Note: An electronic version of this document with working links to all papers is at http://nth.wpi.edu/pubs_and_grants/papers/cv.htm
A18 |
Journal paper sited as one of the best of the year in the journal. It was selected by the editors to appear in the 2009-2010 IEEE Computer Society Publications Sampler. It had earlier been selected at the featured article of that month’s publication. Feng, M., Heffernan, N.T., Heffernan, C., Mani, M. (2009). Using Mixed-Effects Modeling to Analyze Different Grain-Sized Skill Models.. IEEE Transactions on Learning Technologies, vol. 2, no. 2, pp. 79-92, Apr.-June 2009. Featured Article of 8 Article in the edition (Based on PP8 andWP15) |
A17 |
Best Paper First Authored by a Student (Zach Pardos) at the 2nd International Educational Data Mining Conference. Pardos, Z.A., Heffernan, N.T. (2009). Determining the Significance of Item Order In Randomized Problem Sets. In Barnes, Desmarais, Romero & Ventura (Eds) Proc. of the 2nd International Conference on Educational Data Mining. pp. 111-120. ISBN: 978-84-613-2308-1. |
A16 |
Honorable Mention for the Best Paper First Authored by a student at the Artificial Intelligence in Education Conference in Brighton England. The conference rejected over 60% of the paper, so getting one of two honorable mentions out of a set of approximately 25 papers is impressive. Razzaq, L. & Heffernan, N. (2009) To Tutor or Not to Tutor: That is the Question. In Dimitrova, Mizoguchi, du Boulay & Graesser (Eds.) Proceedings of the 2009 Artificial Intelligence in Education Conference. IOS Press. pp. 457-464. |
A15 |
Cited by Provost Office for having the most number of students presenting their research at WPI Grad Day 2009, a campus wide event with about 150 graduate students presenting posters of their work. I had 9 funded students presenting. |
A14 |
Massachusetts Association of School Committee’s Annual Award for “Community Leader for Public Education”. The citation reads “Since coming to Worcester in 2002, Neil and Cristina Heffernan have generously dedicated their time, talent and boundless energy to building ASSISTments, an online math tutoring system, for Worcester middle and high school students and their teachers. This program is a magnificent tool that is distinguished by, among other facets, its clarity and easy of access and use.” http://teacherwiki.assistment.org/Awards_for_the_ASSISTment_system |
A13 |
2008 Sigma Xi Research Award for Outstanding Junior Faculty Researcher. |
A12 |
Honored for meritorious achievement as an advisor to best Major Qualifying Project in the department, Worcester Polytechnic Institute, 2007 |
A11 |
Best 3-page "Poster" Award (with my student Jason Walonoski), International Intelligent Tutoring System Conference. 2006. |
A10 |
US Patent Filed by WPI for technology used in the ASSISTment intelligent tutoring system. |
A9 |
Nominated for Best Paper First Authored by a student (with Mingyu Feng) a conference with an 11% acceptance rate; World Wed Web Conference (WWW'06). |
A8 |
I was invited to serve on the NSF/CRA CyberLearning Workshop focused on Technology-Enabled Assessment to help shape a research agenda for NSF's EHR Directorate. |
A7 |
National Science Foundation's most prestigious award for young researchers. |
A6 |
Nominated for the Massachusetts Teacher Associations “Friend of Education” award by Forest Grove Middle School for my ASSISTment project work. |
A5 |
Nominated by my department for WPI's Ambassador Award for doing an outstanding job of representing WPI to the community. |
A4 |
Best 3-page "Poster" Award (with my student Leena Razzaq), International Intelligent Tutoring System Conference. 2004. |
A3 |
US Patent #6,634,887: Methods and systems for tutoring using a tutorial model with interactive dialog (with Ken Koedinger). |
A2 |
National Academy of Education/Spencer Foundation Post-Doctoral Fellowship Award. 2002. |
A1 |
The David Marr Award for Best Student Paper Award, (with Ken Koedinger), Cognitive Science Conference. 1997. |
My research was benefited from about 9 million dollars from the National Science Foundation, U.S. Department of Education, the Office of Naval Research, the Spencer Foundation, the US Army and the Massachusetts Technology Transfer Council.
GA18 |
US Department of Education: Institute for Education Sciences. ASSISTments Meets Science Learning. PI Janice Gobert. CoPI’s Heffernan and Beck. $1.2 million. 3/09-3/2012 |
GA17 |
NSF: GK12 ““Partnership Implementing Math and Science Education: Assisting Middle School Use of Tutoring Technology. PIMSE. $2 million. 2008-13 |
GA16 |
NSF: Research Experience for Teachers Supplement. $19,500 . |
GA15 |
NSF: DRK-12. “ASSISTments Meets Inquiry” PI: Gobert. Co-PI’s Heffernan, Ruiz & Kim. Anticipated start date is 2007-Sept, 1. Five years. $1.5 million. |
GA14 |
NSF Supplement Research Experience for Undergraduates. $13,500. |
GA13 |
Massachusetts Technology Transfer Center: "Scaling up a Web-Based Formative Assessment System: Testing the Replicability of Deploying ASSISTment beyond its 'Home Town'". PI Heffernan. $40,000. (Awarded Jan 24th, 2007 ) |
GA12 |
US Department of Education: "Making Longitudinal Web-Based Assessments Give Cognitively Diagnostic Reports to Teachers, Parents & Students While Employing Mastery Learning." PI Heffernan. Co-PIs Ken Koedinger (CMU), Brian Junker (CMU), George T. Heineman (WPI), Murali Mani (WPI) & Cristina Heffernan (WPS). $2 million over 4 years commencing in 2007. |
GA11 |
National Science Foundation: CAREER Grant. "Learning About Learning" PI-Heffernan. $900,000. 2005-2010 |
GA10 |
Office of Naval Research: "Demonstrating Affordable Behavior Modeling with CTAT through Machine Learning and Human Computer Interaction Techniques." PI-Heffernan. $275,000 2005-08. |
GA9 |
US Department of Education: "Fellowships in CS to Support the Learning Sciences and Security." Awarded approximately $800,000 to support 5 PhD per year. 2006-2009. PI Matt Ward. Co-PIs Heffernan, Agu and Mani. |
GA8 |
US Dept of Education: Institute of Education Sciences: “Using Web-Based Cognitive Assessment Systems for Predicting Student Performance on State Exams” PI-Koedinger. Co-PIs Heffernan, Junker and Ritter. $1.4 million over 4 years. 2003-07. |
GA7 |
National Science Foundation: “Research Experience for K12”. $99,457. PI-Rundensteiner. Co-PI Heffernan. 2006-08 |
GA6 |
US Army: Phase 2: STTR $500,000 with Sonalysts Inc |
GA5 |
US Army: Phase 1: STTR Grant to explain to the Army how to incorporate intelligent tutoring into their warrior simulation systems. $100,000 with Sonalysts Inc. |
GA4 |
Research Advancement Program at WPI: “Programming by Demonstration for Intelligent Tutoring Systems.” PI-Heffernan. $7,500. 2003. |
GA3 |
Office of Naval Research: "Affordable Cognitive Modeling Authoring Tools using HCI Methods". PI-Heffernan. $203,304 2003-06 |
GA2 |
Office of Naval Research: "Cognitive Tutor Tools for Advanced Instructional Strategies." PI-Koedinger. Co-PI's Heffernan & Aleven. April -Sept, 30th 2002. $200,000. |
GA1 |
National Academy of Education/ Spencer Foundation: "A Comparison of Student Learning Under Multiple Conditions: Classroom Instruction, One-on-one Human Tutoring, and Different types of Computer Tutoring". PI-Heffernan. $50,000. 2002-2004 |
PRESS15 |
Worcester Telegram citation for award from School Committee. |
PRESS14 |
“U.S. gives $1.5 million for science tutoring” by Boston Globe. January 10, 2008. |
PRESS13 |
“New WPI System” by Worcester Telegram & Gazette. January 10, 2008. |
PRESS12 |
“WPI projects win NSF grants: Work on science education, tiny sensors receive funding” by Jacqueline Reis. Worcester Telegram & Gazette. August 23, 2007. |
PRESS11 |
IEEE Intelligent System “In the News” article called “Intelligence Tutors Make the Grade” that talked about ASSISTments and other Intelligent tutoring systems. By reporter Mark Ingebretsen. |
PRESS10 |
“WPI Tutor Program is Money in the Bank” by Matthew Brown. Worcester Business Journal. June 2007. http://nth.wpi.edu/press/WorBus/WBJ.htm |
PRESS9 |
“WPI receives $2M ‘assist’ for tutoring.” by Telegram & Gazette Staff. Telegram & Gazette. May 26, 2007. |
PRESS8 |
“WPI Receives $2 Million Award to Develop an Intelligent Tutoring System That Can Improve Math Education” ACM TechNews. May 23, 2007. |
PRESS7 |
“Assessing the Odds.” by Michael W. Dorsey. Transformations. Fall 2006. |
PRESS6 |
“Professor’s preparation program adds up to better MCAS math scores.” by Gretchen Weber. The Worcester Educator. Spring 2006. |
PRESS5 |
“Enter the Computer Tutor: PCs Can Help Kids Pass No Child Left Behind Tests.” by Angie C. Marek. U.S. News & World Report. November 11, 2005. |
PRESS4 |
“Schools, sponsors teaming up for TV ads.” by Jacqueline Reis Telegram & Gazette. December, 2005. |
PRESS3 |
“WPI asst. profs awarded grants.” by Mallary Jean Tenore. Telegram & Gazette. August 11, 2005 |
PRESS2 |
“‘Assistment’ makes the grade.” by Jacqueline Reis. Telegram & Gazette. May 23, 2005. |
PRESS1 |
“Pupils to get online help with MCAS.” by Clive McFarlane. Telegram & Gazette. January 14, 2004. |
RT3 |
"Prof. Neil Heffernan gets coverage by WPI": A short clip by WPI's TEAM Worcester featuring the ASSISTment system. Archived at: http://web.cs.wpi.edu/Research/trg/public/project/videos/asst_wmv.wmv |
RT2 |
580 AM,
WTAG interview by Greg Byrne, August 11th, 2005: |
RT1 |
"Prof. Neil Heffernan makes huge impact", NECN Nightly News, May 23rd, 2005: A two minute clip showing students at Forest Grove Middle School, and their math teacher, using and talking about the Assistment System. Archived at: |
Note: In the following sections all coauthors who are WPI students are italicized.
BC3 |
Pardos, Z. A., Heffernan, N. T., Anderson, B., Heffernan, L. C. (accepted but not final version) Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks. Chapter in C. Romero, S. Ventura, S. R. Viola, M. Pechenizkiy and R. S. J. Baker. Handbook of Educational Data Mining. Chapman & Hall/CRC Press. |
BC2
|
Feng, M., Heffernan, N.T., & Koedinger, K.R. (accepted but not final version). Student Modeling in an Intelligent Tutoring System. Stankov, Glavinc, Rosic. (Eds.) Intelligent Tutoring Systems in E-learning Environments: Design, Implementation and Evaluation. IGI Global. early 2010 (anticipated) (Based on W10, W11 and W12) |
BC1
|
Razzaq, Feng, Heffernan, Koedinger, Nuzzo-Jones, Junker, Macasek, Rasmussen, Turner & Walonoski. (2007). A Web-based authoring tool for intelligent tutors: Assessment and instructional assistance. In Nadia Nedjah, Luiza deMacedo Mourelle, Mario Neto Borges and Nival Nunesde Almeida (Eds). Intelligent Educational Machines. Intelligent Systems Engineering Book Series. pp.23-49. Springer Berlin / Heidelberg. http://www.springerlink.com/content/m2g23834641m858n/fulltext.pdf |
|
|
J11 |
Militello, M., & Heffernan, N. (2009). Which one is "just right"? What educators should know about formative assessment systems. International Journal of Educational Leadership Preparation, 4(3), 1-8. |
J10 |
Feng, M., Heffernan, N.T., Heffernan, C., Mani, M. (2009). Using Mixed-Effects Modeling to Analyze Different Grain-Sized Skill Models.. IEEE Transactions on Learning Technologies, vol. 2, no. 2, pp. 79-92, Apr.-June 2009. Featured Article of 8 Article in the edition (Based on PP8 and WP15) |
J9 |
Razzaq, L., Patvarczki, J., Almeida, S.F., Vartak, M., Feng, M., Heffernan, N.T. and Koedinger, K. (2009). The ASSISTment builder: Supporting the Life-cycle of ITS Content Creation. IEEE Transactions on Learning Technologies Special Issue on Real-World Applications of Intelligent Tutoring Systems. 2(2) 157-166 (Based on YRP5) |
J8 |
Feng, M., Heffernan, N.T., & Koedinger, K.R. (2009). Addressing the assessment challenge in an Intelligent Tutoring System that tutors as it assesses. The Journal of User Modeling and User-Adapted Interaction. Vol 19: p243-266. (Based on CP15) |
J7 |
Mendicino, M., Razzaq, L. & Heffernan, N. T. (2009). Improving Learning from Homework Using Intelligent Tutoring Systems. Journal of Research on Technology in Education (JRTE). Published by the International Society For Technology in Education (ISTE). Spring 2009 issue. 41:3 p 331-346. |
J6 |
Baker, R., Walonoski, J., Heffernan, T., Roll, I., Corbett, A. & Koedinger, K. (2008) Why students engage in "Gaming the System" behavior in interactive learning environments Journal of Interactive Learning Research (JILR). Chesapeake, VA: AACE. 19(2), 185-224 (Based on CP12 and PP5) |
J5 |
Razzaq, L., Heffernan, N., Feng, M., Pardos Z. (2007). Developing Fine-Grained Transfer Models in the ASSISTment System. Journal of Technology, Instruction, Cognition, and Learning, Vol. 5. Number 3. Old City Publishing, Philadelphia, PA. 2007. pp. 289-304. |
J4 |
Feng, M., Heffernan, N.T. (2007). Towards live informing and automatic analyzing of student learning: Reporting in the Assistment system. Journal of Interactive Learning Research (JILR) 18(2) pp. 207-230. Chesapeake, VA: AACE. (Based on W12) |
J3 |
Feng, M., Heffernan, N.T. (2006). Informing teachers live about student learning: Reporting in the Assistment system Technology, Instruction, Cognition, and Learning Journal Vol. 3. Number 1-2. Old City Publishing, Philadelphia, PA. 2007. (Based on W12) |
J2 |
Heffernan, Koedinger & Razzaq (2008) Expanding the model-tracing architecture: A 3rd generation intelligent tutor for Algebra symbolization.The International Journal of Artificial Intelligence in Education. 18(2). 153-178 (Builds upon CP8 and CP1-4) . |
J1 |
Heffernan, N. T., & Koedinger, K. R. (2002). Results from a Web-Based Tutor for Writing Algebra Expressions for Word-Problems Sciences et Techniques Educatives Volume 9:1-2. (This French language journal has translated our paper into French. My translation of this Journal's title is "Educational Sciences and Technology.") http://www.inrp.fr/atief/ste/ste-res-vol9.htm (Based on D1 .) |
BC4 |
Invited to contribute a book chapter to Advanced in Intelligent Tutoring Systems that will be edited by Roger Nkambou. Due Feb 21, 2010. The tentative title of the piece is Building ITSs: Authoring Systems and Applications. |
BC5 |
Invited to contribute a book chapter to a volume by Chris Dede that will focus on how teachers use ASSISTment. Anticipated coauthors Matt Militello. |
J12 |
Pardos & Heffernan. Invited to turn CP29 that won best student paper into a journal article at the International Journal of Educational Datamining. |
J13 |
Leena Razzaq- Journal of Educational Psychology. |
D1 |
Heffernan, N. T (2001) Intelligent tutoring systems have forgotten the tutor: Adding a cognitive model of human tutors. Dissertation. Computer Science Department, School of Computer Science, Carnegie Mellon University. Technical Report CMU-CS-01-127. (Pieces published as J1, CP8, CP5, CP4, and CP3) |
Note: Unlike most other disciplines where journal paper are more prestigious than conference papers, in Computer Science as a discipline, conference publications are often harder to get and more prestigious than most journal publications. These conference proceedings are stringently reviewed, with at least three reviewers.
CP39 |
Razzaq, L. & Heffernan, N. (2010 in submission) Can We Use Educational Content from the Web? International Conference on Intelligent Tutoring Systems (ITS 2010) |
CP38 |
Razzaq, L. & Heffernan, N. (2010 in submission) Hints: Is It Better to Give or Wait to be Asked? International Conference on Intelligent Tutoring Systems (ITS 2010) |
CP37 |
Pardos, Z. & Heffernan, N. (2010 in submission) Modeling Individualization in a Bayesian Networks Implementation of Knowledge Tracing. Proceedings of the International Conference on User Modeling, Adoption and Personalization. |
CP36 |
Rai, D., Beck, J., & Heffernan, N. (2010 in submission) Mily’s World: A Coordinate Geometry Learning Environment with Game-Like Properties. International Conference on Intelligent Tutoring Systems (ITS 2010) |
CP35 |
Feng, M. & Heffernan, N. T. (2010 in submission) Can We Get Better Assessment From a Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessment) and Eat It Too (Student Leaning During the Test)? International Conference on Intelligent Tutoring Systems (ITS 2010) |
CP34 |
Feng, M., Heffernan, N., Koedinger, K. (2010 in submission) Using Data Mining Findings to Aid Searching for Better Skill Models. International Conference of Intelligent Tutoring Systems (ITS 2010) |
CP33 |
Gong, Y., Beck, J., Heffernan, N. & Forbes-Summers, E. (2010 in submission) The impact of gaming (?) on learning at the fine-grained level. International Conference of Intelligent Tutoring Systems (ITS 2010). |
CP32 |
Gong, Y., Beck, J. & Heffernan, N. (2010 in submission) Comparing Knowledge Tracing and Performance Factor Analysis by Using Multiple Model Fitting. International Conference of Intelligent Tutoring Systems (ITS 2010) |
CP31 |
Baker, R., Goldstein, A. & Heffernan, N. (2010 in submission) Detecting the Moment of Learning, International Conference on Intelligent Tutoring Systems (ITS 2010). |
CP30 |
Sao Pedro, M., Gobert, J., Heffernan, N. & Beck, J. (2009). In N. A. Taatgen & H. van Rijn (Eds.), Comparing Pedagogical Approaches for Teaching the Control of Variables Strategy. Proceedings of the 31st Annual Conference of the Cognitive Science Society Austin, TX: Cognitive Science Society. |
CP29 |
Pardos, Z.A., Heffernan, N.T. (2009). Determining the Significance of Item Order In Randomized Problem Sets. In Barnes, Desmarais, Romero & Ventura (Eds) Proc. of the 2nd International Conference on Educational Data Mining. pp. 111-120. ISBN: 978-84-613-2308-1. Best Paper First-Authored by a Student. |
CP28 |
Feng, M., Beck, J., & Heffernan, N. (2009). Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions on Learning. In Barnes, Desmarais, Romero & Ventura (Eds) Proc. of the 2nd International Conference on Educational Data Mining. Pp. 51-60. ISBN: 978-84-613-2308-1. |
CP27 |
Gong, Y., Rai, D. Beck, J. & Heffernan, N. (2009) Does Self-Discipline impact students’ knowledge and learning? In Barnes, Desmarais, Romero & Ventura (Eds) Proc. of the 2ndInternational Conference on Educational Data Mining. Pp. 61-70. ISBN: 978-84-613-2308-1. |
CP26 |
Pardos, Z. & Heffernan, N. (2009) Detecting the Learning Value of Items in a Randomized Problem Set. In Dimitrova, Mizoguchi, du Boulay & Graesser (Eds.) Proceedings of the 2009 Artificial Intelligence in Education Conference. IOS Press. pp. 499-506. |
CP25 |
Razzaq, L. & Heffernan, N. (2009) To Tutor or Not to Tutor: That is the Question. In Dimitrova, Mizoguchi, du Boulay & Graesser (Eds.) Proceedings of the 2009 Artificial Intelligence in Education Conference. IOS Press. pp. 457-464. Honorable Mention for Best Paper First Authored by a Student. |
CP24 |
Feng, M., Heffernan, N. & Beck, J.(2009) Using Learning Decomposition to Analyze Instructional Effectiveness in the ASSISTment System. Proceedings of the 2009 Artificial Intelligence in Education Conference. IOS Press. pp. 523-530. |
CP23 |
Feng, M., Beck, J,. Heffernan, N. & Koedinger, K. (2008) Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standardized Test? In Baker & Beck (Eds.). Proceedings of the 1st International Conference on Education Data Mining. Montreal, Canada. pp.107-116. ISBN - 13: 9780615306292 |
CP22 |
Feng, M., Heffernan, N., Beck, J, & Koedinger, K. (2008) Can we predict which groups of questions students will learn from? In Baker & Beck (Eds.). Proceedings of the 1st International Conference on Education Data Mining. Montreal, Canada. pp.218-225. ISBN - 13: 9780615306292 |
CP21 |
Pardos, Z. A., Beck, J., Ruiz, C. & Heffernan, N. T. (2008). The Composition Effect: Conjunctive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS. In Baker & Beck (Eds.) Proceedings of the First International Conference on Educational Data Mining. Montreal, Canada. pp. 147-156. ISBN - 13: 9780615306292 |
CP20 |
Razzaq, L., Mendicino, M. & Heffernan, N. (2008) Comparing classroom problem-solving with no feedback to web-based homework assistance. In Woolf, Aimeur, Nkambou and Lajoie (Eds.) Proceeding of the 9th International Conference on Intelligent Tutoring Systems. pp. 426 -437. Springer-Verlag: Berlin. |
CP19 |
Razzaq, L., Heffernan, N. T., Lindeman, R. W. (2007). What Level of Tutor Interaction is Best? In Luckin & Koedinger (Eds.) Proceedings of the 13th Conference on Artificial Intelligence in Education. IOS Press. pp 222-229. |
CP18 |
Pardos, Z. A., Heffernan, N. T., Anderson, B. & Heffernan, C. (2007). The effect of model granularity on student performance prediction using Bayesian networks. The International User Modeling Conference 2007. (Based on W14 and W18) |
CP17 |
Feng, M., Heffernan, N. T., Mani, M., & Heffernan, C. (2007). Assessing students’ performance longitudinally: Item difficulty parameter vs. skill learning tracking. The National Council on Educational Measurement 2007 Annual Conference, Chicago. (Based upon WP15) |
CP16 |
Feng, M., Heffernan, N. & Koedinger, K.R. (2006a). Predicting state test scores better with intelligent tutoring systems: developing metrics to measure assistance required. In Ikeda, Ashley & Chan (Eds.). Proceedings of the Eighth International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 31-40. |
CP15 |
Feng, M., Heffernan, N. T., & Koedinger, K. R. (2006b). Addressing the testing challenge with a Web-based e-assessment system that tutors as it assesses. Proceedings of the Fifteenth International World Wide Web Conference (WWW-06). New York, NY: ACM Press. ISBN:1-59593-332-9. pp. 307-316. [Nominated for Best Student Paper] |
CP14 |
Heffernan N.T., Turner T. E., Lourenco A.L.N., Macasek M.A., Nuzzo-Jones G., & Koedinger K.R. (2006). The ASSISTment builder: Towards an analysis of cost effectiveness of ITS creation.Proceedings of the 19th International FLAIRS Conference, Melbourne Beach, Florida, USA. pp. 515-520. (Based on W10) |
CP13 |
Razzaq, L. & Heffernan, N.T. (2006). Scaffolding vs. hints in the Assistment system. In Ikeda, Ashley & Chan (Eds.). Proceedings of the Eight International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 635-644. |
CP12 |
Walonoski, J. & Heffernan, N.T. (2006a). Detection and analysis of off-task gaming behavior in intelligent tutoring systems. In Ikeda, Ashley & Chan (Eds.). Proceedings of the Eight International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 382-391. 2006. |
CP11 |
Razzaq, L., Feng, M., Nuzzo-Jones, G., Heffernan, N.T., Koedinger, K. R., Junker, B., Ritter, S., Knight, A., Aniszczyk, C., Choksey, S., Livak, T., Mercado, E., Turner, T.E., Upalekar. R, Walonoski, J.A., Macasek. M.A. & Rasmussen, K.P. (2005). The Assistment project: Blending assessment and assisting. In C.K. Looi, G. McCalla, B. Bredeweg, & J. Breuker (Eds.) Proceedings of the 12th Artificial Intelligence in Education, Amsterdam: ISO Press. pp. 555-562. |
CP10 |
Rose C., Donmez P., Gweon G., Knight A., Junker B., Cohen W., Koedinger K., Heffernan N.T. (2005). Automatic and semi-automatic skill coding with a view towards supporting on-line Assessment. In Looi, McCalla, Bredeweg, & Breuker (Eds.) The 12th Annual Conference on Artificial Intelligence in Education 2005, Amsterdam. ISO Press. pp. 571-578. |
CP9 |
Croteau, E., Heffernan, N. T. & Koedinger, K. R. (2004). Why are Algebra word problems difficult? Using tutorial log files and the power law of learning to select the best fitting cognitive model. In J.C. Lester, R.M. Vicari, & F. Parguacu (Eds.) Proceedings of the 7th International Conference on Intelligent Tutoring Systems. Berlin: Springer-Verlag. pp. 240-250. |
CP8 |
Heffernan, N. T. & Croteau, E. (2004). Web-Based Evaluations Showing Differential Learning for Tutorial Strategies Employed by the Ms. Lindquist Tutor. In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. Springer Lecture Notes in Computer Science. pp. 491-500. |
CP7 |
Jarivs, M., Nuzzo-Jones, G. & Heffernan. N. T. (2004). Applying machine learning techniques to rule generation in intelligent tutoring systems. In J.C. Lester, R.M. Vicari, & F. Parguacu (Eds.) In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. Springer Lecture Notes in Computer Science. pp. 541-553. |
CP6 |
Koedinger, K. R., Aleven, V., Heffernan. T., McLaren, B. & Hockenberry, M. (2004). Opening the door to non-programmers: Authoring intelligent tutor behavior by demonstration. In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference,e, Maceio, Brazil. pp.162-173. Springer Lecture Notes in Computer Science. |
CP5 |
Heffernan, N. T. (2003). Web-based evaluations showing both cognitive and motivational benefits of the Ms. Lindquist tutor In F. Verdejo and U. Hoppe (Eds) 11th International Conference Artificial Intelligence in Education. Sydney, Australia. IOS Press. pp.115-122. |
CP4 |
Heffernan, N. T., & Koedinger, K. R.(2002). An intelligent tutoring system incorporating a model of an experienced human tutor In Stefano A. Cerri, Guy Gouardères, Fábio Paraguaçu (Eds.): 6th International Conference on Intelligent Tutoring System. Biarritz, France. Springer Lecture Notes in Computer Science: pp. 596-608. |
CP3 |
Heffernan, N. T., & Koedinger, K. R. (2000). Intelligent tutoring systems are missing the tutor: Building a more strategic dialog-based tutor. In C.P. Rose & R. Freedman (Eds.) Proceedings of the AAAI Fall Symposium on Building Dialogue Systems for Tutorial Applications. Menlo Park, CA: AAAI Press. ISBN 978-1-57735-124-5. pp. 14- 19 |
CP2 |
Heffernan, N. T. & Koedinger, K. R. (1998). A developmental model for algebra symbolization: The results of a difficulty factors assessment. In M. Gernsbacher & S. Derry (Eds.) Proceedings of the Twentieth Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum. pp. 484-489. |
CP1 |
Heffernan, N. T. & Koedinger, K.R. (1997). The composition effect in symbolizing: The role of symbol production vs. text comprehension. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum. pp. 307-312. [Marr prize winner for best student paper.] |
WPI-CS-TR-08-08 – waiting for link to website
1. Baker, R. S., Corbett, A. T., Koedinger, K. R. & Schneider, M. P. (2003). A formative evaluation of a tutor for scatterplot generation: Evidence on difficulty factors. In U. Hoppe, F. Verdejo, & J. Kay (Eds.), Artificial Intelligence in Education: Shaping the Future of Learning through Intelligent Technologies, Proceedings of AI-ED 2003 (pp. 107-114). Amsterdam, IOS Press. http://www.cs.cmu.edu/~rsbaker/BCKSAIED2003Final.pdf
14. Rose, C. P., Aleven, V. & Torrey, C. (2004). CycleTalk: Supporting Reflection in Design Scenarios with Negotiation Dialogue, Proceedings of the CHI 2004 Workshop on Designing for Reflective Practitioners: Sharing and Assessing Progress by Diverse Communities http://www.ics.uci.edu/~redmiles/chiworkshop/papers/Rose.pdf
2. Lundy, M.P. An Analysis of the Effectiveness of an Interactive Educational Game. Interactive Qualifying Project. Worcester Polytechnic Institute Library http://web.cs.wpi.edu/~claypool/iqp/massbalance/iqp.pdf
[CP6] Koedinger, K. R., Aleven, V., Heffernan. T., McLaren, B. & Hockenberry, M. (2004). Opening the door to non-programmers: Authoring intelligent tutor behavior by demonstration. In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. pp.162-173. Springer Lecture Notes in Computer Science.
1. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R. (2006). The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains. In the proceedings of 8th Annual Intelligent Tutoring Systems Conference, Jhongli, Taiwan. http://www.pitt.edu/~bmclaren/CTAT-ITS2006.pdf
2. Aleven, V., Rose, C.P. (2005). Authoring plug-in tutor agents by demonstration: Rapid, rapid tutor development. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 735-737. Amsterdam, the Netherlands, July 2005. http://shamash.cycletalk.cs.cmu.edu/CycleTalkAIED2005.pdf
3. Barnes, T. & Stamper, J. (2007) Toward the extraction of production rules for solving logic proofs. In the Educational Datamining Workshop held at the 13th Conference on Artificial Intelligence in Education. Los Angeles. pp. 11-20.
4. Blessing, S., Gilbert, S., Ourada, S. & Ritter, S. (2007) Lowering the Bar for Creating Model-tracing Intelligent Tutoring Systems . In Rose Luckin and Ken Koedinger (eds.) Proceedings of the 13th International Conference on Artificial Intelligence in Education, Los Angeles, IOS Press. pp. 443-450.
5. Bollen, Lars. (2005). Generating reports of graphical modelling processes for authoring and presentation. In Proccedings of the 12th International Conference on Artificial Intelligence in Education, Young Researcher's Track, p. 954. Amsterdam, The Netherlands http://www.rhodes.aegean.gr/ltee/kaleidoscope-ia/Publications/bollen_Generating_Reports.pdf
6. Brough J.E, Schwartz M., Guptal S.K., Anand D.K. , Clark C., Peterson R., Yeager C. (2006). Virtual Training Studio: a Step Towards Virtual Environment Assisted Training. In Workshop Proceedings of 1st International Virtual Manufacturing Workshop (VirMan 06), Alexandria, Virginia
7. Brown, J. (2004). Integrating Tools for the Creation of Speech-Enabled Tutors. http://www.cs.cmu.edu/~jonbrown/publications/Brown_TechReport.pdf
8. Harrer, A., McLaren, B. M., Walker, E., Bollen, L., and Sewall, J. (2005). Collaboration and Cognitive Tutoring: Integration, Empirical Results, and Future Directions. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), Amsterdam, the Netherlands, July 2005. http://ctat.pact.cs.cmu.edu/pubs/CollaborationAIED05.pdf
9. Harrer, A., McLaren, B. M., Walker, E., Bollen, L., and Sewall, J. (2006). Collaboration and Cognitive Tutoring: steps toward realization. In User Modeling and User-Adapted Interaction 16(3-4), pp.175-209. http://www.springerlink.com/content/p45v8q6m53184717/?p=cbeacb9177424c7d929dd851d9364f25&pi=1
10. Harrer, A., McLaren, B. M., Walker, E.,
Bollen, L., and Sewall, J. (2005) Collaboration and Cognitive Tutoring:
Integration, Empirical Results, and Future Directions. In The
Proceedings of the 12th International Conference on Artificial Intelligence and
Education (AIED-05), Amsterdam, the Netherlands, July 2005.
http://www.pitt.edu/%7Ebmclaren/AIED2005-Collaboration.pdf
11. Herrmann, K., Hoppe, U. (2005). Making an Unintelligent Checker Smarter. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 282-289. Amsterdam, the Netherlands, July 2005.
12. Hockenberry, M. (2005) Simple tutors for hard problems: understanding the role of pseudo-tutors. In Extended Abstracts Proceedings of the 2005 Conference on Human Factors in Computing Systems, CHI 2005, Edited by Gerrit C. van der Veer and Carolyn Gale. p. 459-1462 http://www.informatik.uni-trier.de/~ley/db/conf/chi/chi2005a.html#Hockenberry05
13. Kumar, R., Rose, C., Aleven, V., Iglesias, A., Robinson, A. (2006) Evaluating the Effectiveness of Tutorial Dialogue in an Exploratory Learning Context. Intelligent Tutoring Systems (ITS) 2006, Taipei, Taiwan http://ctat.pact.cs.cmu.edu/pubs/kumar-dialogue.pdf
14. Kumar, R., Rose, C., Wang, Y., Joshi, M. & Robinson, A. (2007) Tutorial Dialogue as Adaptive Collaborative Learning Support. In Rose Luckin and Ken Koedinger (eds.) Proceedings of the 13th International Conference on Artificial Intelligence in Education, Los Angeles, IOS Press. pp. 383-390.
15. Mavrikis, M., Hunn, C. (2005). Interoperability Issues in Authoring Interactive Activities. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 869-871. Amsterdam, the Netherlands, July 2005. http://www.booksonline.iospress.com/Content/View.aspx?piid=55
16. Matsuda, N, Cohen, W.W., Jonathan Sewall, and Kenneth R. Koedinger (2006). Applying Machine Learning to Cognitive Modeling for Cognitive Tutors, Technical report CMU-ML-06-105, School of Computer Science, Carnegie Mellon University. http://reports-archive.adm.cs.cmu.edu/anon/anon/usr/ftp/ml/CMU-ML-06-105.pdf
17. McLaren, B.M. (2005) Lessons in Machine Ethics from the Perspective of Two Computational Models of Ethical Reasoning. Presented at the AAAI Fall 2005 Symposium, Washington, D. C. In Papers from the AAAI Fall Symposium, Technical Report FS-05-06, pp. 70-77.
18. McLaren, B. M., Koedinger, K. R., Schneider, M., Harrer, A., and Bollen, L. (2004). Bootstrapping Novice Data: Semi-Automated Tutor Authoring Using Student Log Files. In the Proceedings of the Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes, Seventh International Conference on Intelligent Tutoring Systems (ITS-2004), August 2004. http://www.pitt.edu/~bmclaren/AAAI-05-MachineEthics.pdf
19. McLaren, B. M., Koedinger, K. R., Schneider, M., Harrer, A., and Bollen, L. (2004). Toward Cognitive Tutoring in a Collaborative, Web-Based Environment. In Engineering Advanced Web Applications, From the Proceedings in Connection with the 4th International Conference on Web Engineering (ICWE 2004), Munich, Germany, 28-30 July, 2004. http://www.pitt.edu/~bmclaren/AHCW-04-Publication1.pdf
20. McLaren, B. M., Lim, S. Yaron, D. & Koedinger, K. (2007) Can a Polite Intelligent Tutoring System lead to Improved Learning Outside of the Lab? . In Rose Luckin and Ken Koedinger (eds.) Proceedings of the 13th International Conference on Artificial Intelligence in Education, Los Angeles, IOS Press. pp 433-440.
21. Mitrovic, A., Suraweera, P., Martin, B.,
Zakharov, K., Milik, N., Holland, J. (2006). Authoring Constraint-Based Tutors
in ASPIRE. In Lecture Notes in Computer Science (4053). pp. 41-50.
www.cosc.canterbury.ac.nz/tanja.mitrovic/ASPIRE-ITS06.pdf
22. Suraweera, P., Mitrovic, A., Martin, B. (2005). A Knowledge Acquisition System for Constraint-based Intelligent Tutoring Systems. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 638-645. Amsterdam, the Netherlands, July 2005. http://www.cosc.canterbury.ac.nz/tanja.mitrovic/ASPIRE-ITS06.pdf
23. Tollinger, I., Lewis, R.L., McCurdy, M., Tollinger, P., Vera, A., Howes, A., Pelton, L. (2005). Supporting efficient development of cognitive models at multiple skill levels: exploring recent advances in constraint-based modeling. Proceedings of the SIGCHI conference on Human factors in computing systems, April 02-07, 2005, Portland, Oregon, USA http://www.cf.ac.uk/psych/howesa/ccm/docs/Tollinger2005chi.pdf
24. Wyle, R. (2007) Are we asking the right questions? Understanding which tasks lead to robust learning of the English Article System. In Rose Luckin and Ken Koedinger (eds.) Proceedings of the 13th International Conference on Artificial Intelligence in Education, Los Angeles, IOS Press. pp 709-711.
[CP7] Jarvis, M., Nuzzo-Jones, G. & Heffernan. N. T. (2004). Applying machine learning techniques to rule generation in intelligent tutoring systems. In J.C. Lester, R.M. Vicari, & F. Parguacu (Eds.) In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. Springer Lecture Notes in Computer Science. pp. 541-553.
1. Fiedler, A., Tsovaltzi. D. (2003). Automating Hinting in an Intelligent Tutorial Dialog System. In Proceedings of the IJCAI workshop on Knowledge Representation and Automated Reasoning for E-Learning Systems, Acapulco, Mexico, pp. 23-35. http://www.ags.uni-sb.de/~tsovaltzi/collective.pdf
2. Kuno, H &
Lemon, M. (2001) A Lightweight Dynamic Conversation Controller for E-Services.
International Workshop on Advanced Issues of E-Commerce and Web-Based
Information Systems (WECWIS) 2001. June 21-22, 2001, San Jose, CA.
Also published as HP Techincal Resport HPL-2001-25R1 http://www.hpl.hp.com/techreports/2001/HPL-2001-25R1.html
3. Matsuda, N., Cohen, W.W., Sewall, J., and Koedinger K.R. (2006). Applying Machine Learning to Cognitive Modeling for Cognitive Tutors, Technical report CMU-ML-06-105, School of Computer Science, Carnegie Mellon University. http://reports-archive.adm.cs.cmu.edu/anon/anon/usr/ftp/ml/CMU-ML-06-105.pdf
4. Matsuda, N., Cohen, W. W., & Koedinger, K. R. (2005). Applying Programming by Demonstration in an Intelligent Authoring Tool for Cognitive Tutors. In AAAI Workshop on Human Comprehensible Machine Learning (Technical Report WS-05-04) (pp. 1-8). Menlo Park, CA: AAAI association. http://www.cs.cmu.edu/~mazda/Doc/AAAI05/Matsuda05b.pdf
5. Matsuda, N., Cohen, W. W., & Koedinger, K. R. (2005). Building Cognitive Tutors with Programming by Demonstration. In S. Kramer & B. Pfahringer (Eds.), Proceedings of the International Conference on Inductive Logic Programming (Technical report, TUM-I0510) (pp. 41-46): Institut fur Informatik, Technische Universitat Munchen. http://www.cs.cmu.edu/~mazda/Doc/ILP2005/Matsuda05c.pdf
6. Matsuda, N., Cohen, W.W., Sewall, J., and Koedinger K.R. (2006). What characterizes a better demonstration for cognitive modeling by demonstration? Technical report CMU-ML-06-106, School of Computer Science, Carnegie Mellon University. http://reports-archive.adm.cs.cmu.edu/anon/anon/ml/CMU-ML-06-106.pdf
7. Mitrovic, A., Suraweera, P., Martin, B., Zakharov, K., Milik, N., Holland, J. (2006). Authoring Constraint-Based Tutors in ASPIRE. In Lecture Notes in Computer Science (4053). pp. 41-50. http://www.cosc.canterbury.ac.nz/tanja.mitrovic/ASPIRE-ITS06.pdf
8. Suraweera, P., Mitrovic, A., Martin, B. (2005). A Knowledge Acquisition System for Constraint-based Intelligent Tutoring Systems. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 638-645. Amsterdam, the Netherlands, July 2005. http://www.cosc.canterbury.ac.nz/tanja.mitrovic/Suraweera-AIED05.pdf
9. Tchetagni, J. and R. Nkambou. A framework for diagnosis and epistemological remediation in learning logic programming. In International Conference on Computer Aided Learning in Engineering Education. 2004 http://www-clips.imag.fr/calie04/actes/Tchetagni_final.pdf
[CP8] Heffernan, N. T. & Croteau, E. (2004). Web-Based Evaluations Showing Differential Learning for Tutorial Strategies Employed by the Ms. Lindquist Tutor. In James C. Lester, Rosa Maria Vicari, Fábio Paraguaçu (Eds.) Proceedings of 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. Springer Lecture Notes in Computer Science. pp. 491-500.
1. Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and Computers. Erlbaum: New Jersey pp. 388. http://www.amazon.com/One-One-Tutoring-Humans-Computers/dp/0805843612
[CP9] Croteau, E., Heffernan, N. T. & Koedinger, K. R. (2004). Why are Algebra word problems difficult? Using tutorial log files and the power law of learning to select the best fitting cognitive model. In J.C. Lester, R.M. Vicari, & F. Parguacu (Eds.) Proceedings of the 7th International Conference on Intelligent Tutoring Systems. Berlin: Springer-Verlag. pp. 240-250.
1. Cen, H., Koedinger, K. R., & Junker, B. (2005). Automating Cognitive Model Improvement by A* Search and Logistic Regression. In Proceedings of AAAI'05 workshop on Educational Data Mining. http://www.learnlab.org/uploads/mypslc/publications/ws205cenh.pdf
2. Cen, H., Koedinger, K. R., & Junker, B. (2006). Learning Factors Analysis: A general method for cognitive model evaluation and improvement. In M. Ikeda, K. D. Ashley, T.-W. Chan (Eds.) Proceedings of the 8th International Conference on Intelligent Tutoring Systems, 164-175. Berlin: Springer-Verlag. http://www.learnlab.org/uploads/mypslc/publications/learning_factor_analysis_5.2.pdf
3. Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and Computers. Erlbaum: New Jersey pp. 388. http://www.amazon.com/One-One-Tutoring-Humans-Computers/dp/0805843612
4. Khan, J., Hardas, M., Ma, Y., A Study of Problem Difficulty Evaluation for Semantic Network Ontology Based Intelligent Courseware Sharing. WI, pp. 426-429, the 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05), 2005. http://www.medianet.kent.edu/publications/WI05DL-problemcmplexity-KHM.pdf
5. Khan, J., Hardas, M., Ma, Y., Analyzing Question Difficulty Using Course Ontology Based Semantic Knowledge Maps for Test-ware Standardization, 2005, Proceedings of WSEAS, Corfu, Greece. http://www.cs.kent.edu/~mhardas/papers/final(WSEAS-DL-2005-Greece).pdf
6. Koedinger, K. R. & Mathan, S. (2004). Distinguishing qualitatively different kinds of learning using log files and learning curves. In the Working Notes of the ITS2004 Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes. http://www.andrew.cmu.edu/user/jb8n/its2004/koedinger.pdf
7. Leszczenskil, J. & Beck, J. E. (2007) What’s in a Word?: Extending Learning Factors Analysis to Model Reading Transfer. In the Educational Datamining Workshop held at the 13th Conference on Artificial Intelligence in Education. Los Angeles. pp 31-39.
8. Manske, M., Conati, C. (2005) Modeling Learning in Educational Games. Proceedings of the International Conference on Artificial Intelligence in Education, 411-418. http://www.cs.ubc.ca/~conati/my-papers/aied05FinalMM2.pdf
[CP11] Razzaq, L., Feng, M., Nuzzo-Jones, G., Heffernan, N.T., Koedinger, K. R., Junker, B., Ritter, S., Knight, A., Aniszczyk, C., Choksey, S., Livak, T., Mercado, E., Turner, T.E., Upalekar. R, Walonoski, J.A., Macasek. M.A. & Rasmussen, K.P. (2005). The Assistment project: Blending assessment and assisting. In C.K. Looi, G. McCalla, B. Bredeweg, & J. Breuker (Eds.) Proceedings of the 12th Artificial Intelligence in Education, Amsterdam: ISO Press. pp. 555-562.
1. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R. (2006). The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains. In the proceedings of 8th Annual Intelligent Tutoring Systems Conference, Jhongli, Taiwan. http://www.pitt.edu/~bmclaren/CTAT-ITS2006.pdf
2. David Yaron, Gaea Leinhardt, Karen Evans, Jordi Cuadros, Michael Karabinos, William McCue and David Dennis, "Creation of an online stoichiometry course that melds scenario based leaning with virtual labs and problem-solving tutors", Paper Presented on CONFCHEM. Online Conference, Spring 2006. http://iry.chem.cmu.edu/about/paper/confchem06/cc06.pdf
[CP12] Walonoski, J. & Heffernan, N.T. (2006). Detection and analysis of off-task gaming behavior in intelligent tutoring systems. In Ikeda, Ashley & Chan (Eds.). Proceedings of the Eight International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 382-391. 2006.
1. Rodrigo, M.M.T., Baker, R.S.J.d., Lagud, M.C.V., Lim, S.A.L., Macapanpan, A.F., Pascua, S.A.M.S., Santillano, J.Q., Sevilla, L.R.S., Sugay, J.O., Tep, S., Viehland, N.J.B. (in press) Affect and Usage Choices in Simulation Problem Solving Environments. To appear in Proceedings of Artificial Intelligence in Education 2007. http://www.psychology.nottingham.ac.uk/staff/lpzrsb/RodrigoBakeretal2006Final.pdf
2. This paper was cited in a official web-based guide to research put out by the American Advance of Artificial Intelligence. I have archived a copy of the web page here and highlighted the relevant section.
[CP15] Feng, M., Heffernan, N. T., & Koedinger, K.R. (2006). Addressing the testing challenge with a Web-based e-assessment system that tutors as it assesses. Proceedings of the Fifteenth International World Wide Web Conference (WWW-06). New York, NY: ACM Press. ISBN:1-59593-332-9. pp. 307-316.
1. Anozie, N., Junker, B. (2006). Predicting end-of-year accountability assessment scores from monthly student records in an online tutoring system. AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/anozie-aaai06.pdf
2. Ayers E. & Junker B. (2006). Do skills combine additively to predict task difficulty in eighth grade mathematics? AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/WS0606AyersE.pdf
[CP16] Feng, M., Heffernan, N. & Koedinger, K. (2006a). Predicting state test scores better with intelligent tutoring systems: developing metrics to measure assistance required. In Ikeda, Ashley & Chan (Eds.). Proceedings of the Eighth International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp. 31-40.
1. Anozie, N., Junker, B. (2006). Predicting end-of-year accountability assessment scores from monthly student records in an online tutoring system. AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/anozie-aaai06.pdf
2. Ayers E. & Junker B. (2006). Do skills combine additively to predict task difficulty in eighth grade mathematics? AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/WS0606AyersE.pdf
[PP1] Razzaq, L. & Heffernan, N. T (2004) Tutorial dialog in an equation solving intelligent tutoring system . In J.C. Lester, R.M. Vicari, & F. Parguacu (Eds.) Proceedings of 7th Annual International Intelligent Tutoring Systems Conference, Berlin: Springer-Verlag. pp. 851-853.
1. Kafkas, S., Bayram, Z., Yaratan, H. Implementation Strategies for “Equation Guru,” A User Friendly Intelligent Algebra Tutor. 8th International Conference on Enterprice Information Systems (ICEIS'06), 23-27 May 2006, Paphos, Cyprus. http://cmpe.emu.edu.tr/bayram/Papers/EG_ICEIS_4.pdf
[PP2] Koedinger, K. R., Aleven, V., & Heffernan, N. T. (2003). Toward a rapid development environment for cognitive tutors. In F. Verdejo and U. Hoppe (Eds) 11th International Conference Artificial Intelligence in Education. Sydney, Australia. IOS Press. pp. 455-457.
1. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R. (2006). The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains. In the proceedings of 8th Annual Intelligent Tutoring Systems Conference, Jhongli, Taiwan. http://www.pitt.edu/~bmclaren/CTAT-ITS2006.pdf
2. Ayala, A.P., Azuela, J.H.S. Educacion Basada en Web: un Estado del Arte http://www.somece.org.mx/simposio2004/memorias/grupos/archivos/069.doc
3. Brown, J. (2004). Integrating Tools for the Creation of Speech-Enabled Tutors http://www.cs.cmu.edu/~jonbrown/publications/Brown_TechReport.pdf
4. Chepegin V., Aroyo, L., De Bra, P., Houben, G.J. (2003). CHIME: service-oriented framework for adaptive web-based systems. In Proceedings of Dutch National Conference InfWet, Eindhoven, The Netherlands, November 20, 2003, 29-35. http://wwwis.win.tue.nl/infwet03/proceedings/3/
5. Di Eugenio, B., Lu, X., Kershaw, T.C., Corrigan-Halpern, A., Ohlsson, S. (2005). Positive and Negative Verbal Feedback for Intelligent Tutoring Systems. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 798-800. Amsterdam, the Netherlands, July 2005. http://www.cs.uic.edu/~bdieugen/PS-papers/AIED05p.pdf
6. Herrmann, K., Hoppe, U., Kuhn, M. (2005). Help in Modeling with Visual Languages. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 830-832. Amsterdam, the Netherlands, July 2005.
7. Hockenberry, M. (2005). Simple tutors for hard problems: understanding the role of pseudo-tutors. Conference on Human Factors in Computing Systems, Portland, Oregon. pp. 1459-1462 http://portal.acm.org/citation.cfm?id=1056941
8. Hunn, C., Mavrikis, M. (2004). Improving Knowledge Representation, Tutoring, and Authoring in a Component-based ILE. Springer Lecture Notes in Computer Science: pp. 827-829.
9. John, B.E., Prevas, K., Salvucci, D.D., Koedinger, K.R. (2004). Predictive Human Performance Modeling Made Easy. Proceedings of the SIGCHI conference on Human factors in computing systems, Vienna, Austria, pp. 455-462. http://www.cs.cmu.edu/~bej/cogtool/p466-john.pdf
10. John, B.E., Salvucci, D.D. (2005). Multipurpose prototypes for assessing user interfaces in pervasive computing systems. In Pervasive Computing, IEEE 4(4). pp. 27-34 http://www.sis.pitt.edu/~mariah/hci/CogTool.pdf
11. John, B.E., Salvucci, D.D., Centgraf, P., Prevas, K. (2004). Predictive Human Performance Modeling Made Easy. Proceedings of the Sixth International Conference on Cognitive Modeling, Mahwah, New Jersey, pp.130-135. http://portal.acm.org/ft_gateway.cfm?id=985750&type=pdf&coll=GUIDE&dl=GUIDE&CFID=22383924&CFTOKEN=84183877
12. Luo, L., John, B.E. (2005). Predicting task execution time on handheld devices using the keystroke-level model. Conference on Human Factors in Computing Systems, Portland, Oregon. pp. 1605-1608 http://portal.acm.org/citation.cfm?id=1056808.1056977
13. Matsuda, N., Cohen, W.W., Sewall, J., and Koedinger K.R. (2006). Applying Machine Learning to Cognitive Modeling for Cognitive Tutors, Technical report CMU-ML-06-105, School of Computer Science, Carnegie Mellon University. http://reports-archive.adm.cs.cmu.edu/anon/anon/usr/ftp/ml/CMU-ML-06-105.pdf
14. Matsuda, N., Cohen, W. W., Sewall, J., Lacerda, G., & Koedinger, K. R. (2007; in press). Predicting students performance with SimStudent that learns cognitive skills from observation. In Proceedings of the international conference on Artificial Intelligence in Education. http://www.cs.cmu.edu/~mazda/Doc/AIED2007/MatsudaN07b-toAppear.pdf
15. Matsuda, N., Cohen, W. W., & Koedinger, K. R. (2005). Applying Programming by Demonstration in an Intelligent Authoring Tool for Cognitive Tutors. In AAAI Workshop on Human Comprehensible Machine Learning (Technical Report WS-05-04) (pp. 1-8). Menlo Park, CA: AAAI association. http://www.cs.cmu.edu/~mazda/Doc/AAAI05/Matsuda05b.pdf
16. Matsuda, N., Cohen, W. W., & Koedinger, K. R. (2005). Building Cognitive Tutors with Programming by Demonstration. In S. Kramer & B. Pfahringer (Eds.), Proceedings of the International Conference on Inductive Logic Programming (Technical report, TUM-I0510) (pp. 41-46): Institut fur Informatik, Technische Universitat Munchen. http://www.cs.cmu.edu/~mazda/Doc/ILP2005/Matsuda05c.pdf
17. Matsuda, N., Cohen, W.W., Sewall, J., and Koedinger K.R. (2006). What characterizes a better demonstration for cognitive modeling by demonstration? Technical report CMU-ML-06-106, School of Computer Science, Carnegie Mellon University. http://reports-archive.adm.cs.cmu.edu/anon/anon/ml/CMU-ML-06-106.pdf
18. Mavrikis, M., Hunn, C. (2005). Interoperability Issues in Authoring Interactive Activities. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 869-871. Amsterdam, the Netherlands, July 2005.
[PP3] Turner, T.E., Macasek, M.A., Nuzzo-Jones, G., Heffernan, N..T & Koedinger, K. (2005). The Assistment builder: A rapid development tool for ITS. In Looi, McCalla, Bredeweg, & Breuker (Eds.) Proceedings of the 12th Artificial Intelligence in Education, Amsterdam: ISO Press. pp. 929-931. A longer version appears in Hefferan et al. 2006. (Based on W10)
1. Core, M. G., J. D. Moore, and C. Zinn, 2000. Supporting Constructive Learning with a Feedback Planner. In Building Dialogue Systems for Tutorial Applications, Papers of the 2000 AAAI Fall Symposium, edited by C. P. Rose and R. Freedman, 1-9. Technical Report FS-00-01. Menlo Park, CA: AAAI Press. http://people.ict.usc.edu/~traum/cs599f05/core00supporting.pdf
2. Le, V. “Learning and Tutoring Agent Shell: A New Approach to Building Intelligent Tutoring System for Expert Problem Solving Knowledge.” Thesis Defense http://lac.gmu.edu/publications/data/2006/Vu-Proposal-Defense.pdf
[WP3] Heffernan, N. T., & Koedinger, K. R. (2000). Building a 3rd generation ITS for symbolization: Adding a tutorial model with multiple tutorial strategies. Workshop entitled "Learning Algebra with the computer, a transdisciplinary workshop". Held at Intelligent Tutoring Systems 2000 Conference. (pp. 12-22). Lecture Notes in Computer Science 1839, Berlin: Springer.
1. Core, M. G., J. D. Moore, and C. Zinn, 2000. Supporting Constructive Learning with a Feedback Planner. In Building Dialogue Systems for Tutorial Applications, Papers of the 2000 AAAI Fall Symposium, edited by C. P. Rose and R. Freedman, 1-9. Technical Report FS-00-01. Menlo Park, CA: AAAI Press. http://people.ict.usc.edu/~traum/cs599f05/core00supporting.pdf
2. Dietrich, D., Buckley, M. Verification of Proof Steps for Tutoring Mathematical Proofs. In Rose Luckin and Ken Koedinger, editors, Proceedings of the 13th International Conference on Artificial Intelligence in Education, Los Angeles, USA, 2007. http://www.coli.uni-saarland.de/~buckley/content/DietrichBuckleyAIED07.pdf
3. Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and Computers. Erlbaum: New Jersey pp. 83 & 388. http://www.amazon.com/One-One-Tutoring-Humans-Computers/dp/0805843612
4. Fiedler, A. and D. Tsovaltzi, Automating hinting in an intelligent tutorial system, in: Proceedings of the IJCAI Workshop on Knowledge Representation and Automated Reasoning for E-Learning Systems, Acapulco, 2003, pp. 23-35. http://www.ags.uni-sb.de/~tsovaltzi/collective.pdf
5. Freedman, Reva. 2001. An Approach to Increasing Programming Efficiency in Plan-Based Dialogue Systems. Proceedings of the Tenth International Conference on AI in Education (AI-ED 2001), San Antonio http://www.cs.niu.edu/~freedman/papers/aied2001.pdf
6. Tsovaltzi, D., Fiedler, A., Horacek, H. (2004). A Multi-Dimensional Taxonomy for Automating Hinting. Intelligent Tutoring Systems: 7th Annual Conference, ITS 2004, pp. 772-781
7. Tsovaltzi, D., Horacek, H., Fiedler, A. (2004). In Valerie Barr and Zdravko Markov (eds.), Proceedings of the Seventeenth Florida Artificial Intelligence Research Society Conference (FLAIRS 2004), pp. 929-934, Menlo Park, CA, AAAI Press, 2004
[WP4] Heffernan, N. T, Koedinger, K. (2001). The design and formative analysis of a dialog-based tutor. Workshop on Tutorial Dialogue Systems held as part of the 2001 Artificial Intelligence in Education. pp. 23-34.
1. Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and Computers. Erlbaum: New Jersey pp. 388. http://www.amazon.com/One-One-Tutoring-Humans-Computers/dp/0805843612
[WP5] Heffernan, N. T., (2002). Web-based evaluation showing both motivational and cognitive benefits of the Ms. Lindquist tutor. SIGdial endorsed Workshop on Empirical Methods for Tutorial Dialogue Systems which was part of the International Conference on Intelligent Tutoring System 2002. pp. 1-8. Also appeared in a NSF-DFG sponsored workshop on Collaboration between German and American researchers in instructional technology. Tampa, Florida, May 5-7, 2002
1. Kaklauskas, A., Ditkevicius, R., Gargasaite, L. (2006). Intelligent Tutoring System for all Real Estate Management. International Journal of Strategic Property Management (2006) 10, pp. 113-130. http://www.vgtu.lt/upload/property_zurn/ijspm_2006_vol_10_no_2_p_113-130.pdf
[WP6] Koedinger, K. R., Aleven, V., & Heffernan, N. T. (2003). Toward a rapid development environment for cognitive tutors. The 12th Annual Conference on Behavior Representation in Modeling and Simulation. Simulation Interoperability Standards Organization. (Work later led to CP7)
1. Heinath, M., Dzaack, J., Wiesner, A. & Ubas, L. (2007) Applications for cognitive user modeling. In C. Conati, K. McCoy & G. Paliouras (Eds.) User Modeling 2007. Springer. Pp., 127-136.
2. Mavrikis, M., Hunn, C. (2005). Interoperability Issues in Authoring Interactive Activities. In the Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), pp. 869-871. Amsterdam, the Netherlands, July 2005. http://www.booksonline.iospress.com/Content/View.aspx?piid=55
[WP9] Freyberger, J., Heffernan, N., & Ruiz, C. (2004). Using association rules to guide a search for best fitting transfer models of student learning.ing. In Beck, Baker, Corbett, Kay, Litman, Mitrovic & Rigger (Eds.) Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes. Held at the 7th Annual Intelligent Tutoring Systems Conference, Maceio, Brazil. Lecture Notes in Computer Science. ISBN 978-3-540-22948-3.
1. Jaroszewicz, S. (2006). Polynomial association rules with applications to logistic regression. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Philadelphia, Pennsylvania. pp. 586-591 http://portal.acm.org/citation.cfm?id=1150472
2. Leszczenskil, J. & Beck, J. E. (2007) What’s in a Word?: Extending Learning Factors Analysis to Model Reading Transfer. In the Educational Datamining Workshop held at the 13th Conference on Artificial Intelligence in Education. Los Angeles. pp 31-39.
3. Morales, C.M., Soto, S.V., Martinez, C.H. (2005). Estado actual de la aplicacion de la mineria de datos a los sistemas de ensenanza basada en web. Actas del III Taller Nacional de Mineria de Datos y Aprendizaje, TAMIDA2005. pp. 49-56 http://www.lsi.us.es/redmidas/CEDI/papers/189.pdf
4. Winters, T. (2006) Educational Data Mining: Collection and Analysis of Score Matrices for Outcomes-Based Assessment. Dissertation. Doctor of Philosophy, Computer Science, University of California Riverside. June 2006
[WP11] Nuzzo-Jones, G., Walonoski, J.A., Heffernan, N.T. & Livak, T. (2005). The eXtensible tutor architecture: A new foundation for ITS. Workshop on Adaptive Systems for Web-Based Education: Tools and Reusability held at the 12th Annual Conference on Artificial Intelligence in Education. Amsterdam. pp. 1-7.
1. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R. (2006). The Cognitive Tutor Authoring Tools (CTAT): Preliminary Evaluation of Efficiency Gains. In the proceedings of 8th Annual Intelligent Tutoring Systems Conference, Jhongli, Taiwan. http://www.pitt.edu/~bmclaren/CTAT-ITS2006.pdf
[WP13] Feng, M., Heffernan, N. T., & Koedinger, K. R. (2005). Looking for sources of error in predicting student's knowledge. In Beck. J. (Eds). Educational Data Mining: Papers from the 2005 AAAI Workshop. Menlo Park, California: AAAI Press. pp. 54-61. Technical Report WS-05-02.
1. Romero, C., Ventura, S. (2007). Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications: An International Journal 33(1) pp. 135-146. Tarrytown, NY http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V03-4JW10WR-2&_user=10&_coverDate=07%2F31%2F2007&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=f46e1fe62b7d3422a81f1999604158cf
2. Winters, T. (2006) Educational Data Mining: Collection and Analysis of Score Matrices for Outcomes-Based Assessment. Dissertation. Doctor of Philosophy, Computer Science, University of California Riverside. June 2006
[WP14]Pardos, Z. A., Heffernan, N. T., Anderson, B., & Heffernan C. (2006). Using fine-grained skill models to fit student performance with Bayesian networks. Workshop in Educational Data Mining held at the Eighth International Conference on Intelligent Tutoring Systems. Taiwan. 2006.
1. Anozie, N., Junker, B. (2006). Predicting end-of-year accountability assessment scores from monthly student records in an online tutoring system. AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/anozie-aaai06.pdf
2. Ayers E. & Junker B. (2006). Do skills combine additively to predict task difficulty in eighth grade mathematics? AAAI'06 workshop on Educational Data Mining, Boston, 2006. http://www.assistment.org/project/papers/aaai06/WS0606AyersE.pdf
[D1] Heffernan, N. T (2001) Intelligent tutoring systems have forgotten the tutor: Adding a cognitive model of human tutors. Dissertation. Computer Science Department, School of Computer Science, Carnegie Mellon University. Technical Report CMU-CS-01-127.
1. Baker, R.S. (2005) Designing Intelligent Tutors That Adapt to When Students Game the System. Doctoral Dissertation. CMU Technical Report CMU-HCII-05-104. http://reports-archive.adm.cs.cmu.edu/anon/anon/usr0/ftp/hcii/CMU-HCII-05-104.pdf
2. Beal, C. R., & Lee, H. (2005). Creating a pedagogical model that uses student self reports of motivation and mood to adapt ITS instruction. Workshop on Motivation and Affect in Educational Software, July 18-22, 2005, Amsterdam. 12th International Conference on Artificial Intelligence and Education. http://wayangoutpost.net/paper/Beal&LeeCRC.pdf
3. Bruno, A., Gonzalez, C., Moreno, L., Noda, M., Aguilar, R., Munoz, V. Teaching Mathematics to Children with Down’s Syndrome. http://www.it.usyd.edu.au/~aied/vol8/vol8_Bruno.pdf
4. Chiu-Chen Hsieh, Tzong-Han Tsai, David Wible, Wen-Lian Hsu: Exploiting Knowledge Representation in an Intelligent Tutoring System for English Lexical Errors. ICCE 2002: 115-116 http://csdl2.computer.org/comp/proceedings/icce/2002/1509/00/15090115.pdf
5. Evens, M. & Michael, J. (2000) One-on-One Tutoring by Humans and Computers. Erlbaum: New Jersey pp. 388. http://www.amazon.com/One-One-Tutoring-Humans-Computers/dp/0805843612
6. Gama, Claudia. PAL Tool: uma ferramenta cognitiva para organização e representação de problemas algébricos. Anais do XIV Simpósio Brasileiro de Informática na Educação SBIE, Novembro. NCE/UFRJ, Rio de Janeiro, Brasil, 2003. PAL Tool: uma ferramenta cognitiva para organização e representação de problemas algébricos
7. Grubisic, A., Stankov, S., Zitko, B. (2002). Evaluating the Educational Influence of an E-Learning System. http://www.pmfst.hr/~ani/radovi/2005CEEPUS.pdf
8. Ibraheem, A.M., Shaalan, K., Riad, M.B., Darwish, M.G. (2003). A Model and Supporting Mechanism for Item Evaluation in Distance-Learning Based Environment. Egyptian Informatics Journal 4(2), 169-188 http://www.claes.sci.eg/publication/document_view.asp?doc_id=160&File_Name=item_evalutaion_fci.pdf
9. Kim, Jung Hee, Reva Freedman, Michael Glass, and Martha W. Evens. Annotation of Tutorial Dialogue Goals for Natural Language Generation. Discourse Processes vol. 42 no. 1 (2006), pp. 37--74. http://www.csam.iit.edu/~circsim/documents/kfgedp06.pdf
10. Kim, J.H., Glass, M. (2004). Evaluating Dialogue Schemata with the Wizard of Oz Computer-Assisted Algebra Tutor. Intelligent Tutoring Systems: 7th Annual Conference, ITS 2004, pp. 358-367
11. Kodaganallur, V., Weitz, R., Rosenthal, D. (2006). Tools for Building Intelligent Tutoring Systems. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (2), p. 46.2 http://doi.ieeecomputersociety.org/10.1109/HICSS.2006.490
12. Padilla Franco Jávitt Higmar Nahitt, Lara Rodríguez Amado, Márquez Gutiérrez Pedro Rafael. (2001). Sistema Inteligente para la Ensenanze de las Matematicas. Electro 2001. pp. 99-104 http://www.depi.itchihuahua.edu.mx/electro/archivo/electro2001/mem2001/articulos/cmp6.pdf
13. Patel, N., Glass, M., Kim, J.H. (2003). Data Collection Application for the North Carolina A&T State University Algebra Tutoring Dialogue (Wooz Tutor) Project. Fourteenth Midwest Cognitive Science and AI Conference (MAICS-03), Cincinnati http://www.comp.ncat.edu/itsLab/docs/maics03-v2.2.pdf
14. Pon-Barry, H., Clark, B., Schultz, K., Bratt, E.O., Peters, S. (2004). Advantages of Spoken Language Interaction in Dialogue-Based Intelligent Tutoring Systems. In Intelligent Tutoring Systems (3220) pp. 390-400. http://godel.stanford.edu/old/muri/papers/ITS_2004.pdf
15. Sarrafzadeh, A., Page, C., Overmyer, S.P., Fan, C., Messom, C.H. (2003). The Next Generation Intelligent Tutoring Systems. In Ulrich Hoppe, Felisa Verdejo, and Judy Kay (eds.) Artificial Intelligence in Education. Amsterdam: IOS Press. 500-502.
16. Stamey, J.W. (2006). A Comparison of the Performance of Undergraduate Statistics Students Using Intelligent Learning Objects Versus those Receiving Traditional Classroom Instruction. Dissertation. Technology Education, North Carolina State University. http://www.lib.ncsu.edu/theses/available/etd-07102006-075902/
17. VanLehn, K., Siler, S., Murray, C, Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21 (3), 209-249. http://www.pitt.edu/~vanlehn/distrib/Papers/TutorialEvents.pdf
18. Woolf, B. A draft version of a text book called Building Intelligent Tutors, to be published by Elsevier, gives two pages to this work.
19. Zeferino, L.H., Rapkiewicz, C.E., Morales, G. (2003). Construindo o Modulo do Dominio de um Assitente Inteligente Utilizando a Ferramenta Java Expert System Shell. XIV Simpósio Brasileiro de Informática na Educação - NCE - IM/UFRJ 2003