Publications of the Why2000 project

• Project Documents
• Atlas
• Auto Tutor
• Computer Modelling of Collaborative Problem-solving Dialogues
• Computer Modelling of Tutorial Dialogues
• ITS
• Latent Semantic Analysis
• Robust Parsing
• Tutoring Studies

Project Documents (Top)

• 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]


• 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]


• 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. (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]


• 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]


• Jordan, P., Makatchev, M., and ,U., 2005. Relating Student Text to Ideal Proofs: Issues of Efficiency of Expression.In Proceedings of AIED 2005 Workshop on Mixed Language Explanation in Learning Environments (XLANG), pp. 43-50.


• 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.


• 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]


• 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]


• 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]


• 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]


• 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]


• Jordan, P., (2004). Using Student Explanations as Models for Adapting Tutorial Dialogue, In Proceedings of the 17th International FLAIRS Conference, pp 905-910.


• 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., 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.


• 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]


• Jordan, P., Makatchev, M. and Pappuswamy, U., (2003). Extended Explanations as Student Models for Guiding Tutorial Dialogue. In Proceedings of AAAI Spring Symposium on Natural Language Generation in Spoken and Written Dialogue, pp 65-70.


• Wilson, R., 2003. A Method for Comparing Fluency Measures and its Application to ITS Natural Language Question Generation. In Proceedings of AAAI Spring Symposium on Natural Language Generation in Spoken and Written Dialogue. Presentation slides.


• 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., 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]


• 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]


• 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]


• Jordan, P. and Siler, S. (2002). Student Initiative and Questioning Strategies in Computer-Mediated Human Tutoring Dialogues. In Proceedings of ITS 2002 Workshop on Empirical Methods for Tutorial Dialogue Systems, 2002.


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


• 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.P., (2000). Facilitating the Rapid Development of Language Understanding Interfaces for Tutoring Systems,Proceedingsof the AAAI Fall Symposium on Building Tutorial Dialogue Systems


• 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]

Atlas(Top)

• 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]


• 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.
• 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]


• Freedman, R. (2000). Plan-Based Dialogue Management in a Physics Tutor. Proceedings of the Sixth Applied Natural Language Processing Conference (ANLP 2000), Seattle, WA.


• Freedman, R. (2000). Using a Reactive Planner as the Basis for a Dialogue Agent. Proceedings of the Thirteenth Florida Artificial Intelligence Research Symposium (FLAIRS 2000), Orlando, FL.


• 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]


• Freedman, R. (1999). Atlas: A Plan Manager for Mixed-Initiative, Multimodal Dialogue. AAAI-99 Workshop on Mixed-Initiative Intelligence, Orlando
  

AutoTutor(Top)

• Graesser, A.C., Olney, A., Haynes, B.C., & Chipman, P. (2005).  AutoTutor: A cognitive system that simulates a tutor that facilitates learning through mixed-initiative dialogue.  In C. Forsythe, M.L. Bernard, and T.E. Goldsmith (Eds.), Cognitive systems: Human cognitive models in systems design.  Mahwah, NJ: Erlbaum. [Word Doc]


• Graesser, A.C., Person, N., Lu, Z., Jeon, M.G., & McDaniel, B. (2005).  Learning while holding a conversation with a computer.  In L. PytlikZillig, M. Bodvarsson, & R. Bruning (Eds.), Technology-based education: Bringing researchers and practitioners together (pp. 143-167).  Greenwich, CT: Information Age Publishing. [PDF]


• Graesser, A.C., Lu, S., Jackson, G.T., Mitchell, H., Ventura, M., Olney, A., & Louwerse, M.M. (2004).  AutoTutor: A tutor with dialogue in natural language.  Behavioral Research Methods, Instruments, and Computers, 36, 180-193. [PDF]  


• Jackson, G.T., Person, N.K., and Graesser, A.C. (2004) Adaptive Tutorial Dialogue in AutoTutor. Proceedings of the workshop on Dialog-based Intelligent Tutoring Systems at the 7th International conference on Intelligent Tutoring Systems. Universidade Federal de Alagoas, Brazil, 9-13.


• Jackson, G.T., Ventura, M.J., Chewle, P., Graesser, A.C., and the Tutoring Research Group (2004). The Impact of Why/AutoTutor on Learning and Retention of Conceptual Physics. .  In J.C. Lester, R.M. Vicari, & F. Paraguacu (Eds.), Intelligent Tutoring Systems 2004 (pp. 501-510).  Berlin, Germany: Springer.


• Franceschetti, D., Adcock, A., & Graesser, A.A. (2003). Analysis of strategies in expert tutoring dialog for use in intelligent tutoring system development. In R. Alterman and D. Hirsh (Eds.), Proceedings of the 25rd Annual Conference of the Cognitive Science Society (pp. 1). Boston, MA: Cognitive Science Society.


• Graesser, A.C. (2003). AutoTutor and other conversational agents that scaffold learning. In F. Schmalhofer, R.M. Young, and G. Katz (Eds.), Proceedings of the European Cognitive Science Society 2003 (p. 11). Mahwah, NJ: Erlbaum.


• Graesser, A.C., Jackson, G.T., Mathews, E.C., Mitchell, H.H., Olney, A.,Ventura, M., Chipman, P., Franceschetti, D., Hu, X., Louwerse, M.M., Person, N.K., & TRG (2003). Why/AutoTutor: A test of learning gains from a physics tutor with natural language dialog. Proceedings of the 25rd Annual Conference of the Cognitive Science Society (pp. xx). Mahwah, NJ: Erlbaum.


• Graesser, A.C., Moreno, K., Marineau, J., Adcock, A., Olney, A., & Person, N. (2003). AutoTutor improves deep learning of computer literacy: Is it the dialog or the talking head? In U. Hoppe, F. Verdejo, and J. Kay (Eds.), Proceedings of Artificial Intelligence in Education. (pp, 47-.54). Amsterdam: IOS Press. (finalist for outstanding paper award).


• Person, N., & Graesser, A.C. (2003). Fourteen facts about human tutoring: Food for thought for ITS developers. In V. Aleven, U. Hoppe, J. Kay, R. Mizoguchi, H. Pain, F. Verdejo, and K. Yacef (Eds.), AIED2003 Supplemental Proceedings (pp. 335-344). Sydney, Australia: University of Sydney School of Information Technologies. [Word Doc] 


• Susarla, S., Adcock, A., Van Eck, R., Moreno, K., & Graesser, A.C. (2003). Development and evaluation of a lesson authoring tool for AutoTutor. In V. Aleven, U. Hoppe, J. Kay, R. Mizoguchi, H. Pain, F. Verdejo, and K. Yacef (Eds.), AIED2003 Supplemental Proceedings (pp. 378-387). Sydney, Australia: University of Sydney School of Information Technologies. [PDF]


• Jackson, G.T., Mathews, E.C., Lin, K., Olney, A., Graesser, A.C. (2003). Modeling student performance to enhance the pedagogy of AutoTutor. In the Proceedings of the 2003 conference on User Modeling.


• Louwerse, M.M., Graesser, A.C. and the Tutoring Research Group (2003). Language use in intelligent tutoring systems: mixed-initiative dialog in AutoTutor. In A.K. Noor (Ed.), Proceedings of workshop on Advanced learning technologies and learning networks and their impact on future aerospace workforce (pp. 251-276). Hanover, MD: NASA Center for Aerospace Information (NASA/CP-2003-212437).


• Graesser, A.C., Person, N., & Hu, X. (2002). Improving comprehension through discourse processes. New Directions in Teaching and Learning, 89, 33-44.


• Louwerse, M., Graesser, A., Hu, X., Person, N. (2002) The Role of Intelligent Tutoring Systems in Education: An Overview of AutoTutor. In Proceedings of the Society for Information Technology & Teacher Education. Association for the Advancement of Computing in Education.


• Person, N. P., & Graesser, A.C. (2002). Pedagogical agents and tutors. In J. W. Guthrie (Ed.), Encyclopedia of Education. New York: Macmillan.


• Graesser, A. C., Hu, X., Olde, B. A., Ventura, M., Olney, A., Louwerse, M., Franceschetti, D. R., Person, N.K. ( 2002, August). Implementing latent semantic analysis in learning environments with conversational agents and tutorial dialog. In W. G. Gray and C. D. Schunn (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society (pp 37). Mahwah, NJ: Erlbaum.


• Louwerse, M., Graesser, A., Hu, X., Person, N. (2002) The Role of Intelligent Tutoring Systems in Education: An Overview of AutoTutor. In Proceedings of the Society for Information Technology & Teacher Education. Association for the Advancement of Computing in Education.


• Louwerse, M.M., Graesser, A.C., Olney,A.,& TRG (2002). Good computational manners: Mixed-initiative dialog in conversational agents. Proceedings of the AAAI Fall Symposium on Computer Etiquette


• Marineau, J., Olney, A., Louwerse, M., Person, N., Olde, B., Susarla, S., Chipman, P., Graesser, A.C., & TRG (2002). AutoTutor’s log files and categories of language and discourse. In C. P. Rose and V. Eleven (Eds.), Workshop Proceedings of Empirical Methods for Tutorial Dialogue Systems at IRS 2002 (pp. 85-92). San Sebastian, Spain.


• Olde, B. A., Franceschetti, D.R., Karnavat, Graesser, A. C. & the Tutoring Research Group (2002, August). The right stuff: Do you need to sanitize your corpus when using latent semantic analysis? Proceedings of the 24th Annual Conference of the Cognitive Science Society (pp. 708-713). Mahwah, NJ: Erlbaum.


• Person, N.K., Erkel, M., Graesser, A.C., & TRG (2002). AutoTutor passes the bystander Turing test. In M. Driscoll and T. C. Reeves (Eds.), Proceedings for E-Learning 2002: World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education (pp. 778-782). Montreal, Canada: AACE.


• Person, N.K., Graesser, A.C., & the Tutoring Research Group (2002). Human or computer?: AutoTutor in a bystander Turing test. In S. A. Cerri, G. Gouarderes, & F. Paraguacu (Eds.), Intelligent Tutoring Systems 2002 (pp. 821-830). Berlin, Germany: Springer.


• Graesser, A.C., VanLehn, K., Rose, C., Jordan, P., & Harter, D. (2001). Intelligent tutoring systems with conversational dialogue. AI Magazine, 22, 39-51.


• Person, N.K., Graesser, A.C., Kreuz, R.J., Pomeroy, V., & TRG (2001). Simulating human tutor dialog moves in AutoTutor. International Journal of Artificial Intelligence in Education , 12, 23-39.[Word Doc]


• Person, N. K., Graesser, A. C., Bautista, L., Mathews, E. C., & the Tutoring Research Group (2001). Evaluating Student Learning Gains in Two Versions of AutoTutor. In J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.) Artificial intelligence in education: AI-ED in the wired and wireless future (pp. 286-293). Amsterdam, IOS Press.


• Rajan, S., Craig, S.D., Gholson, B., Person, N.K., Graesser, A.C., & TRG (2001). AutoTutor: Incorporating backchannel feedback and other human-like conversational behaviors into an intelligent tutoring system. International Journal of Speech Technology, 4, 117-126.


• Franceschetti, D.R., Karnavat, A., Marineau, J., McCallie, G.L., Olde, B.A., Terry, B.L., & Graesser, A.C. (2001). Development of physics test corpora for latent semantic analysis. Proceedings of the 23rd Annual Conference of the Cognitive Science Society (pp. 297-300). Mahwah, NJ: Erlbaum.


• Graesser, A.C., Hu, X., Susarla, S., Harter, D., Person, N., Louwerse, M., Olde, B., & the TRG (2001). AutoTutor:An intelligent tutor and conversational tutoring scaffold.Papers from the Workshop on "Tutorial Dialog Systems" at the Artificial Intelligence in Education 2001 Conference (pp.47-49). San Antonio, TX.


• Graesser, A.C., Person, N., Harter, D., & TRG (2001). Teaching tactics and dialog in AutoTutor. International Journal of Artificial Intelligence in Education.


• Jackson, T., Mueller, J., Person, N., & Graesser, A.C. (2001). Assessing the pedagogical effectiveness and conversational appropriateness in three versions of AutoTutor. In J.D. Moore, C.L. Redfield, and W.L. Johnson (Eds.) Artificial Intelligence in Education: AI-ED in the Wired and Wireless Future (pp. 263-267). Amsterdam: OIS Press.


• Person, N.K., Graesser, A.C., Bautista, L., Mathews, E., & TRG (2001). Evaluating student learning gains in two versions of AutoTutor. In J.D. Moore, C.L. Redfield, and W.L. Johnson (Eds.) Artificial Intelligence in Education: AI-ED in the Wired and Wireless Future (pp. 286-293). Amsterdam: OIS Press.


• Graesser, A., Wiemer-Hastings, P., Wiemer-Hastings, K., Harter, D.,Person, N., & The Tutoring Research Group. (2000). Using Latent Semantic Analysis to evaluate the contributions of students in AutoTutor. Interactive Learning Environments, 8 ,149-169.


• Marineau, J., Wiemer-Hastings, P., Harter, D., Olde, B., Chipman, P.,Karnavat, A., Pomeroy, S., Graesser, A.C., & TRG (2000). Classification of speech acts in tutorial dialog. Proceedings of the workshop on modeling human teaching tactics and strategies at the Intelligent Tutoring Systems 2000 conference. University of Quebec at Montreal, 65-71.


• Graesser, A., Wiemer-Hastings, K., Wiemer-Hastings, P., Kreuz, R., &the Tutoring Research Group (1999). AutoTutor: A simulation of a human tutor. Journal of Cognitive Systems Research, 1,35-51.


• Wiemer-Hastings, P., Graesser, A., Harter, D., and the Tutoring Research Group, (1998). The foundations and architecture of Autotutor. Proceedings of the 4th International Conference on Intelligent Tutoring Systems, San Antonio, Texas (pp. 334-343).  Berlin: Springer-Verlag.


• Graesser, A., Franklin, S., Wiemer-Hastings, P., and the Tutoring Research Group (1998). Simulating smooth tutorial dialogue with pedagogical value, Proceedings of the 11th International Florida Artificial Intelligence Research Symposium, Menlo Park, CA: AAAI Press.

Computer Modelling of Collaborative Problem-solving Dialogues(Top)

• Jordan, P. (2003). Feature Sharing in the Generation and Interpretation of in Dialogue.In Proceedings of AAAI Spring Symposium on Natural Language Generation in Spoken and Written Dialogue March, pp 58-64. [PDF]


• Jordan, P. (2002). Tag-sets for the generation of nominals in 1:58 PM 6/2/2009 collaborative dialogue.  Presented at ISLE Workshop on Dialogue Tagging for Multi-Modal Human Computer Interaction.[PDF]


• Jordan, P. (2001).  Contextual Influences on Attribute Selection for Repeated Descriptions. In Information Sharing, edited by Kees van Deemter and Rodger Kibble, CSLI Publications, pp 295-328. [PDF]


• Jordan, P. (2000).  Can Nominal Expressions Achieve Multiple Goals?:  An Empirical Study.    In the Proceedings of ACL2000, Hong Kong, pp 142-149.[PDF]


• Jordan, P. (2000).  Influences on Attribute Selection in Redescriptions: A Corpus Study   In the Proceedings of CogSci2000, pp 250-255.[PDF]


• Di Eugenio, B., Jordan, P., Thomason, R.H., and Moore, J.D. (2000). The Agreement Process: An Empirical Investigation of Human-human Computer-mediated Collaborative Dialogues."  International Journal of Human-Computer Studies, vol 53, no 6, pgs 1017-1076, December 2000. [PDF]

Computer Modelling of Tutorial Dialogues(Top)

• Freedman, R., Zhou, Y., Glass, M., Kim, J.H. Evens, M. W. (1998). Using Rule Induction to Assist in Rule Construction for a Natural-Language Based Intelligent Tutoring System. Proceedings of the Twentieth Annual Conference of the Cognitive Science Society, Madison, WI. [Postscript File]


• Kim, J., Freedman, R., and Evens, M. W. (1998). Relationship between Tutorial Goals and Sentence Structure in a Corpus of Tutoring Transcripts. Proceedings of the Ninth Midwest Artificial Intelligence and Cognitive Science Conference (MAICS '98), Dayton, OH. [Postscript File]


• Kim, J.H., Freedman, R., and Evens, M.W. (1998). Responding to Unexpected Student Utterances in Circsim-Tutor v. 3: Analysis of Transcripts. Proceedings of the Eleventh Florida AI Research Symposium (FLAIRS '98), Sanibel Island, FL. [Postscript File]


• Rosé, C. P. Di Eugenio, B., and Moore, J. D. (1999). "A Dialogue Based Tutoring System for Basic Electricity and Electronics." Proceedings of AI in Education.


• Rosé, C.P., Moore, J.D., VanLehn, K., Allbritton, D. (1999). A Comparative Evaluation of Socratic versus Didactic Tutoring, LRDC Tech Report LRDC-BEE-1.


• Zhou, Y., Freedman, R., Glass, M., Michael, J. A., Rovick, A. A., and Evens, M. W. (1999). What Should the Tutor Do When the Student Cannot Answer a Question? Proceedings of the Twelfth Florida AI Research Symposium (FLAIRS '99), Orlando, FL. [PDF]


• Zhou, Y., Freedman, R., Glass, M., Michael, J. A., Rovick, A. A., and Evens, M. W. (1999). Delivering Hints in a Dialogue-Based Intelligent Tutoring System. Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI '99), Orlando,FL. [PDF]

ITS (Top)

• VanLehn, K., Freedman, R., Jordan, P. Murray, C., Osan, R., Ringenberg, M., Rosé, C., Schulze, K., Shelby, R., Treacy, D., Weinstein, A., and Wintersgill, M. (2000). Fading and Deepening: The Next Steps for Andes and Other Model-Tracing Tutors.   In Intelligent Tutoring Systems: Fifth International Conference (ITS 2000), Montreal.  Springer-Verlag Lecture Notes in Computer Science.


• Conati, C., and VanLehn K. (1999). A student model to assess self-explanation while learning from examples. In Proceedings of UM '99, 7th International Conference on User Modeling, Banff, Canada. [Word Doc]


• Conati, C., and VanLehn, K. (1999). Teaching meta-cognitive skills: implementation and evaluation of a tutoring system to guide self-explanation while learning from examples. To appear in Proceedings of AIED '99, 9th World Conference of Artificial Intelligence and Education, Le Mans, France.[Word Doc]


• 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., Jones, R.M. & Chi, MTH. (1992). A model of the self explanation effect.  Journal of the Learning Sciences, 2(1), pp. 1-60.

Latent Semantic Analysis (Top)

• Wiemer-Hastings, P. (1999) How Latent is Latent Semantic Analysis? Proceedings of the 16th International Joint Conference on Artificial Intelligence, Stockholm, Sweden, Aug 1999, pp. 932-937. San Francisco: Morgan Kaufmann.


• Wiemer-Hastings, P., Wiemer-Hastings, K., and Graesser, A., (1999). Improving an intelligent tutor's comprehension of students with Latent Semantic Analysis. AI in Education 1999, Le Mans, France. July 19 - 23, 1999, pp. 535-542. Amsterdam: IOS Press


• Wiemer-Hastings, P., Wiemer-Hastings, K., and Graesser, A. (1999). Approximate natural language understanding for an intelligent tutor, Proceedings of the 12th International Florida Artificial Intelligence Research Symposium, (pp.192-196). Menlo Park, CA: AAAI Press.

Robust Parsing (Top)

• 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]


• Lavie, A. and Rosé, C.P. (2003). Optimal Ambiguity Packing in Context-Free Parsers with Interleaved Unification. H. Bunt, J. Carroll and G. Satta (eds.), Current Issues in Parsing Technologies Kluwer Academic Press. [PDF]


• Rosé, C.P. and Lavie, A. (2002). A Domain Independent Approach for Efficiently Interpreting Ungrammatical Utterances. The Journal of Natural Language Engineering.[Postscript File]


• Rosé, C.P. and Lavie, A. (2001). Balancing Robustness and Efficiency in Unification-Augmented Context-Free Parsers for Large Practical Applications, Robustness in Language and Speech Technology, J. C. Junqua and G. Van Noord (eds.), Veronis and Ide Series, Kluwer Academic Press. [PDF]


• Lavie, A. and Rosé, C.P. (2000). Optimal Ambiguity Packing in Context-Free Parsers with Interleaved Unification, Proceedings of the International Workshop on Parser Technologies. [Postscript File]


• Rosé, C.P., (2000). A Framework for Robust Semantic Interpretation, 1st Meeting of the North American Chapter of the Association for Computational Linguistics. [PDF]


• Rosé, C.P., (2000). A Syntactic Framework for Semantic Interpretation, Proceedings of the ESSLLI Workshop on Linguistic Theory and Grammar Implementation. [PDF]


• Rosé, C.P. and Lavie, A. (1999). LCFLEX: An Efficient Robust Left-Corner Parser. LRDC Technical Report LRDC-NLU-1.


• Rosé, C.P. (1999). A Genetic Programming Approach for Robust Language Interpretation. Advances in Genetic Programming, Volume 3. L. Spencer et al. (eds.) 

Tutoring Studies (Top)

• >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., 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]


• 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]


• Rosé, C.P., Di Eugenio, B., Moore, J.D. (1999). A Dialogue Based Tutoring System for Basic Electricity and Electronics, Proceedings of AI in Education.


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


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

Last update: July 21, 2009.