3406. (pp. 704 - 714). Berlin: Springer-Verlag Berlin & Heidelberg GmbH & Co. K. [abstract & PDF]

Pappuswamy, U., Jordan, P. W., & VanLehn, K. (2005). Resolving Discourse Deictic Anaphors in Tutorial Dialogues. In C. Sassen, A. Benz, & P. Kühnlein (Eds.), Proceedings of Constraints in Discourse (pp. 96-103). Dortmund University, Germany. [abstract & PDF]

Rosé, C. P., & VanLehn, K. (2005). An Evaluation of a Hybrid Language Understanding Approach for Robust Selection of Tutoring Goals. International Journal of Artificial Intelligence in Education, 15(4), 325-355. [abstract & PDF]

VanLehn, K., Lynch, C., Schulze, K. Shapiro, J. A., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., & Wintersgill, M. (2005). The Andes physics tutoring system: Lessons Learned. In International Journal of Artificial Intelligence and Education, 15 (3), 1-47. [abstract & PDF]

VanLehn, K., Lynch, C., Schulze, K. Shapiro, J. A., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., & Wintersgill, M. (2005). The Andes physics tutoring system: Five years of evaluations. In G. McCalla, C. K. Looi, B. Bredeweg & J. Breuker (Eds.), Artificial Intelligence in Education.  (pp. 678-685) Amsterdam, Netherlands: IOS Press. Winner of a Best Paper Award of this conference. [abstract & PDF]

2006

Murray, R. C. & VanLehn, K. (2006). A comparison of decision-theoretic, fixed-policy and random tutorial action selection. In K. Ashley & M. Ikeda (Eds.), Intelligent Tutoring Systems: 8th International Conference, ITS2006. pp. 114-123 Amsterdam: IOS Press. [PDF 140Kb]

Ringenberg, M. & VanLehn, K. (2006). Scaffolding problem solving with annotated, worked-out examples to promote deep learning. In K. Ashley & M. Ikeda (Eds.), Intelligent Tutoring Systems: 8th International Conference, ITS2006. pp. 625-634. Amsterdam: IOS Press. [ PDF 231Kb]

Jordan, P., Makatchev, M., Pappuswamy, U., VanLehn, K., & Albacete, P. (2006). A natural language tutorial dialogue system for physics. In G. Sutcliffe & R. Goebel (Eds.), Proceedings of the 19th International FLAIRS Conference. Menlo Park, CA: AAAI Press. [PDF 90Kb]

Makatchev, M., VanLehn, K., Jordan, P. W., & Pappuswamy, U. (2006). Representation and reasoning for deeper natural language understanding in a physics tutoring system. In G. Sutcliffe & R. Goebel (Eds.), Proceedings of the 19th International FLAIRS conference. Menlo Park, CA: AAAI Press. [PDF 86Kb]

Litman, D., Rose, C., Forbes-Riley, K., VanLehn, K., Bhembe, D., & Silliman, S. (2006). Spoken versus typed human and computer dialogue. International Journal of Artificial Intelligence and Education, 16, 145-170.  [Abstract & PDF]

VanLehn, K. (2006) The behavior of tutoring systems.  International Journal of Artificial Intelligence in Education. 16, 3, 227-265. [Abstract & PDF]

2007

VanLehn, K., Graesser, A. C., Jackson, G. T., Jordan, P., Olney, A., & Rose, C. P. (2007). When are tutorial dialogues more effective than reading? Cognitive Science 31(1), 3-62.  [Abstract & PDF]

Chi, Min & VanLehn, K. (2007) The impact of explicit strategy instruction on problem-solving behaviros across intelligent tutoring systems. In D. McNamara & G. Trafton (Eds.) Proceedings of the 29th Annual Conference of the Cognitive Science Society. pp. 167-172 New York, NY: Erlbaum. [PDF 209KB]

Chi, Min & VanLehn, K.  (2007) Domain-specific and domain-independent interactive behaviors in Andes. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education.  pp. 548-550. Amsterdam, Netherlands: IOS Press. [PDF 136KB]

Chi, Min & VanLehn, K.  (2007) Porting an intelligent tutoring system across domains. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education. pp. 551-553.  Amsterdam, Netherlands: IOS Press. [PDF 446KB]

Chi, Min & VanLehn, K.  (2007) Accelerated future learning via explicit instruction of a problem solving strategy. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education.  pp. 409-416.  Amsterdam, Netherlands: IOS Press. [PDF 188KB]

Craig, S. D., VanLehn, K., Gadgil, S., & Chi, M. T. H. (2006). Learning from collaboratively observing videos during problem solving with Andes. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education.  pp. 554-556. Amsterdam, Netherlands: IOS Press. [PDF 35KB]

Hausmann, R. G. M. & VanLehn, K. (2007).  Explaining self-explaining:  A contrast between content and generation.  In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education.  pp. 417-424. Amsterdam, Netherlands: IOS Press. [PDF 63KB] Winner of the Best Paper Award for this conference.

Hausmann, R. G. M. & VanLehn, K. (in press).  Self-explaining in the classroom:  Learning curve evidence   In D. McNamara & G. Trafton (Eds.) Proceedings of the 29th Annual Conference of the Cognitive Science Society. pp 1067-1072 New York, NY: Erlbaum. [PDF 94KB]

Makatchev, M. & VanLehn, K. (2007) Combining Bayesian networks and formal reasoning for semantic classification of student utterances. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education. pp. 307-314. Amsterdam, Netherlands: IOS Press. [PDF 102KB]

Nwaigwe, A., Koedinger, K.,VanLehn, K., Hausmann, R. G. M. & Weinstein, A.  (2007) Exploring alternative methods for error attribution in learning curves analyses in intelligent tutoring systems. In R. Luckin, K. R. Koedinger & J. Greer (Eds.)  Artificial Intelligence in Education. pp 246-253. Amsterdam, Netherlands: IOS Press. [157 KB PDF]

VanLehn, K., Koedinger, K., Skogsholm, A., Nwaigwe, A., Hausmann, R.G.M., Weinstein, A. & Billings, B. (2007). What’s in a step?  Toward general, abstract representations of tutoring system log data.  In C. Conati & K. McCoy (eds).  Proceedings of User Modelling 2007. [PDF 48KB].

2008

Hausmann, R. G., van de Sande, B. & VanLehn, K. (2008). Trialog: How Peer Collaboration Helps Remediate Errors in an ITS.  Proceedings of the 21th International FLAIRS Conference, pp . 415-420 Menlo Park: CA, AAAI Press. [243 KB PDF]

Chi, Min, Jordan, P.,& VanLehn, K. & Hall, M. (2008). Reinforcement learning-based feature selection for developing pedagogically effective tutorial dialogue tactics.  Proceedings of the Educational Data Mining Workshop, Montreal, Canada: [137 KB PDF]  Winner of Best Poster Award.

Jung, S.-Y., VanLehn, K. (2008). Bi-directional search for bugs: A tool for accelerating knowledge acquisition for equation-based ITS.  In B. P. Woolf, E. Aimeur, R. Nkambou & S. Lajoie (eds).  Intelligent Tutoring Systems: 9th International Conference, ITS2008, pp. 758-762. Amsterdam: IOS Press. [110 KB PDF]

Chi, Min & VanLehn, K. (2008). Eliminating the Gap between the High and Low Students through Meta-Cognitive Strategy Instruction.  In B. P. Woolf, E. Aimeur, R. Nkambou & S. Lajoie (eds).  Intelligent Tutoring Systems: 9th International Conference, ITS2008, pp 603-613. Amsterdam: IOS Press. [90 KB PDF]  Winner of Best Student Paper Prize.

Hausmann, R. G., van de Sande, B. & VanLehn, K. (2008). Shall we explain? Augmenting Learning from Intelligent Tutoring Systems and Peer Collaboration. In B. P. Woolf, E. Aimeur, R. Nkambou & S. Lajoie (eds).  Intelligent Tutoring Systems: 9th International Conference, ITS2008, pp. 636-645. Amsterdam: IOS Press.

Gheorghiu, R. & VanLehn, K. (2008). XTutor: an Intelligent Tutor System for science and math based on Excel.  In B. P. Woolf, E. Aimeur, R. Nkambou & S. Lajoie (eds).  Intelligent Tutoring Systems: 9th International Conference, ITS2008, pp. 749-752.  Amsterdam: IOS Press. [128 KB PDF]

Hausmann, R. G., van de Sande , B. & VanLehn, K. (2008). Are Self-explaining and Coached Problem Solving More Effective When Done by Pairs of Students Than Alone?  In B. C. Love, K. McRae & V. M. Sloutsky (Eds.), Procedings of the 30th Annual Conference of the Cognitive Science Society(pp. 2369-2374).  New York, NY: Erlbaum. [244 KB PDF]

Hausmann, R. G., van de Sande, B., van de Sande, C. & VanLehn, K. (2008).  Productive dialogue during collaborative problem solving.  Proceedings of the International Conference of the Learning Sciences.  [129 KB PDF].

Nokes, T. J. & VanLehn, K. (2008)  Bridging principles and examples through analogy and explanation.  Proceedings of the International Conference of the Learning Sciences. [122 KB PDF]

Craig, S. D., VanLehn, K., & Chi. M.T.H. (2008). Promoting learning by observing deep-level reasoning questions on quantitative physics problem solving with Andes. In K. McFerrin, R. Weber, R. Weber, R. Carlsen, & D.A. Willis (Eds.). The proceedings of the 19th International conference for the Society for Information Technology & Teacher Education. (pp. 1065-1068). Chesapeake, VA: AACE.  [26 KB PDF]

2009

Siler, S.A. & VanLehn, K. (2009). Learning, interactional and motivational outcomes in one-to-one synchronous computer-mediated versus face-to-face tutoring.  International Journal of Artificial Intelligence in Education. 19(1), pp. 73-102. [274 KB PDF]

Craig, S. D., Chi, M. T. H. & VanLehn, K. (2009). Improving classroom learning by collaboratively observing human tutoring videos while problem solving.  Journal of Educational Psychology . 101(4), 779-789. [135 KB PDF]

Chi, M., Jordan, P. VanLehn, K & Litman, D. (2009). To elicit or to tell: Does it matter?  Artificial Intelligence in Education. In V. Dimitrova, R. Mizoguchi, B. Du Boulay & A. C. Graesser (Eds.), Amsterdam, Netherlands: IOS Press. [230 KB PDF]

Hausmann, R. G. M., Nokes, T. J., VanLehn, K & van de Sande, B. (2009) Collaborative dialog while studying worked-out examples.  In V. Dimitrova, R. Mizoguchi, B. Du Boulay & A. C. Graesser (Eds.), Artificial Intelligence in Education. Amsterdam, Netherlands: IOS Press. [144 KB PDF]

Hausmann, R. G. M., Nokes, T. J., VanLehn, K, van de Sande, B. & Gershman, S. (2009) The design of self-explanation prompts: The Fit hypothesis. In N. Taatgen & H. van Rijn (Eds) CogSci 2009 Proceedings. [628 KB PDF]

2010

Chi, Min & VanLehn, K (2010). Meta-cognitive strategy instruction in intelligent tutoring systems: How, when, and why.  Journal of Educational Technology and Society, 13(1), 25-39. [459 KB PDF]

Hausmann, R. G. M. & VanLehn, K (2010). The effect of self-explaining on robust learning  International Journal of Artificial Intelligence in Education, 20, 4, 303-332. [731 KB PDF]

Chi, Min, VanLehn, K. & Litman, D. (2010). Do micro-level tutorial decisions matter: Applying reinforcement learning to induce pedagogical tutorial tactics.  In V. Aleven, J. Kay & J. Mostow (Eds), Intelligent Tutoring Systems: 10th International Conference, ITS 2010 (pp. 184-193). Heidelberg, Germany: Springer. [152 KB PDF] Winner of the Best Paper Award.

Chi, Min, VanLehn, K. & Litman, D. (2010). The more the merrier? Examining three interaction hypotheses.   In Proceedings of the Thirty-Second Annual conference of the Cognitive Science Society. Portland, OR. pp 2870-2875. [561 KB PDF]

Chi, Min, VanLehn, K. Litman, D., & Jordan, P. (2010). Inducing effective pedagogical strategies using learning context features.   In P. De Bra, A. Kobsa & D. Chin (Eds.) User Modeling, Adaptation and Personalization: 18th International Conference, UMAP 2010 (pp. 147-158) Heidelberg, Germany: Springer. [243 KB PDF] Winner of the Best Student Paper award.

Moss, J., Schunn, C. D., Schneider, W., McNamara, D. S. & VanLehn, K. (2010). An fMRI study of strategic reading comprehension   In Proceedings of the Thirty-Second Annual conference of the Cognitive Science Society. Portland, OR. pp 1319-1324. [188 KB PDF]

Muldner, K., Burleson, W., van de Sande, B. & VanLehn, K. (2010). An analysis of gaming behaviors in an intelligent tutoring system.  In V. Aleven, J. Kay & J. Mostow (Eds), Intelligent Tutoring Systems: 10th International Conference, ITS 2010 (pp. 224-233). Heidelberg, Germany: Springer. [152 KB PDF]

Muldner,K., Burleson, W., & VanLehn, K. (2010). "Yes!": Using tutor and sensor data to predict moments of delight during instructional activities.   In P.De Bra, A. Kobasa & D. Chin (Eds.) User Modeling, Adaptation and Personalization: 18th International Conference, UMAP 2010 (pp. 159-170) [243 KB PDF]

2011

Chi, Min, VanLehn, K, Litman, D. & Jordan, P. (2011). Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical tactics.  User Modeling and User Adapted Instruction, 21, 1-2, pp. 137-180. [956 KB PDF]

Muldner, K., Burleson, W., van de Sande, B., & VanLehn, K. (2011). An analysis of students' gaming behaviors in an intelligent tutoring system: Predictors and impacts.  User Modeling and User Adapted Instruction, 21, 1-2, pp. 99-135. Winner of 2011 James Chen Annual Award for Best UMUAI Paper [3.5 MB PDF]

Chi, Min, Koedinger, K., Gordon, G., Jordan, P. & VanLehn, K. (2011). Instructional factors analysis: A cognitive model for multiple instructional interventions.   In C. Conati & S. Ventura (Eds.) Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011). [733 KB PDF]

Nokes, T. J., Hausmann, R. G. M., VanLehn, K., & Gershman, S. (2011). Testing the instructional fit hypothesis: the case of self-explanation prompts.  Instructional Science, 39, 5, pp. 645-666 [491 KB PDF]

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems and other tutoring systems.   [489 KB Preprint] Educational Psychologist, 46, 4, 197-221. doi:10.1080/00461520.2011.611369

Chi, Min, VanLehn, K, Litman, D. & Jordan, P. (2011). An evaluation of pedagogical tutorial tactics for a natural language tutoring system: A reinforcement learning approach  [0.9 MB Preprint] International Journal of Artificial Intelligence in Education, 21, 1-2, pp. 83-113. doi:10.3233/JAI-2011-014

Moss, J., Schunn, C. D., Schneider, W., McNamara, D. S. & VanLehn, K. (2011). The neural correlates of strategic reading comprehension: Cognitive control and discourse comprehension.   NeuroImage, 58, 2, pp. 675-686. [919 Kb PDF]

VanLehn, K., Burleson, W., Chavez Echeangary, H., Christopherson, R., Gonzales Sanchez J., Hastings, J., Hidalgo Pontet, Y., Muldner, K., & Zhang, L. (2011). The Level Up Procedure: How to Measure Learning Gains Without Pre- and Post-testing.   In T. Hirashima et al. (Eds), Proceedings of the 19th International Conference on Computers in Education. Chiang Mai, Thailand: Asia-Pacific Society for Computers in Education. [50 Kb PDF]

Gonzalez Sanchez, J., Chavez Echeagaray, M. E., VanLehn, K. & Burleson, W. (2011). From behavioral descriptions to a pattern-based model for intelligent tutoring systems.   In Proceedings of the 18th International Conference on Pattern Languages of Programs (PLoP). ACM Press.

2012

Chi, M. T. H. & VanLehn, K. (2012). Seeing deep structure from the interactions of surface features.   [0.1 MB Preprint] Educational Psychologist, 47, 3, pp. 177-188. doi:10.1080/00461520.2012.695709

2013

Nokes-Malach, T. J., VanLehn, K., Belenky, D. M., Lichtenstein, M. & Cox, G. (2013). Coordinating principles and examples through analogy and self-explanation.   European Journal of Psychology of Education, 28, 1237-1263. doi:10.1007/s10212-012-0164-z

VanLehn, K. (2013). Model construction as a learning activity: A design space and review.   [0.1 MB Preprint] Interactive Learning Environments, 21, 4, 371-413. doi:10.1080/10494820.2013.803125

Girard, S., Zhang, L., Hidalgo-Pontet, Y., VanLehn, K., Burleson, W., Chavez-Echeagaray, M. E., & Gonzalez-Sanchez, J., (2013). Using HCI task modeling techniques to measure how deeply students model   [0.2 MB Preprint] In H. C. Lane, K. Yacef, J. Mostow & P. Pavlik (Eds), Artificial Intelligence in Education: 16th International Conference, AIED 2013, 766-769. doi:10.1007/978-3-642-39112-5_108

Girard, S., Chavez-Echeagaray, M. E., Gonzalez-Sanchez, J., Hidalgo-Pontet, Y., Zhang, L., Burleson, W. & VanLehn, K. (2013). Defining the behavior of an affective learning companion in the Affective Meta-Tutor project   [0.2 MB Preprint] In H. C. Lane, K. Yacef, J. Mostow & P. Pavlik (Eds), Artificial Intelligence in Education: 16th International Conference, AIED 2013, 21-30. doi:10.1007/978-3-642-39112-5_3

2014

VanLehn, K., Burleson, W., Girard, S., Chavez-Echeagaray, M. E., Gonzalez-Sanchez, J., Hidalgo-Pontet, Y. & Zhang, L. (2014). The Affective Meta-Tutoring project: Lessons learned.   [0.2 MB Preprint] In Trausan-Matu, Stefan, Boyer, Kristy E., Crosby, Martha, Panourigia, Kitty Intelligent Tutoring Systems, 12th International Conference, ITS 2014, Berlin: Springer, 94-103. doi 10.1007/978-3-319-07221-0_11

Chi, M., Jordan, P. & VanLehn, K.(2014). When is tutorial dialogue more effective than step-based tutoring?   [0.3 MB Preprint] In S. Trausan-Matu, K. E. Boyer, M. Crosby, & K. Panourigia, Intelligent Tutoring Systems, 12th International Conference, ITS 2014, Berlin: Springer, 210-219. doi:10.1007/978-3-319-07221-0_25

Gonzalez-Sanchez, J., Chavez-Echeagary, M. E., VanLehn, K., Burleson, W., Girard, S., Hidalgo-Pontet, Y., Zhang, L.(2014). A system architecture for affective meta intelligent tutoring.   [0.3 MB Preprint] In S. Trausan-Matu, K. E. Boyer, M. Crosby, & K. Panourigia, Intelligent Tutoring Systems, 12th International Conference, ITS 2014, Berlin: Springer, 529-534. doi:10.1007/978-3-319-07221-0_67

Ranganathan, R., van de Sande, B. & VanLehn, K. (2014). What do students do when using a step-based tutoring system.   [0.7 MB Preprint] Research and Practice in Technology Enhanced Learning, 9(2), 323-347.

Iwaniec, David M., Childers, Daniel L., VanLehn, K., & Wiek, Arnim. (2014). Studying, teaching and applying sustainabilty visions using systems modeling.   Sustainability, 6(7), 4452-4469. doi:10.3390/su6074452

Zhang, L., VanLehn, K., Girard, S., Burleson, W., Chavez-Echeagaray, M. E., Gonzalez-Sanchez, J., & Hidalgo-Pontet, Y. (2014). Evaluation of a meta-tutor for constructing models of dynamic systems.   [3.7 MB Preprint] Computers & Education, 75, 196-217. doi:10.1016/j.compedu.2014.02.015

2015

Siler, S. & VanLehn, K. (2015). Investigating microadaptation in one-to-one human tutoring.   The Journal of Experimental Education, 83, (3), 344-367. doi:10.1080/00220973.2014.907224

2016

VanLehn, K. (2016). Regulative loops, step loops and task loops.   International Journal of Artificial Intelligence in Education, [0.3 MB Preprint] 26, 1, pp 107-112, doi:10.1007/s40593-015-0056-x

VanLehn, K. (2016). Reflections on Andes' goal-free user interface.   International Journal of Artificial Intelligence in Education, [0.4 MB Preprint] 26, 1, pp 82-81, doi:10.1007/s40593-015-0067-7

VanLehn, K., Chung, G., Grover, S., Madni, A. & Wetzel, J. (2016). Learning science by constructing models: Can Dragoon increase learning without increasing the time required?   International Journal of Artificial Intelligence in Education 26 (4), 1033-1068. [3 MB Preprint] doi:10.1007/s40593-015-0093-5

Zhang, L. & VanLehn, K. (2016). How do machine-generated questions compare to human-generated questions?   Research and Practice in Technology Enhanced Learning 11, 7. doi:10.1186/s41039-016-0031-7

Cheeman, S., VanLehn, K., Burkhardt, H., Pead, D. & Schoenfeld, A.(2016). Electronic posters to support formative assessment   Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems 1159-1164, ACM. doi: 10.1145/2851581.2892417

Swartout, W. R., Nye, B.D., Hartholt, A., Reilly, A., Graesser, A. C., VanLehn, K., Wetzel, J., Liewer, M., Morbini, F., Morgan, B., Wang, L., Benn, G., & Rosenberg, M.(2016). Designing a personal assistant for life-long learning (PAL3)   FLAIRS Conference, 491-496, AAAI.

2017

Zhang, L. & VanLehn, K. (2017). Adaptively selecting biology questions generated from a semantic network   Interactive Learning Environments, 25 (7), 828-846. [0.2 MB Preprint], doi: 10.1080/10494820.2016.1190939

VanLehn, K., Zhang, L., Burleson, W., Girard, S. & Hidago-Pontet, Y. (2017). Can a non-cognitive learning companion increase the effectiveness of a meta-cognitive learning strategy?   IEEE Transactions on Learning Technology, 10 (3), 277-289. [0.6 MB Preprint] doi: 10.1109/TLT.2016.2594775.

Wetzel, J., VanLehn, K., Chaudhari, P., Desai, A., Feng, J., Grover, S., Joiner, R., Kong-Silvert, M., Patade, V., Samala, R., Tiwari, M. & van de Sande, B. (2017). The design and development of the Dragoon intelligent tutoring system for model construction: Lessons learned.   Interactive Learning Environments, 25 (3), 361-381. [0.7 MB Preprint], doi: 10.1080/10494820.2015.1131167

VanLehn, K., Wetzel, J, Grover, S. & van de Sande, B. (2017). Learning how to construct models of dynamic systems: An initial evaluation of the Dragoon intelligent tutoring system.   IEEE Transactions on Learning Technology 10 (2), 154-167. [0.7 MB Preprint], doi:10.1109/TLT.2016.2514422

Viswanathan, S. & VanLehn, K. (2017). High accuracy detection of collaboration from log data and superficial speech features   In Smith, B. K., Borge, M., Mercier, E., and Lim, K. Y. (Eds.). Making a Difference: Prioritizing Equity and Access in CSCL, 12th International Conference on Computer Supported Collaborative Learning (CSCL) Volume 1. Philadelphia, PA: International Society of the Learning Sciences. pp 335-342. [Preprint], doi:10.22318/cscl2017.46

2018

Viswanathan, S. & VanLehn, K.. (2018). Using the tablet gestures and speech of pairs of students to classify their collaboration   IEEE Transactions on Learning Technology, 11 (2), 230-242. doi: 10.1109/TLT.2017.2704099 [Preprint].

Grover, S., Wetzel, J., & VanLehn, K. (2018). How should knowledge composed of schemas be represented in order to optimize student model accuracy? In C. Rosé, R. Martínez-Maldonado, U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, & B. du Boulay (Eds.), Artificial Intelligence in Education: Proceedings of the 19th International Conference, (pp. 127-139), Berlin: Springer. doi: 10.1007/978-3-319-93843-1_10 [Preprint]

VanLehn, K., Burkhardt, H., Cheema, S., Kang, S., Pead, D., Schoenfeld, A. H., & Wetzel, J. (2018). The effect of digital versus traditional orchestration on collaboration in small groups. In C. Rosé, R. Martínez-Maldonado, U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, & B. du Boulay (Eds.), Artificial Intelligence in Education: Proceedings of the 19th International Conference, ( pp. 369-373). Berlin: Springer. doi: 10.1007/978-3-319-93846-2_69 [Preprint]

Wetzel, J., Burkhardt, H., Cheema, S., Kang, S., Pead, D., Schoenfeld, A. H., & VanLehn, K. (2018). A preliminary evaluation of the usability of an AI-infused orchestration system. In C. Rosé, R. Martínez-Maldonado, U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, & B. du Boulay (Eds.), < i>Artificial Intelligence in Education: Proceedings of the 19th International Conference, (pp. 378-383). Berlin: Springer. doi: 10.1007/978-3-319-93846-2_71 [Preprint]

2019

Zhang, L., & VanLehn, K. (2019). Evaluation of auto-generated distractors in multiple choice questions from a semantic network. Interactive Learning Environments, currently online only. doi:10.1080/10494820.2019.1619586 [Preprint]

VanLehn, K., Burkhardt, H., Cheema, S., Kang, S., Pead, D., Schoenfeld, A. H., & Wetzel, J. (2019). Can an orchestration system increase collaborative, productive struggle in teaching-by-eliciting classrooms? Interactive Learning Environments. currently online only, doi: 10.1080/10494820.2019.1616567 [Preprint]

VanLehn, K., Cheema, S., Kang, S., & Wetzel, J. (2019). Auto-sending messages in an intelligent orchestration system: A pilot study. In Proceedings of Artificial Intelligence in Education. (pp. 292-297) doi: 10.1007/978-3-030-23207-8_54 [Preprint]

Viswanathan, S. A., & VanLehn, K. (2019). Collaboration detection that preserves privacy of students' speech. In Proceedings of Artificial Intelligence in Education. (pp. 507-517) doi: 10.1007/978-3-030-23204-7_42 [Preprint]

Viswanathan, S. A., & VanLehn, K. (2019). Detection of collaboration: relationship between log and speech-based classification. In S. Isotani, E. Millan, A. Ogan, P. Hastings, B. McLaren, & R. Luckin (Eds.), International Conference on Artificial Intelligence in Education (pp. 327-331). Berlin: Springer. doi: 10.1007/978-3-030-23207-8_60 [Preprint]

2020

Vanlehn, K., Banerjee, C., Milner, F., & Wetzel, J. (2020). Teaching algebraic model construction: A tutoring system, lessons learned and an evaluation. International Journal of Artificial Intelligence in Education. doi: 10.1007/s40593-020-00205-3 [Preprint]

Shahrokhian, B., Sivaraman, A., & VanLehn, K. (2020). Toward an Automatic Speech Classifier for the Teacher. In I. I. Bittencourt, M. Cukurova, K. Muldner, R. Luckin, & E. Millan (Eds.), Artificial Intelligence in Education, 21st International Conference, AIED 2020. Switzerland: Springer Nature. doi: 10.1007/978-3-030-52240-7_51 [Preprint]

In press

 Book chapters and conferences without stringent reviewing

1980

VanLehn, K., & Brown, J. S. (1980). Planning Nets: A representation for formalizing analogies and semantic models of procedural skills. In R. E. Snow, P.A. Federico, & W. E. Montague (Eds.), Aptitude, Learning, and Instruction: Cognitive Process Analyses of Learning and Problem Solving (pp. 95-138). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

1982

Brown, J. S., & VanLehn, K. (1982). Towards a generative theory of bugs. In T. Carpenter, J. Moser, & T. Romberg (Eds.), Addition and Subtraction: A Developmental Perspective (pp. 117-135). Hillsdale, NJ: Erlbaum.

1983

VanLehn, K. (1983). On the representation of procedures in Repair Theory. In H. P. Ginsberg (Ed.), The Development of Mathematical Thinking (pp. 201-253). New York: Academic Press. [Abstract & PDF]

1984

VanLehn, K., Brown, J. S., & Greeno, J. G. (1984). Competitive argumentation in computational theories of cognition. In W. Kintsch, J. Miller, & P. Polson (Eds.), Methods and Tactics in Cognitive Science (pp. 235-262). Hillsdale, NJ: Erlbaum. [Abstract & PDF]

1986

VanLehn, K. (1986). Arithmetic procedures are induced from examples. In J. Hiebert (Ed.), Conceptual and Procedural Knowledge: The Case of Mathematics (pp. 133-180). Erlbaum, Hillsdale, NJ. [PDF]

1988

VanLehn, K. (1988). Student modeling. In M. Polson & J. Richardson (Eds.), Foundations of Intelligent Tutoring Systems (pp. 55-78). Hillsdale, NJ: Erlbaum. [1 MB PDF]

VanLehn, K. (1988). Toward a theory of impasse-driven learning. In H. Mandl & A. Lesgold (Eds.), Learning Issues for Intelligent Tutoring Systems (pp. 19-41). New York, NY: Springer. [2.9 MB PDF]

1989

VanLehn, K. (1989). Problem solving and cognitive skill acquisition. In M. I. Posner (Ed.), Foundations of Cognitive Science (pp. 526-579). Cambridge, MA: M. I. T. Press. [2.6MB PDF]

1991

VanLehn, K. (1991). Two pseudo-students: Applications of machine learning to formative evaluation. In R. Lewis & S. Otsuki (Eds.), Advanced Research on Computers in Education (pp. 17-26). Amsterdam: Elsevier. [Abstract & PDF]

VanLehn, K., & Ball, W. (1991). Goal Reconstruction: How Teton blends situated action and planned action. In K. VanLehn (Ed.), Architectures for Intelligence (pp. 147-188). Hillsdale, NJ: Erlbaum. [2 MB PDF]

Woolf, B. P., Soloway, E., Clancey, W., VanLehn, K., & Suthers, D. (1991). Knowledge-based environments for teaching and learning. AI Magazine, 11(5), 74-76. [Abstract & PDF]

1992

VanLehn, K. (1992). A workbench for discovering task-specific theories of learning. In E. Scanlon and T. O’Shea (Eds.), New Directions in Educational Technology (pp. 23-31). Berlin: Springer-Verlag. [Abstract & PDF]

1993

VanLehn, K. (1993). Cascade: A simulation of human learning and its applications. Invited paper. In S. P. Brna, S. Ohlsson, & H. Pain (Eds.), Artificial Intelligence in Education, 1993: Proceedings of AI-ED 93 (pp. 1-3). Charlottesville, VA: Association for the Advancement of Computing in Education.

VanLehn, K., & Jones, R.M. (1993). Integration of analogical search control and explanation-based learning of correctness. In S. Minton (Ed.), Machine Learning Methods for Planning (pp. 273-315). Los Altos, CA: Morgan Kaufmann. [abstract & PDF]

VanLehn, K., & Jones, R.M. (1993). Learning by explaining examples to oneself: A computational model. In S. Chipman & A. Meyrowitz (Eds.), Cognitive Models of Complex Learning (pp. 25-82). Boston, MA: Kluwer Academic. [abstract & PDF]

1995

Martin, J., & VanLehn, K. (1995). A Bayesian approach to cognitive assessment. In P. Nichols, S. Chipman, & R. L. Brennan (Eds.). Cognitively Diagnostic Assessment (pp. 141-165). Hillsdale, NJ: Erlbaum.

Polk, T. A., VanLehn, K., & Kalp, D. (1995). ASPM2: Progress toward the analysis of symbolic parameter models. In P. Nichols, S. Chipman, & R. L. Brennan (Eds.), Cognitively Diagnostic Assessment (pp. 127-139). Hillsdale, NJ: Erlbaum.

1996

Ploetzner, R., & VanLehn, K. (1996). Direkt und indirekt vermittelte Transferleistungen beim Erwerb konzept-uellen Wissens in der Physik [Direct and indirect mediated transfer during the acquisition of conceptual physics knowledge]. In R. H. Kluge & M. May (Eds.), Proceedings of the Second Meeting of the German Cognitive Science Society (pp. 116-118). Hamburg: Department of Psychology, University of Hamburg.

VanLehn, K. (1996). Cognitive skill acquisition. In J. T. Spence (Ed.), J. M. Darly & D. J. Foss (Assoc. Eds.), Annual Review of Psychology: Vol. 47 (pp. 513-539). Palo Alto, CA: Annual Reviews, Inc.  [abstract & PDF]

VanLehn, K. (1996). Conceptual and meta learning during coached problem solving. Invited paper. In C. Frasson, G. Gauthier & A. Lesgold (Eds.), ITS’96: Proceedings of the Third International Conference on Intelligent Tutoring Systems. New York: Springer-Verlag.

1997

Ploetzner, R. & VanLehn, K. (1997). Direkt und indirekt vermittelte Transferleistungen beim Erwerb konzeptuellen Wissens in der Physik [Direct and indirect transfer in the acquisition of conceptual physics knowledge]. In R. H. Kluge (Ed.), Strukturen und Prozesse intelligenter Systeme [Structures and processes of intelligent systems]. Wiesbaden, Germany: Deutscher Universitats Verlag.

1999

VanLehn, K. (1999). AI and Education. In R.A. Wilson & F. Keil (Eds.), MIT Encyclopedia of Cognitive Science (pp. 9-10).

VanLehn, K. (1999). Introductory Remarks: Three phases in the development of a new paradigm. In D. Kayser & S. Vosniadou (Eds.), Modeling Changes in Understanding: Case Studies in Physical Reasoning (pp. 15-21). Amsterdam, Netherlands: Elsevier.

2000

Rosé, C., Freedman, R., Jordan, P., Ringenberg, M., Roque, A., Schulze, K., Shelby, R., Siler, S., Treacy, D., VanLehn, K., Weinstein, A., & Wintersgill, M. (2000). Conceptual Tutoring in Atlas-Andes. In Building Dialogue Systems for Tutorial Applications: Papers from the 2000 Fall Symposium (North Falmouth, MA), demo session. AAAI Technical Report FS-00-01.

2001

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 (pp. 41-48). New Brunswick, NJ: Association for Computational Linguistics. [abstract & PDF]

Murray, R. C., VanLehn, K., & Mostow, J. (2001). A decision-theoretic architecture for selecting tutorial discourse actions. Presented at the AI-ED 2001 Workshop on Tutorial Dialogue Systems, San Antonio, TX, May 20, 2001. [abstract & PDF]

2002

Jordan, P. & VanLehn, K. (2002). Discourse processing for explanatory essays in tutorial applications. In Proceedings of the 3rd SIGdial Workshop on Discourse and Dialogue. Philadelphia, PA. [abstract & PDF]

Rosé, C., VanLehn, K., & Jordan, P. (2002). Can we help students with a high initial competency? In C. P. Rosé & V. Aleven (Eds.), ITS2002 Workshop on Empirical Methods for Tutorial Dialogue Systems (pp. 91-99). San Sebastian, Spain. [abstract & PDF]

Siler, S., Rosé, C., Frost, T., VanLehn, K., & Koehler, P. (2002). Evaluating knowledge construction dialogs (KCDs) versus minilessons within Andes2 and alone. In ITS2002 Workshop on Empirical Methods for Tutorial Dialogue Systems (pp. 9-15). San Sebastian, Spain. [abstract & PDF]

2003

Rosé, C. P., Litman, D., Bhembe, D., Forbes, K., Silliman, S., Srivastava, R., & VanLehn, K. A. (2003). Comparison of Tutor and Student Behavior in Speech Versus Text Based Tutoring. In Proceedings of the HLT-NAACL Workshop on Building Educational Applications Using Natural Language Processing.

Rosé, C. P., Roque, A., Bhembe, D., & VanLehn, K. (2003). A hybrid text classification approach for analysis of student essays. In J. Burstein & C. Leacock (Eds.), Proceedings of the HLT-NAACL 03 Workshop: Building Educational Applications Using Natural Language Processing (pp. 68-75). Edmonton, Alberta, Canada: Association for Computational Linguistics. [abstract & PDF]

Rosé, C. P., VanLehn, K. & NLT Group. (2003). Is human tutoring always more effective than reading?: Implications for tutorial dialogue systems. In Proceedings of AIED Workshop on Tutorial Dialogue Systems: With a View Towards the Classroom: Vol. VI. [abstract & PDF]

2005

Makatchev, M., Hall, B., Jordan, P., Pappuswamy, U., & VanLehn, K. (2005). Mixed language processing in the Why2-Atlas tutoring system. In Proceedings of the Workshop on Mixed Language Explanations in Learning Environments, AIED2005. Amsterdam, Netherlands.

2007

VanLehn, K. (2007).  Getting out of order: Avoiding lesson effects through instruction.  In F. E. Ritter, J. Nerb, E. Lehtinen & T. M. O’Shea (Eds.), In order to learn: How the sequences of topics affect learning. pp. 169-180.  Oxford University Press.

Hausmann, R. G. M. & VanLehn, K. (2007).  A test of the interaction hypothesis: Joint explaining vs.  self-explaining.  In D. McNamara & G. Trafton (Eds.) Proceedings of the 29th Annual Conference of the Cognitive Science Society. pg. 1770 New York, NY: Erlbaum. [PDF 32KB]

VanLehn, K. , Jordan, P. & Litman, D. (2007).  Developing pedagogically effective tutorial dialogue tactics: Experiments and a testbed.   Proceedings of SLaTE Workshop on Speech and Language Technology in Education pp 17-20, Farmington, PA

2008

Ringenberg, M. A. & VanLehn, K. (2008).  Does solving ill-defined physics problems elicit more learning than conventional problem solving? In B. P. Woolf, E. Aimeur, R. Nkambou & S. Lajoie (Eds) Doctoral Consortium, Intelligent Tutoring Systems: 9th International Conference, ITS2008. [97 KB PDF]

Hausmann, R. G., van de Sande , B. & VanLehn, K. (2008). The content of self-explanations while studying incomplete worked-out examples  In B. C. Love, K. McRae & V. M. Sloutsky (Eds.), Procedings of the 30th Annual Conference of the Cognitive Science Society.  (pg. 1680).  New York, NY: Erlbaum.

Nokes, T. J., VanLehn, K. & Belenky, D. M. (2008) Coordinating principles and examples through analogy and explanation (abstract only).  Proceedings of the 30th Annual Conference of the Cognitive Science Society. (pg. 2365).  New York, NJ: Erlbaum.  [11 KB PDF]

Moss, J., Schunn, C.D., VanLehn, K., Schneider, W., McNamara, D. S., & Jarbo, K. (2008). They were trained, but they did not all learn: Individual differences in uptake of learning strategy training  In B. C. Love, K. McRae & V. M. Sloutsky (Eds.), Procedings of the 30th Annual Conference of the Cognitive Science Society.  (pg. 1389).  New York, NY: Erlbaum.

VanLehn, K. (2008). Intelligent tutoring systems for continuous, embedded assessment. In C. A. Dwyer (Ed.), The future of assessment: Shaping teaching and learning.  pp. 113-138 New York, NY: Erlbaum. [Abstract & PDF]

VanLehn, K. (2008) The Interaction Plateau: Answer-based Tutoring < Step-based Tutoring = natural tutoring (abstract only).  Intelligent Tutoring Systems 2008. p. 7 Berlin: Springer-Verlag  [70 KB PDF]

2009

VanLehn, K. & van de Sande, B. (2009).  Acquiring conceptual expertise from modeling: The case of elementary physics.   In K. A. Ericsson (Ed.) The Development of Professional Performance:  Toward Measurement of Expert Performance and Design of Optimal Learning Environments. pp. 356-378. Cambridge, UK: Cambridge University Press. [Abstract & PDF]

2010

VanLehn, K. & van de Sande, B., Shelby, R. & Gershman, S. (2010).  The Andes physics tutoring system: An experiment in freedom. In R. Nkambou & J. Bourdeau (Eds.) Advances in Intelligent Tutoring Systems. pp. 421-446. Berlin: Springer-Verlag.

2011

VanLehn, K. & Burleson, W., Chavez Echeagaray, M-E., Christopherson, R., Gonzalez Sanchez, J., Hastings, J., Hidalgo Pontet, Y. & Zhang, L. (2011).  The affective meta-tutoring project: How to motivate students to use effective meta-cognitive strategies. In T. Hirashima et al. (Eds.) Proceedings of the 19th International Conference on Computers in Education. Chiang Mai, Thailand: Asia-Pacific Society for Computers in Education. [244 Kb PDF]

2012

VanLehn, K. & Chi, Min (2012).  Adaptive expertise as acceleration of future learning: A case study. [0.9 MB Preprint] In P. J. Durlach & A. M. Lesgold (Eds.) Adaptive Technologies for Training and Education. pp. 28-45. Cambridge, UK: Cambridge University Press.

2013

VanLehn, K. (2013).  Evaluation of assessment and guidance technologies in the context of conceptual physics essay writing. Paper presented at the American Educational Research Association, San Francisco, CA, April 28, 2013.

Zhang, L., Burleson, W., Chavez-Echeagary, M. E., Girard, S., Gonzalez-Sanchez, J., Hidalgo-Pontet, Y. & VanLehn, K. (2013). Evaluation of a meta-tutor for constructing models of dynamic systems   In H. C. Lane, K. Yacef, J. Mostow & P. Pavlik (Eds), Artificial Intelligence in Education: 16th International Conference, AIED 2013, 666-669.

2016

VanLehn, K., Cheema, S., Wetzel, J. Z & Pead, D. (2016). Some less obvious features of classroom orchestration systems   In L. Lin & R. Atkinson (Eds), Educational Technologies: Challenges, Applications and Learning Outcomes. pp. 73-94. Nova Scientific Publishers. [Preprint]

2019

VanLehn, K. (2019). What do human tutors do? In J. E. Laird & K. Gluck (Eds.), Interactive Task Learning: Agents, Robots, and Humans Acquiring New Tasks through Natural Interactions. pp. 195-211, Frankfurt am Main, Germany & Cambridge, MA: Ernst Strüngmann Forum & MIT Press. [preprint]

VanLehn, K., Burkhardt, H., Cheema, S., Pead, D., Schoenfeld, A. H., & Wetzel, J. (2019). How can FACT encourage collaboration and self-correction? In K. Millis, D. Long, J. Magliano, & K. Wiemer (Eds.), Deep comprehension: Multi-disciplinary approaches to understanding, enhancing and measuring comprehension (pp. 114-127). New York, NY: Routledge. [preprint]

Other Publications

VanLehn, K. (1985) Review of Michalski, Carbonell & Mitchell’s “Machine Learning: An Artificial Intelligence Approach.” Artificial Intelligence, 25 , 233-239.

VanLehn, K. (1986) Review of J. R. Anderson’s “The Architecture of Cognition.” Artificial Intelligence, 28, 2, 235-240.

VanLehn, K. (2017) What Do Human Tutors Do? Unpublished manuscript prepared for the Ernst Strüngmann Forum: Interactive Task Learning: Agents, Robots, and Humans Acquiring New Tasks through Natural Interactions, May 21-26, 2017.

Technical Reports

VanLehn, K. (1973). SAIL User Manual (AIM-204, CS-373), Stanford, CA: Stanford Artificial Intelligence Laboratory, Computer Science Department, Stanford University.

VanLehn, K. (1978). Determining the scope of English quantifiers (Technical report AI-TR-483). Artificial Intelligence Laboratory, Massachusetts Institute of Technology.

VanLehn, K. (1985). Acquiring procedural skills from lesson sequences (Xerox PARC Technical Report ISL-11). Palo Alto, CA: Xerox PARC.

VanLehn, K. (1983). Felicity conditions for human skill acquisition: Validating an AI-based theory (Xerox PARC Technical Report CIS-21). Palo Alto, Ca: Xerox PARC. (Out of print, but copies can be ordered from University Microfilm, 300 N. Zeeb Road, Ann Arbor, MI 48106.)

VanLehn, K. (1985). Theory reform caused by an argumentation tool (Xerox PARC Technical Report ISL-11). Palo Alto, CA: Xerox PARC.

VanLehn, K. (1987). Changing the layers of mind (Technical Report PCG-9). Pittsburgh, PA: Dept. of Psychology, CMU.

Garlick, S., & VanLehn, K. (1987). Deriving descriptions of the mind: A rationale for serial models of cognition (Technical report PCG-7). Pittsbrgh, PA: Dept. of Psychology, CMU. [abstract & PDF]

VanLehn, K., & Ball, W. (1987). Understanding algebra equation solving strategies (Technical report PCG-2). Pittsburgh, PA: Dept. of Psychology, CMU. [abstract & PDF]

VanLehn, K., & Ball, W. (1987). Flexible execution of cognitive procedures (Technical report PCG-5). Pittsburgh, PA: Dept. of Psychology, CMU. [abstract & PDF]

VanLehn, K., & Ball, W. (1987). A version space approach to learning grammars (Technical Report PCG-3). Pittsburgh, PA: Dept. of Psychology, CMU.

Kowalski, B., & VanLehn, K. (1988). Induction of partial orders beats classification (Technical report AIP-56). Pittsburgh, PA: Dept. of Psychology, CMU. [abstract & PDF]

VanLehn, K. (1988). Felicity conditions for cognitive skill acquisition: Tutorial instruction does not need them (Technical Report PCG-13). Pittsburgh, PA: Depts. of Psychology and Computer Science, CMU.

VanLehn, K. (1989). Problem solving and cognitive skill acquisition (Technical Reports AIP-32 and PCG-14). Pittsburgh, PA: Dept. of Psychology, CMU.

Chi, M. T. H., Glaser, R., & VanLehn, K. (1990). On line assessment of individual expertise (Technical Report PCG-33). Pittsburgh, PA: LRDC, University of Pittsburgh.

Polk, T. A., Newell, A., & VanLehn, K. (1990). Fitting symbolic parameter models: a proposal for the ASPM system (Technical report PCG-31). Pittsburgh, PA: LRDC, University of Pittsbugh.

Polk, T. A., Newell, A., & VanLehn, K. (1991). Analysis of symbolic parameter models (ASPM): A new model-fitting technique for the cognitive sciences (Technical Report PCG-34). Pittsburgh, PA: LRDC, University of Pittsburgh

Ur, S., & VanLehn, K. (1991). Applying machine learning techniques to choosing a sorting algorithm (Technical Report PCG-38). Pittsburgh, PA: LRDC, University of Pittsburgh.

VanLehn, K. (1992). A model of long-term learning: Integration of knowledge acquisition and knowledge compilation (Technical Report PCG-36). Pittsburgh, PA: LRDC, University of Pittsburgh. [abstract & PDF]

Bloom, C., Villano, M., VanLehn, K., Jones., J., Watson, P. K., & O’Bannon, M. (1992). Application of artificial intelligence technologies to training systems: Computer-based diagnostic testing system (Technical report AL-TR-1992-0072). Brooks Air Force Base, TX: Armstrong Laboratory Human Resources Directorate, Technical Training Research Division.

Martin, J., & VanLehn, K. (1994). Discrete factor analysis: Learning hidden variables in Bayesian networks (Technical report LRDC-ONR-94-1). Pittsburgh, PA: LRDC, University of Pittsburgh. [abstract & PDF]

VanLehn, K., Chi, M. T. H., Baggett, W., & Murray, R. C. (1995). Progress Report: Towards a theory of learning during tutoring, Progress report for Office of Naval Research Cognitive Sciences Division (Technical report LRDC-ONR-95-1). Pittsburgh, PA: LRDC, University of Pittsburgh.

Invited addresses, tutorials, workshops and colloquia
(since 1996 only)

1996

“Extensions to model-tracing tutoring.” First CMU Symposium on Technology Enhanced Learning, Carnegie Mellon University, Pittsburgh, PA, May, 1996.

“Conceptual and meta-learning during coached problem solving.” Keynote address, Third International Conference on Intelligent Tutoring Systems, Montreal, Canada, June, 1996.

“Andes: A physics homework tutor.” The 1996 Navy Research and Education Symposium on Command, Control, Communications, Computers, and Intelligence (C4I), United States Naval Academy, Annapolis, MD, August, 1996.

“Bayesian student modeling.” ARPA CAETI contractors meeting, Berkeley, CA, November, 1996.

1997

“Learning scientific problem solving.” School of Education Colloquium, University of California, Berkeley, CA, April, 1997.

“Human and computer tutors.” Center for Advanced Study in the Behavioral Sciences, Stanford, CA, May, 1997.

“Andes: A homework helper for physics.” Stanford Research Institute, Stanford, CA, May, 1997.

“The three phases of cognitive science research.” European Science Foundation’s final conference on Learning in Humans and Machines, Mannheim, Germany, October, 1997.

“A pedagogically useful theory of physics learning.” Keynote address, European Science Foundation’s final conference on Learning in Humans and Machines, Mannheim, Germany, October, 1997.

1998

“What makes a tutorial event effective?” Twentieth Conference of the Cognitive Science Society, Madison, Wisconsin, August, 1998.

“Student modeling from conventional test data : A Bayesian approach without priors.” 4th Intelligent Tutoring Systems Conference ITS'98, San Antonio, Texas, September, 1998

“Assessment based on a Bayesian-network tutoring system,” National Academy of Science, Committee on the Future of Assessment, Woods Hole, MA, October, 1998.

“An introduction to CIRCLE,” Third International Conference for the Learning Sciences, Georgia Tech, Atlanta, GA, December 1998.

1999

“Constructive learning environments.” Division C highlighted panel, American Educational Research Association, Montreal, CA, April 1999.

“Microadaptation: Human tutors do it, and so should computer tutors.” Computer Human Interaction, CHI99, May, 1999.

2000

“CIRCLE: Center for Interdisciplinary Research on Constructive Learning Environments,” Fourth International Conference for the Learning Sciences, Ann Arbor, Michigan, June 2000

“How might NL improve learning gains, motivation and/or learning experience?” AAAI, Fall Symposium, Austin, TX, July 2000

“Andes: An intelligent homework helper for physics,” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June. 2000

“Fading and deepening: The next steps for Andes and other model-tracing tutors,” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

“ITS tools for natural language dialogue: A domain-independent parser and planner,” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

“Why: An intelligent tutoring system with natural language understanding.”

“DT Tutor: A decision-theoretic, dynamic approach for optimal selection of tutorial actions.” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

“Further results from the evaluation of an intelligent computer tutor to coach self-explanation.” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

“The conceptual helper: An intelligent tutoring system for teaching fundamental physics concepts.” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

“A reification of a strategy for geometry theorem proving.” Intelligent Tutoring Systems, 5th International Conference, Montreal, Canada, June, 2000

2001

“Why2, a Conceptual Physics Tutor.” Office of Naval Research/MURI Conference, Memphis, TN, May, 2001

“An introduction to the Andes, Atlas and Why2 research,” Microsoft, Seattle, Washington, April, 2001

“Olae: A Bayesian performance assessment for complex problem solving.” National Council on Measurement in Education, Seattle, WA, April2001.

“Tools for Authoring Tutorial Dialogue Knowledge,” AI-ED, San Antonio, TX, May 2001

2002

“Andes and other other applications of Bayesian inference to training.” Defense Science Board Task Force on Training for Future Conflicts.February 14-15, 2002, Arlington, VA.

“The architecture of Why2-Atlas: A coach for qualitative physics essay writing.” ITS2002, Biaritz, France, June 2002.

“Minimally invasive tutoring of complex physics problem solving.” ITS2002, Biaritz, France, June 2002.

2003

“The advantages of explicitly representing problem spaces,” Keynote Speaker, User Modeling ’03 Conference, June, 2003.

“The impact of natural language tutoring on cognitive skill acquisition.” Computer Science Department and CLASS, Columbia University, New York, NY, July 2003.

“The Andes project,” Office of Naval Research Contractor's Conference, University of Mississippi, Starksville, MS, May, 2003

“Natural Language Tutoring,” Institute for Scientific and Technological Research, Povo, Italy, August, 2003.

2004

“Why2: Tutors that teach mental models using natural language dialog.” Office of Naval Research/MURI Conference, University of Memphis, Memphis, TN, May, 2004.

“Tutoring scientific explanations via natural language dialogue,” Information Technology Research Grantee Meeting, Crystal City, VA, June 2004.

2005

“The Andes Intelligent Tutoring System,” IADIS Virtual Multi Conference on Computer Science and Information Systems (MCCSIS 2005): eLearning. April 20, 2005.

2006

“Representation and reasoning for deeper natural language understanding in a physics tutoring system.”  FLAIRS, Melbourne Beach, FL, May, 2006.

“A natural language tutorial dialogue system for physics”  FLAIRS, Melbourne Beach, FL, May 2006

“The Pittsburgh Science of Learning Center: Studying robust learning in LearnLab classrooms”   International Conference on Cognition and Neural Science, Boston, MA, May 2006.

“When is tutorial dialogue more effective than cheaper instruction?”  Serious Games Workshop, Institute for Creative Technology, Marina del Rey, CA, August 2006.

 2007

“Expertise in elementary physics, and how to acquire it.” The Development of Professional Performance:  Approaches to Objective Measurement and Designed Learning Environments, Orlando, FL, March 2007.

 “What’s in a step?  Toward general, abstract representations of tutoring system log data.”  User Modelling Conference, Corfu, Greece, June 28, 2007.

“Combining Bayesian Networks and Formal Reasoning for Semantic Classification of Student Utterances”  AI in Education Conference,  Marian Del Rey, CA, July 13, 2007.

“Step-level assistance while solving complex physics problems can significantly improve semester-long learning” CRESMET, Arizona State University, Tempe, AZ, August 13, 2007

“Can natural language tutoring systems be as effective as human tutors?” School of Computing and Informatics, Arizona State University, Tempe, AZ, August 14, 2007.

“Cognitive Analysis of Student Learning Using LearnLab”  Physics Education Research Conference, Greensboro, NC, August 2, 2007.

“Is the “self” of self-explanation important?  In vivo experiments.”  European Association of Research on Learning and Instruction (EARLI) conference, Budapest, Hungary, August 30, 2007.

“Can natural language tutoring systems be as effective as human tutors?”  Stanford Research Institute, Menlo Park, CA,  September 20, 2007.

“Why will you see so many null results for learning gains in these talks?”  Speech and Language Technology in Education, Farmington, PA, October 2, 2007.

 2008

“When Is Tutorial Dialogue More Effective Than Less Interactive Instruction?  .” American Educational Research Association, New York, NY,  March 28, 2008.

“Intelligent Tutoring Systems: What Do We Do Next?”  Fordham University, New York, NY, March 27, 2008.

“Designing for conceptual understanding: College physics”,  Interplay 2008, Pittsburgh, PA,  March 10, 2008.

“The interaction plateau: Answer-based tutoring < Step-based tutoring = Natural tutoring”  Keynote talk, Intelligent Tutoring Systems, July, 2008.

 

  2009

“Toward a practical learning theory for step-based tutoring systems”   ARI Workshop on Adaptive Training Technologies, Charleston, SC,  March 3-5, 2009.

“Step-based tutoring systems emulate human tutors”  TII-Vanguard Conference on Learning, Washington, DC, May 9-11 2009.

“Transfer of Meta-Strategies”  AAAI Fall Symposium, Washington, DC, Novermber 10, 2009.

“Why are intelligent tutoring systems just as effective as expert human tutors?”  CERI-PALM seminar series, ASU PolyTechnic, Mesa, AZ September 23, 2009.

  2010

“Why are step-based tutoring systems almost as effective as human tutors?”  International Conference on Cognitive Modeling, Philadelphia, PA, August 6, 2010.

  2011

“The relative effectiveness of human tutoring and 3 types of computer tutoring.”  Pearson Educational Products, Boston, MA, February 17, 2011

“What granularity is best for tutoring? Implications for learning, assessment and classrooms”  Educational Testing Service, Princeton, NJ, March 25, 2011

“Now that ITS are as effective as human tutors, how can they become even better?”  International Conference on Computers in Education, Chiang Mai, Thailand, Nov. 30, 2011

  2012

Intelligent tutoring systems (ITS) for online learning.  Conversations on Quality: A Symposium on K-12 Online Learning, MIT, Jan. 24, 2012

“Now that Intelligent Tutoring Systems are as effective as human tutors, how can they become even better?”  Cognitive Science Institute, University of Colorado at Boulder, Feb. 17, 2012

“Now that Intelligent Tutoring Systems are as effective as human tutors, how can they become even better?”  Optimal Teaching Workshop, University of California at San Diego, May 4, 2012

“Now that Intelligent Tutoring Systems are as effective as human tutors, how can they become even better?”  Plenary talk at the Annual Meeting of the Cognitive Science Society, Sapporo, Japan, August 2, 2012

Neal Stephenson's 'The Diamond Age or, A Young Lady's Illustrated Primer' in the Classroom.”  Emerging Technology & Science and the Imagination Conference, Scottsdale, AZ October 26, 2012

  2013

Can intelligent tutoring systems become more effective than human tutors?  Learning Sciences Institute, ASU, Tempe, AZ, January, 2013

Dragoon: An ITS Authoring System for Scientific and Engineering Modeling.  Office of Naval Research, Arlington, VA, April 19, 2013

Evaluation of assessment and guidance technologies in the context of conceptual physics essay writing.  American Educational Research Association Conference, San Francisco, CA, April 28, 2013

Dragoon: An ITS Authoring System for Scientific and Engineering Modeling   DODEA, Arlington, VA, August 22, 2013.

How to build tutoring systems that are almost as effective as human tutors.   The Education Group, Massachusetts Institute of Technology, Cambridge, MA, June 12, 2013.

How to build tutoring systems that are almost as effective as human tutors.   Cognitive Science Department, Rensselaer Polytechnic Institute, Troy, NY, Nov. 6, 2013.

  2014

Handheld teacher dashboards: The potential impact of real-time formative assessment on classroom culture.   The Center for Advanced Technology in Schools Conference, Redondo Beach, CA, April 30, 2014.

An ITS Authoring System for Scientific and Engineering Modeling.   Intelligent Tutoring Systems Conference, Honolulu, HI, June 5, 2014.

Comments on papers on model-based instruction & assessment.   The 9th International Conference on Conceptual Change, Bologna, Italy, Aug. 25, 2014.

  2015

An ITS Authoring System for Scientific and Engineering Modeling.   Office of Naval Research, Arlington, VA, Jan. 26, 2015.

FACT: Formative Assessment using Computational Technology.   Mathematics Design Collaboration, Phoenix, AZ, Feb. 23, 2015.

Dashboards in FACT.   National Council on Measurement in Education: Annual Conference, Chicago, IL, April 19, 2015.

Dashboards in FACT.   Council of Chief State School Officers: Annual Conference, Atlanta, GA, October 28, 2015.

Classroom Centaurs: A new genre of educational technology.   IBM T. J. Watson Research Center, Yorktown Heights, NY, December 15, 2015.

  2016

Formative Assessment of Complex Mathematical Exploration during Class: Can FACT reduce the analytic load on the teacher without harming the classroom processes? Human Development Department Colloquia, Columbia Teachers College, New York, March 1, 2016

Can FACT reduce the analytic load on the teacher without harming classroom processes? Google, New York, NY, March 2, 2016

A Cognitive Solution to the Assignment of Blame Problem in Knowledge Tracing. American Educational Research Association, Washington, DC, April 9, 2016

Dragoon: An ITS Authoring System for Scientific and Engineering Modeling. Cognition and Instruction Seminar, Columbia Teachers College, New York, NY, April 19, 2016

A Dragoon solution to the assignment of blame problem in Knowledge Tracing. Learning Analytics Seminar Series, Columbia Teachers College, New York, NY, May 4, 2016

  2017

Mathematical model construction activities are feasible and effective when student use the Dragoon tutoring system, PIER Talk, Dept. of Psychology, Carnegie-Mellon University, Pittsburgh, PA, March 6, 2017

The FACT classroom orchestration system, PIER EdBag, Dept. of Psychology, Carnegie-Mellon University, Pittsburgh, PA, March 7, 2017

Dragoon is a effective tutoring system for system dynamics model construction, AERA Structured Poster session: Supporting Science as a Modeling Practice in the Classroom through the Lens of NGSS, San Antonico, TX, April 28, 2017

Discussant, AERA Session: Automation and Data Analytics to Inform Teaching and Learning, San Antonico, TX, April 30, 2017

What do human tutors do?, The Ernst Strüngmann Forum: Interactive Task Learning: Agents, Robots, and Humans Acquiring New Tasks through Natural Interactions, Frankfurt, Germany, May 21-26, 2017

Can FACT reduce the analytic load on the teacher without harming classroom processes?, The 5th Annual Midwest Meeting on Mathematical Thinking, University of Minnesota, Minneapolis, MN, July 8, 2017

Intelligent Tutoring Systems, Symposium on Building America's Skilled Technical Workforce: The Role of Digital Tutors, The National Academies of Science, Engineering and Medicine, The National Academy, Washington, DC, October 26, 2017

FACT: An orchestration system that encourages math self-correction, National Institute of Education, Singapore, November 11, 2017

  2018

How tutoring systems analyze student performance 2nd REASON Interdisciplinary Spring School 2018, Ludwig-Maximilians-Universität, München, Germany, March 6, 2018

The FACT classroom orchestration system: Helping teachers effectively enact individual, small-group and whole-class activities, Keynote, The Sixth Computational Behavior Science summit, Wuhan, China, Oct. 7, 2018

Educational technology 2018: A framework, Keynote, The Sixth Computational Behavior Science summit, Wuhan, China, Oct. 7, 2018

Educational Technology 2018: A framework, Talk presented to the Graduate College, Central China Normal University, Wuhan, China, Oct. 8, 2018

When teachers orchestrate a complex lesson that integrates individual, small-group and whole-class activities, how can technology help without disrupting?, Colloquium, Tsinghua Institute of Education, Tsinghua University, Beijing, China, Oct. 15, 2018

When teachers orchestrate a complex lesson that integrates individual, small-group and whole-class activities, how can technology help without disrupting?, Webinar, Alelo, Oct. 9 & 10, 2018

  2019

The future of AI in education: From knowledge-based systems to data-drive approaches. Learning Analytics Conference, Tempe, AZ March 7, 2019

21. The Future of Classroom Work: Automated Teaching Assistants, Future of Work: The Human-Technology Frontier, Arlington, VA, April 5, 2019

 

Research funding (* indicates current funding)

ONR N00014-82-C-0067 “Competitive argumentation in computational theories of cognition” $297,190 over three years, from January 1, 1982 to May 31, 1985. Joint with John Seely Brown.

ONR N00014-85-C-0688 “Impasses: Keys to a unified theory of the acquisition and mental representation of cognitive skills” $97,110 over 12 months, from June 15, 1985 to June 14, 1986. Joint with John Seely Brown.

ONR N00014-86-K-0349 “The psychological reality of meta-level skill acquisition and problem solving” $139,171 over 15 months, from June 15, 1986 to October 31, 1987.

ONR/DARPA N00014-86-K-0678 “Learning, teaching and discovery in artificial intelligence and psychology” $11,575,053 over 5 years, from September 15, 1986 to September 14, 1991. Joint with 9 other faculty.

ONR N00014-88-K-0086 “A model of self-explanation in skill-acquisition” $338,181 over 3 years, from January 1, 1988 to December 31, 1991.

ONR N00014-91-J-1529 “Fitting of symbolic parameter cognitive models” $93,662 for 2 years, from February 15, 1991 to February 14, 1993.

ONR N00014-91-J-1532 “On-line assessment of individual expertise” $258,080 for 2 years, from February 15, 1991 to February 14, 1993. Joint with Michelene T. H. Chi & Robert Glaser. Renewed: $161,000 for 1 year, from February. 15, 1993 to June 30, 1994.

ONR N00014-92-J-1945 “A model of long-term learning: Integration of knowledge acquisition and knowledge compilation” $116,990 for 15 months, from July 1, 1992 to November 15, 1993.

ONR N00014-93-1-1161 “Toward a model of interactive learning” $74,192 over 3 years, from September 1, 1993 to August 30, 1996.

ONR N00014-94-1-0674 “How people learn from a tutor” $353,814 over 2.5 years, from May 1, 1994 to November 15, 1996.

ARPA N66001-95-C-8367 “A student modeling module based on Bayesian reasoning” $193,344 over 2 years, from August 31, 1995 to August 30, 1997.

ONR N00014-95-1-0950 “Example-based tutoring systems” $118,205 over 3 years, from May 1, 1995 to April 30, 1998.

AFOSR F49620-96-1-0180 “Tutoring the planning of solutions”$336,126 over 3 years, from May 1, 1996 to April 30, 1999.

Micro Analysis and Design Inc “Real Time Intelligent Coaching for Command and Control” $32,000 from August 1,1998 to March 31, 1999.

National Institutes of Health 1-R25-CA63548-01A2 “Educational resource for tumor heterogeneity” $861,878 over 4 years, from September 1, 1995 to August 31, 1999. PI: Roger S. Day.

A. W. Mellon & Russell Sage Foundation 49500654 “Simulating work” $1,000,000 over 3 years, from January 1, 1996 to December 31, 1999. Co-PIs: Michelene T. H. Chi & Gaea Leinhardt.

ONR N00019-13-1-0017 and ONR N00014-96-1-0260 “Andes: A tutoring system for classical physics” $2,400,444 over 8.5 years, from January 1, 1996 to October, 2002.

NSF 9720359 “CIRCLE: Center for Interdisciplinary Research on Constructive Learning Environments” $4,997,797 over 5 years, from January 1, 1998 to December 31, 2002. PI, with 4 Co-PIs at the University of Pittsburgh and 4 at CMU.

ONR N00014-98-1-0467 “Decision-theoretic Tutoring Systems for Coached Problem Solving” $88,196.00 over 3 years, from April 1, 1998 to March 31, 2001.

ONR N00014-00-1-0600 “Why2000: An intelligent tutoring system with natural language understanding” $4,713,451 over 5 years, beginning April 30, 2000 to April, 30, 2005. Joint with Art Graesser at the University of Memphis.

NSF EIA-0325054 “Tutoring scientific explanation via natural language dialogue” $2,500,000 over 5 years beginning January 1, 2004. Co-PIs: Michelene Chi, Diane Litman, Pamela Jordan and Carolyn Rosé.

NSF 0354420 “Pittsburgh Science of Learning Center: Studying Robust Learning with Learning Experiments in Real Classrooms” $14,898,917 over 5 years, October 2004 – September 30, 2009. Joint with Ken Koedinger at Carnegie Mellon University.

NSF IIS-0705243 “Supporting students attending User Modeling 2007 Conference”  $14,880 from July 1, 2007 to June 30, 2008.

DARPA “Biologically accelerated learning technology” $1,114,781 from March 1, 2007 to August 31, 2008.  PI: Walter Schneider; Co-PIs: Chris Schunn, Natasha Tokowicz & Kurt VanLehn.

NSF 0354420 via CMU to ASU 0354420 “PSLC LearnLab Course” $354,044  from August, 2008 to September 30, 2009.

Aptima 0574-1504 “Adaptive Device for Adaptive Performance Training (ADAPT)” $171,000 from June 29, 2009 to January 31, 2012.

NSF DRL-0910221 “Deeper modeling via affective meta-tutoring” $963,675 from September 1, 2009 to August 31, 2013. REU supplements $63,444 from June 28, 2010 to August 31, 2013.

NSF 0836012 via CMU to ASU “PSLC LearnLab Course” $499,413  from October 1, 2009 to Sept. 30, 2012.

NSF IIS-1123823 “Students authoring intelligent tutoring systems for constructing models of ill-defined dynamic systems” $549,871  from October 1, 2011 to Sept. 30, 2015.

NSF DUE-1140901 “A Meta-cognitive Approach to Teaching Organic Chemistry from Fundamental Principles” $199,269   from April 1, 2012 to March 31, 2015.

*Bill and Melinda Gates Foundation OPP1061281 "Formative Assessment with Computational Technologies (FACT)" $5,567,457 from November, 2012 to December 31, 2018

ONR N00014-13-C-0029 "ITS Authoring System for Scientific Engineering Modeling Technologies" $1,471,270 from November 1, 2012 to December 31, 2014

US Army, W911NF-04-D-0005, Delivery Order No. 0041, to University of Southern California, "Personal Assistant for Life Long Learning (PAL3)" Subcontract from University of Southern California to ASU for $400,000 from August 1, 2014 to January 1, 2016

ONR N00014-12-C-0643 "Integration of Intelligent Systems for Electronics" Subcontract from University of Memphis to ASU for $330,000, from May 1, 2015 to June 30, 2017

NSF DUE-1525197 "An Intelligent Tutoring System for Organic Chemistry" $591,958   from September 15, 2015 to August 31, 2019. PI: Ian Gould

*NSF IIS-1628782 "DIP: Graphical Model Construction by System Decomposition: Increasing the Utility of Algebra Story Problem Solving" $1,346,298 (+ $16,000 REU)   from September 1, 2016 to August 31, 2020.

*NSF 1840051 "FW-HTF: The future of classroom work: Automated Teaching Assistants" $1,478,882   from September 1, 2018 to August 31, 2021.

NSF 1936997 "RAISE: C-Accel Pilot - Track B2 (National Talent Ecosystem): Safe Skill-Aligned On-The-Job Training with Autonomous Systems" PI: Siddharth Srivastava $998,588   from September 1, 2019 to March 31, 2020.

Teaching

Fall, 1985 “Cognitive Processes and Problem Solving'' Co-taught with Prof. Herbert Simon. Senior level undergraduates and first-year graduate course, CMU Psychology.

Spring, 1986 “Machine Learning'' Graduate seminar, CMU Computer Science.

Fall, 1986 “Cognitive Core Course'' Coordinator, with Prof. Marcel Just. Graduate course, CMU Psychology.

Fall, 1986 “Cognitive Processes and Problem Solving'' Co-taught with Prof. Herbert Simon. Senior level undergraduates and first-year graduate course, CMU Psychology.

Spring, 1987 “Introduction to AI'' Co-taught with Prof. Tom Mitchell. Junior-level undergraduate course, CMU Computer Science.

Fall, 1987 “Cognitive Processes and Problem Solving'' Co-taught with Prof. Herbert Simon. Senior level undergraduates and first-year graduate course, CMU Psychology.

Spring, 1988 “The mind of the expert'' Graduate seminar, CMU Psychology.

Fall, 1988 “Introduction to AI'' Junior level undergraduate course, CMU Computer Science.

Spring, 1989 “Cognitive Psychology'' Sophomore level undergraduate course, CMU Psychology.

Spring, 1989 “Intelligence Architectures'' Graduate seminar, CMU Computer Science.

Fall, 1989 “Introduction to Machine Learning'' Graduate seminar, CMU Computer Science.

Spring, 1990 “Cognition and Instruction'' Graduate seminar, CMU Psychology.

Fall, 1990 “Problem Solving and Planning'' Graduate course (CS 2730), Pitt Computer Science.

Fall, 1991 “Problem Solving and Planning'' Graduate course (CS 2730), Pitt Computer Science.

Fall, 1992 “Artificial Intelligence Programming'' Undergraduate course (CS 1583), Pitt Computer Science.

Fall, 1993 “Artificial Intelligence Programming'' Undergraduate course (CS 1583), Pitt Computer Science.

Spring, 1994 “Introduction to computer science: Pascal'' Undergraduate course (CS 0407), Pitt Computer Science.

Fall, 1994 “Problem solving and planning'' Graduate course (CS 2730/ISSP 2170), Pitt Computer Science/Intelligent Systems Program.

Spring, 1996 “Problem solving and planning'' Graduate course (CS 2730/ISSP 2170), Pitt Computer Science/Intelligent Systems Program.

(Fall, 1996 & Spring 1997: On Sabbatical)

Fall, 1997 “Foundations of AI” Graduate course (CS 2701/ISSP 2160), Pitt Computer Science/Intelligent Systems Program.

Fall, 1998 “Foundations of AI” Graduate course (CS 2701/ISSP 2160), Pitt Computer Science/Intelligent Systems Program.

Fall, 1999 “Intelligent Tutoring Systems” Graduate course (CS 3710 / ISSP 3565), Pitt Computer Science/Intelligent Systems Program.

Spring, 2000 “Independent study” (ISP 2000) Tutoring 5 students in Prolog and Lisp programming.

Fall, 2000 “Foundations of AI” Graduate course (CS 2701/ISSP 2160), Pitt Computer Science/Intelligent Systems Program.

Summer, 2001 “CIRCLE Summer School”. 1-week intensive course

Spring, 2002 “AI Application and Development” Undergrad course (CS 1573), Pitt Computer Science

Fall, 2002, “Discrete Mathematics for Computer Science” Undergrad course (CS0441), Pitt computer Science.

Spring, 2005, “Applications of Artificial Intelligence” Undergrad course (CS1573), Pitt Computer Science.

Fall, 2006 & 2007, “Tutoring Interest Group (TIG)”  Unofficial paper reading course that met biweekly.

Fall, 2009, “Tutoring Interest Group (TIG)”  Unofficial paper reading course (3 graduate students) that met biweekly.

Spring, 2010, “Principles of programming languages.” Undergraduate (CSE340) ASU Computer Science core course.

Fall 2011, “The ASU Experience” Undergraduate (ASU-101-CSE) ASU Computer Science course.

Spring 2012, “Introduction to Informatics” (CPI101) ASU Informatics course.

Fall 2010, Fall 2011, Spring 2014, “Intelligent Interactive Instructional Systems” Undergraduate (CPI494) and graduate (CSE598) ASU Computer Science course.

Spring 2009, Spring 2010, Spring 2011, Fall 2012, Fall 2013, Fall 2014, Fall 2015, Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020. “Problem solving and decision making.” Undergraduate (CPI360) ASU Informatics course.

Thesis supervision

Kowalski, Bernadette: CMU CS M. S., 1988. Research staff member, NASA Ames, Mountain View, CA.

Ur, Sigalit: Pitt ISP M. S., 1993. Research staff member, IBM Haifa Research Lab, Haifa, Israel

Rubin, Jonathan: Pitt ISP M. S., 1994. (took industrial position in Boston)

Karyadi, Iwan: Pitt CS M. S., 1996. (returned to India)

Albacete, Patricia: Pitt ISP Ph. D., 1999. Consultant, Monroeville, PA.

Conati, Cristina: Pitt ISP Ph. D., 1999 Professor, Department of Computer Science, U. of British Columbia, Vancouver.

Matsuda, Norboru: Pitt ISP Ph. D., 2005, Associate Professor, Department of Computer Science, North Carolina State University

Lane, Chad: Pitt CS Ph. D., 2005, Associate Professor, College of Education, Indiana University

Siler, Stephanie: Pitt Psychology Ph.D., 2005, Research Associate, CMU

Murray, R. Charles: Pitt ISP Ph. D., Ph.D., 2005, Research Scientist, Carnegie Learning, Pittsburgh, PA.

Chi, Min: Pitt ISP Ph. D, 2009, Associate Professor, Computer Science, North Carolina State University.

Jung, Sung-Young:  Pitt ISP Ph D, 2011.

Ranganathan, Rajagopalan :  ASU CS MS, 2011.

Sorensen, Asael :  ASU CS MS, 2011.

Zhang, Lishan:  ASU CS Ph.D., 2015, Assistant Professor, Central China Normal University. Wuhan, China

Beerman, Eric:  ASU CS MS., 2015, Researcher, Google.

Grover, Sachin:  ASU CS MS., 2015, PhD student, ASU.

Koesler, Refika :  ASU CS Ph.D., 2020. Google

Ritchey, ChristiAnne:  ASU EduTech Ph.D., 2018.

Viswanathan, Sree:  ASU CS Ph.D., expected 2020.

Shahrokhian , Bahar:  ASU Computer Engineering Ph.D., expected 2022.

Post-doc mentoring

Jones, Randolf M. : Professor and Dept. Chair, Computer Science Dept., Colby College, Waterville, Maine;and VP, Soar Technologies, Inc.

Martin, Joel: Research Associate, Interactive Information Group, Institute for Information Technology, National Research Council of Canada, Ottawa, CA.

Baggett, William: Fedex, Memphis TN.

Niu, Zhendong: Deputy Dean & Professor, Software School, Beijing Institute of Technology, China.

Gertner, Abigail: Research Scientist, MITRE Corporation, Bedford, MA.

Rosé, Carolyn: Professor, CMU HCII.

Jordan, Pamela: Research Associate, LRDC.

Muldner, Katarzyna: Associate Professor, Institute of Cognitive Science, Carleton University, Ottawa, Canada.

Girard, Sylvie.

Cheema, Salman: Researcher, Microsoft Research, Redmond, WA.

Wetzel, Jon: Research Associate, ASU.

Dissertation committees

Zhang, Guojun: CMU Psychology Ph. D., 1985.

Singley, Kevin: CMU Psychology Ph. D., 1986.

Kessler, Claudius: CMU Psychology Ph. D., 1988.

Minton, Steve: CMU Computer Science Ph. D., 1988.

Etzioni, Oren: CMU Computer Science Ph. D., 1990.

Koedinger, Ken: CMU Psychology Ph. D., 1990.

Fisher, Carolanne: CMU Psychology Ph. D., 1991.

Leng, Bing: Pitt Computer Science Ph. D., 1993.

Provost, Foster: Pitt Computer Science Ph. D., 1993.

Shahidi, Anoosh: Pitt ISP Ph. D., 1993.

Joslin, David: Pitt ISP Ph. D., 1995.

Lee, Yongwon: Pitt Computer Science Ph. D., 1995.

Slotta, James D. : Pitt Psychology Ph. D., 1996.

Ryan, Robert: Pitt Psychology Ph. D., 1996.

Aleven, Vincent: Pitt ISP Ph. D., 1997.

Lu, Tsai-Ching: Pitt Information Sciences Ph. D., 1999.

Siler, Stephanie: Pitt Psychology MS, 2000.

Heffernan, Neil: CMU Ph. D., 2001.

Roscoe, Rod: Pitt Psychology Ph. D., 2007.

Jacobson, Jeffery: Pitt Information Sciences Ph. D., 2008.

Freed, Natalie: ASU CSE MS, 2010.

Priyamvada Tripathi: ASU CSE Ph.D., 2011.

Elodie V. Billionniere: ASU CSE Ph.D., 2011.

Andre Denham: ASU EduTech Ph.D., 2013.

Tejas Budukh: ASU CSE M.S., 2013.

Arun Reddy Nelakurthi: ASU CSE M.S., 2014.

Ritesh Samala: ASU CSE M.S., 2015.

Nguyen Ha Vo: ASU CSE M.S., 2015.

Matthew Scott Dexheimer: ASU CSE M.S., 2017.

Po-Kai Huang: ASU CSE M.S., 2017.

Shaik, Faizaan: ASU CSE M.S., 2019.

Maria-Elena Chavez-Echeagaray, ASU CS Ph.D., 2019.

Andreea Danielescu: ASU CS Ph.D., 2019.

Nicola Lubold: ASU CS Ph.D., 2019.

Yihan Lu: ASU CS Ph.D., 2020.

Shang Wang: ASU CS Ph.D., 2019.

Editorships and Editorial board memberships

Associate Editor, Interactive Learning Environments, 1987 to 1997.

Editorial board member, Cognitive Science, 1989 to 1998.

Editorial board member, Journal of the Learning Sciences, 1989 to 1998

Editorial board member, Machine Learning, 1994 to 1997.

Senior Editor, Cognitive Science, 1998 to 2001.

Editorial board member, International Journal of Learning Technology, 2004 to 2006.

Editorial board member, Cognition and Instruction, 2008 to present.

Editorial board member, International Journal of Artificial Intelligence in Education, 1996 to present.

International Service

Articles reviewer for Artificial Intelligence, Machine Learning, Cognitive Science, Cognition and Instruction, Cognition, Cognitive Psychology, Journal of the Learning Sciences, IEEE Transactions on Learning Technologies, and International Journal of AI in Education.

Proposal reviewer for NSF, AFOSR and other agencies.

Secretary/Treasurer of the Cognitive Science Society, 1985 to 1988.

Organizer and editor, Architectures for Intelligence: the Twenty-Second Annual Carnegie Symposium on Cognition, CMU, May, 1988.

Governing board member, Cognitive Science Society, 1990 to 1997.

Co-organizer, Cognition and Instruction Workshop, Pittsburgh, PA, March 1991.

Program committee member, AAAI84, AAAI90, AAAI91, IJCAI91, AIEd92, ML93, AIEd01, ITS02, AIEd03, ITS04, AIEd05, ITS06, AIEd07, ITS08, ICCE08, AIEd09, ITS10, AIEd11, ITS12, L@S13, AIEd13, ITS14, AIEd15, ITS16, AIEd17, ITS2018, ICLS18, CogSci18, AIEd18, AIEd19, AIEd20.

Program Committee Chair, Intelligent Tutoring Systems Conference, 2000.

Principal member, Institute of Educational Sciences (IES) Mathematics and Science Education Research Panel, 2008 to 2011

Co-organizer, Scalability Workshop at the 2009 International Conference on Artificial Intelligence in Education.

Co-organizer, Global resouces for online education workshop, Tempe, AZ, April, 2009.