Professor Neil T. Heffernan
Note: An electronic version of this document with working links to all papers is at all
papers is at http://nth.wpi.edu/pubs_and_grants/papers/index-home.html
Education
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Ph. D. Computer Science, Carnegie Mellon University, 2001.
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M.S. Computer Science, Carnegie Mellon University, 1997.
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B.A. Computer Science and History, Amherst College, Summa cum laude,1993.
Appointments
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Associate Professor July 2008 to present.
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Assistant Professor, WPI, July, 2002 to 2008.
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Post-Doctoral Researcher, Human-Computer Interaction Institute, School of
Computer Science, Carnegie Mellon University, 2001 to 2002.
Teaching
Teaching Experience
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Department of Computer Science, Worcester Polytechnic Institute
2002 - present
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Teaching Assistant
Human Computer Interaction, Carnegie Mello University
2001
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Math and Science Teacher
Ephraim Curtis Middle School, Sudbury Public Schools, 1998-99
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Teaching Assistant
Data Structures (1996), Artificial Intelligence (1997), Human Computer Interaction
(2001), Carnegie Mellon University
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Math and Science Teacher
Holy Sprit Catholic School, Baltimore, MD
1994-95
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Science Teacher
Booker T. Washington Middle School, Baltimore Public Schools, Baltimore, MD
Teach For America Placement, 1993-1994
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Amherst College
Helped run Student for Educational Equality. Ran a one-on-one tutoring program pairing
up Amherst College students with inner-city children in Holyoke. MA
1989-1993
Courses Taught at WPI
Undergraduate Courses
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2002 Fall B-Term: CS4341: Artificial Intelligence.
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2005 Spring: D-term: CS4341: Artificial Intelligence.
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2006 Fall: A-term: CS4341: Artificial Intelligence.
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2007 Spring D-Term: CS2102: Object Oriented Design (the first Java class
students take at WPI.)
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2008 Spring D-Term: CS2102: Object Oriented Design (the first Java class
students take at WPI.)
Graduate Courses
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2002 Fall: CS534: Artificial Intelligence.
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2003 Spring: CS525: Intelligent Tutoring Systems and Cognitive Modeling.
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2004 Spring: CS538: Expert Systems.
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2004 Spring: CS525: Intelligent Tutoring Systems and Cognitive Modeling.
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2004 Fall: CS534 : Artificial Intelligence.
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2006 Spring: CS525: Intelligent Tutoring System and Cognitive Modeling.
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2006 Fall: CS525: Advanced Intelligent Tutoring Systems: Web-based
Technologies and Knowledge Tracing.
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2007 Fall: CS525: Pedagogical Agents.
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2008 Fall: CS525 Intelligent Tutoring Systems
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2009 Fall: CS525: Empirical methods for CS student. (Assisted Joe Beck in
teaching this class).
Graduate Theses and Dissertations
Advisor of Ph.D. Dissertations
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Leena Razzaq, in progress, 2004-present. Dissertation Proposal Accepted by
Department.
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Mingyu Feng, in progress, 2004-present. Dissertation Proposal Accepted by
Department.
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Jozsef Parvarczki, in progress, 2005-present. Planning a dissertation proposal
Spring 2008.
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Michael Sao Pedro, in progress, 2007-present. Currently past master degree.
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Zachary Pardos, in progress, 2006-07. Currently pursuing Master Degree
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Yue Gong, in progress, 2008-present. Currently researching a topic.
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Dovan Rai, in progress, 2008-present. Currently researching a topic.
Advisor of Master Theses
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Vilmos Csizmadia: Constructing an Authoring Tool for Intelligent Tutoring
Systems with Hierarchical Domain Models, 2003
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Leena Razzaq, Tutorial Dialog in an Equation Solving Intelligent Tutoring
System, 2003.
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Ethan Croteau, Evaluating Predictions of Transfer and Analyzing Student
Motivation, 2004
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Jon Freyberger, Using Association Rules to Guide a Search for Best Fitting
Transfer Models of Student Learning, 2004
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Matt Jarvis, Applying Machine Learning Techniques to Rule Generation in
Intelligent Tutoring Systems, 2004
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Tom Livak, Collaborative Warrior Tutoring, 2004
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Sanket Choksey, Developing an Affordable Authoring Tool For Intelligent
Tutoring Systems, 2004
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Michael Macasek, Towards Teachers Quickly Creating Tutoring Systems, 2005
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Terrence Turner, The Assistment Builder: A tool for rapid tutor development,
2005
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Jason Walonowski, Visual Feedback for Gaming Prevention in Intelligent
Tutoring Systems, 2005
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Ruta Upalekar, Tools to help build models that predict student learning, 2005
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Goss Nuzzo-Jones, The Common Tutor Object Platform, 2005
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Kai Rasmussen, Developing a Cognitive Rule-Based Tutor for the ASSISTment
System, 2007
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Nick Lloyd, Measuring Student Engagement in an Intelligent Tutoring System,
2007
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Yu Gao, TBA, 2009
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Elijah Forbes Summer, TBA, 2009
Member of Ph.D. Dissertation Committee
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Leena Razzaq (2007)
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Mingyu Feng (2007)
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Aparna Varde, Graphical Data Mining for Computational Estimation in Materials
Science Applications, 2006
Undergraduate Projects (MQPs, IQPs, Sufficiency) Advised
Advisor of Major Qualifying Projects
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Derek Radkte, ? 2008
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Pardos, Zach A., Using Bayesian Networks to Predict Test Scores, 2006
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Kardian, Kevin R., Knowledge Engineering for Intelligent Tutoring, 2006
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Schafer, Roger James & Walsh, Jonathan B., Curriculum Tools in the
ASSISTment Project, 2006
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Fusaro, Michael Vincent, Peltier, Brandon Geoffrey & Runcie, Jason Michael,
Latent Semantic Analysis Use in a Museau Exhibit, 2004
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Nuzzo-Jones, Goss F., Machine Learning in Intelligent Tutoring Systems, 2004
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Moyer, Dale Christopher, Warrior Tutoring:Intelligent Tutoring Sys for US
Army, 2004
Advisor of Interactive Qualifying Projects
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Aniszczyk, Christopher Richard, Analysis of an ITS: The Assistments Project,
2004
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Haines, Charles Allen, Analysis of 8th Grade MCAS ITS: Assistment Project,
2005
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Pardos, Zach A. & Quinn, Patrick J, Improving Online Tutoring Content, 2006
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Lourenco, Abraao N., Methods of Teaching Mathematics in Middle School, 2006
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Ushakov, Igor, Intellignet Tutoring System Project, 2006
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Radtke, Derek B. & Spetla, Hattie, Scaffolding in Computer Aided Learning,
2006
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Paduroiu, Andrei & Potter, Emily June, Effective Teaching Methods, 2006
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Petrova, Olga Petrovna, Role of Multimedia in Tutoring Systems, 2006
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Sader, Paul M., Enhancing Web-Based Tutoring with Scaffolding, 2007
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Christopher Freeman, Roderick Talyor, Cosmin Tutor, & Michael Zhang , The
ASSISTment Project, 2007
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Ramon Harrington & Aaron Holroyd, Hints versus Scaffolding, 2007
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Loren Gjata, David Curran & David Lamoureux, Intelligent Tutoring Content for
10th Grade Math, 2007
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Denis Vadimovich, Mihai Tiberiu Luca & Antoniya Toneva Statelova; Which
Works Better: Worked Examples or Hint Messages? 2008
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Jeslin J Wu & Boris Svirchuk; the Assistment Project 2008
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Ashish Maharjan, Prawal Shrestha & Xing Wei; Comparison Between
Scaffolding and Worked Example in ASSISTment Tutoring System 2008
Awards & Honors
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 in support of the early
career-development activities of those teacher-scholars who most effectively integrate
research and education within the context of the mission of their organizationers.
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 a
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
Best Student Paper Award, (with Ken Koedinger), Cognitive Science Conference.
1997.
Publications
Note: In the following sections all coauthors who are WPI students are italicized.
Book Chapters
BC3 Pardos, Z., Heffernan, N., Anderson, B. & Heffernan C., (in Submission) The
Effect of Model Granularity on Student Performance Prediction Using Bayesian
Networks. Submitted to EDM 2009.
BC2
BC1
Feng, M., Heffernan, N.T., & Koedinger, K.R. (in Submission). Student Modeling
in an Intelligent Tutoring System. Submitted to
Stankov, Glavinc, Rosic. (Eds.) Intelligent Tutoring Systems in E-learning Environments:
Design, Implementation and Evaluation. IGI Global. early 2010 (anticipated)
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. (Based on W10,
W11 and W12)
Journal Articles
J8
Feng, M., Heffernan, N.T., & Koedinger, K.R. (accepted). Addressing the
assessment challenge in an Intelligent Tutoring System that tutors as it assesses.
Accepted by The Journal of User Modeling and User-Adapted Interaction.
J7
Mendicino, M., Razzaq, L. & Heffernan, N. T. (accepted- In Press) Comparison
of Traditional Homework with Computer Supported Homework. 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). Scheduled to appear in the Spring 2009 issue.
J6
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.
J5
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)
J4
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)
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.
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)
Journal Articles in Submission:
JS2
Razzaq, L., Parvarczki, J., Almeida, S.F., Vartak, M., Feng, M., Heffernan, N.T.
and Koedinger, K. (Submitted). The ASSISTment builder: Supporting the Life-cycle of
ITS Content Creation. Submitted to the IEEE Transactions on Learning Technologies
Special Issue on Real-World Applications of Intelligent Tutoring Systems.
JS1
Feng , M, Heffernan, N., Heffernan, C. & Mani, M. (submitted) Using MixedEffects Modeling to Analyze Different Grain-Sized Skill Models. IEEE Transaction on
Learning Technologies.
Strictly Reviewed Conferences (Percent acceptance rate in the 30s or below) ;
CP29 Kim, R, Weitz, R., Heffernan, N. & Krach, N. (submitted) Tutored Problem
Solving vs. “Pure: Worked Examples Submitted to Cognitive Science Society Annual
2009 Conference
CP28 Sao Pedro, M., Gobert, J. Heffernan, N. & Beck, J. (submitted) Can an Intelligent
Tutor Teach the Control Variables Strategy for Scientific Inquiry? Submitted to
Cognitive Science Society Annual Conference
CP27 Gong, Y., Rai, D., Beck, J. & Heffernan, N. (submitted) Motivational Effect in
Learning: An Empirical Analysis. Submitted to AIED 2009.
CP26 Pardos, Z. & Heffernan, N. (submitted) Detecting the Learning Value of Items in
a Randomized Problem Set. Submitted to AIED 2009.
CP 25 Razzaq, L. & Heffernan, N. (submitted) To Tutor or Not to Tutor: That is the
Question. Submitted AIED 2009
CP24 Prawal, Xing, Maharjan, Razzaq, Heffernan & Heffernan (submitted) The
Controversy over Tutored Problem Solving Versus: Worked Examples: A Study and
Plausible Explanation Proposed. Submitted to CHI2009.
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.
pp.107-116.
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. pp.218-225.
CP21 Pardos, Z. A., Heffernan, N. T., Ruiz, C. & Beck, J. In press (2008). Effective
Skill Assessment Using Expectation Maximization in a Multi Network Temporal
Bayesian Network. The Young Researchers Track at the 20th International Conference
on Intelligent Tutoring Systems. Montreal, Canada. (Page numbers and link to final copy)
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.
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 978-1-57735124-5. 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.]
Published 3-4 Page Papers (aka "Poster") in Prestigious Conferences (Percent acceptance
rate in the 50-60s%)
PP10 Jozsef Patvarczki, Shane F. Almeida, Joseph E. Beck, and Neil T. Heffernan.(
2008 Note- this is not the final version linked yet ) Lessons Learned from Scaling Up a
Web-Based Intelligent Tutoring System. In Woolf & Aimeur (Eds.) Proceeding of the 9th
International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin.
PP9 Yu Guo , Neil T.Heffernan, Joseph E. Beck.(2008) Trying to Reduce Bottom-out
hinting: Will telling student how many hints they have left help?. In Woolf & Aimeur
(Eds.) Proceeding of the 9th International Conference on Intelligent Tutoring Systems.
Springer-Verlag: Berlin.
PP8 Pardos, Z., Feng, M. & Heffernan, N. T. & Heffernan-Lindquist, C. (2007)
Analyzing fine-grained skill models using bayesian and mixed effect methods. In Luckin
& Koedinger (Eds.) Proceedings of the 13th Conference on Artificial Intelligence in
Education. IOS Press. pp. 626-628. (Based on W17)
PP7 Wietz, R., Heffernan, N. T., Kodaganallur, V. & Rosenthal, D. (2007). The
distribution of student errors across schools: An initial study. In Luckin & Koedinger
(Eds.) Proceedings of the 13th Conference on Artificial Intelligence in Education. IOS
Press. pp 671-673.
PP6 Kardian, K. & Heffernan, N.T. (2006). Knowledge engineering for intelligent
tutoring systems: Assessing semi-automatic skill encoding methods. In Ikeda, Ashley &
Chan (Eds.) Proceedings of the Eight International Conference on Intelligent Tutoring
Systems. Springer-Verlag: Berlin. pp. 735-737. A longer version was published as WPICS-TR-06-06 (pdf)
PP5 Walonoski, J. & Heffernan, N. (2006b). Prevention of off-task gaming behavior in
intelligent tutoring systems. In Ikeda, Ashley & Chan (Eds.). Proceedings of the 8th
International Conference on Intelligent Tutoring Systems. Springer-Verlag: Berlin. pp.
722-724. [Winner of the Best 3-page Paper Award out of 40 such papers]. A longer
version is here.
PP4 Nuzzo-Jones, G., Walonoski, J.A., Heffernan, N.T. & Livak, T. (2005). The
eXtensible tutor architecture: A new foundation for ITS. In Looi, McCalla, Bredeweg, &
Breuker (Eds.) Proceedings of the 12th Artificial Intelligence in Education, 555-562.
Amsterdam: ISO Press. pp. 902-904. (Based on W11)
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)
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.
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. [Winner of the Best Poster Award]
Less Stringently Reviewed Venues
WP19 Razzaq, L., Heffernan, N.T. (2008). Towards Designing a User-Adaptive WebBased E-Learning System. In Mary Czerwinski, Arnold M. Lund, Desney S. Tan (Eds.):
Extended Abstracts Proceedings of the 2008 Conference on Human Factors in
Computing Systems. pp. 3525-3530. Florence, Italy: ACM 2008
WP18 Pardos, Z., Heffernan, N. T., Anderson, B., & Heffernan-Lindquist, C. (2007).
The effect of model granularity on student performance prediction using Bayesian
networks. The Educational Data Mining Workshop held at the International User
Modeling Conference 2007. Corfu, Greece. (Work later led to CP18)
WP17 Pardos, Z., Feng, M. Heffernan, N. T., Heffernan-Lindquist, C. & Ruiz, C. (2007)
Analyzing fine-grained skill models using Bayesian and mixed effect methods. In the
Educational Data Mining Workshop held at the 13th Conference on Artificial Intelligence
in Education. This is a longer version of CP18.
WP16 Lllyod, N., Heffernan, N. & Ruiz, C. (2007). Predicting student engagement in
intelligent tutoring systems using teacher expert knowledge. In the Educational
DataMining Workshop held at the 13th Conference on Artificial Intelligence in
Education.
WP15 Feng, M., Heffernan, N. T., Mani, M., & Heffernan, C. (2006). Using mixedeffects modeling to compare different grain-sized skill models. In Beck, J., Aimeur, E., &
Barnes, T. (Eds). Educational Data Mining: Papers from the AAAI Workshop. Menlo
Park, CA: AAAI Press. pp. 57-66. Technical Report WS-06-05. (Work later led to PP8)
WP14 Pardos, Z. A., Heffernan, N. T., Anderson, B., & Heffernan C. (2006). Using finegrained 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. (Work later led to PP8)
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.
WP12 Feng, M., & Heffernan, N. (2005). Informing teachers live about student learning:
Reporting in the Assistment system. Workshop on Usage Analysis in Learning Systems
held at the 12th International Conference on Artificial Intelligence in Education.
Amsterdam. (Work later led to J3 and J5)
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. (Work later led to BC1 and
PP4)
WP10 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 a workshop on on
Adaptive Systems for Web-Based Education: Tools and Reusability, held at the 12th
Annual Conference on Artificial Intelligence in Education Amsterdam. (Work later led to
BC1, PP4 and CP14)
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.
WP8 Livak, T., Heffernan, N. T., Moyer, D. (2004). Using cognitive models for
computer generated forces and human tutoring. 13th Annual Conference on (BRIMS)
Behavior Representation in Modeling and Simulation. Simulation Interoperability
Standards Organization. Arlington, VA. Summer 2004.
WP7 Razzaq, L. & Heffernan, N. T (2004). Tutorial dialog in an equation solving
intelligent tutoring system. Workshop on “Dialog-based Intelligent Tutoring Systems:
State of the art and new research directions” at the 7th Annual Intelligent Tutoring
Systems Conference, Maceio, Brazil. pp. 33-42.
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)
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. (Work later led to CP8)
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. (Work later led to CP8)
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. (Work later led to CP8)
WP2 Heffernan, N. T. (2000). Adding a cognitive model of human tutor to an
intelligent tutoring systems. Intelligent Tutoring System Conference- Young Researchers
Track. (Work later led to D1)
WP1 Heffernan, N. T. (1998). Intelligent tutoring systems have forgotten the tutor:
Adding a cognitive model of human tutors. Abstract at the 1998 Computer Human
Interaction Conference's Doctoral Consortium. (Work later led to D1)
My Young Researchers Track Papers
YRP5 Almeida, S., Vartak, M & Heffernan, N. (2008) Supporting the Generation of
Isomorphic Tutoring Content Intelligent Tutoring System Conference 2008 - Young
Researchers Track
YRP4 Guo, Yu, Beck, J. & Heffernan, N. (2008) Trying to Reduce Bottom-out hinting:
Will telling student how many hints they have left help? Intelligent Tutoring System
Conference 2008 - Young Researchers Track
YRP3 Feng, M., Heffernan, N., Beck, J. & Koedinger, K. (2008) Can we predict which
groups of questions students will learn from? Intelligent Tutoring System Conference
2008 - Young Researchers Track
YRP2 Pardos, Z., Heffernan, N., Ruiz, C., Beck, J. (2008) Effective Skill Assessment
Using Expectation Maximization in a Multi Network Temporal Bayesian Network
Intelligent Tutoring System Conference 2008 - Young Researchers Track
YRP1 Heffernan, N. T. (2000). Adding a cognitive model of human tutor to an
intelligent tutoring systems. Intelligent Tutoring System Conference- Young Researchers
Track. (Work later led to D1)
Papers in Preparation
PIP 2 WPI-CS-TR-08-07 is assigned to NTH on Mon Aug 25, 2008
Title: "An Analysis of Middle-School Math Errors Across Schools"
Authors: Weitz, Neil T. Heffernan, Rosenthal, and Mingyu Feng
Rob Weitz, Neil Heffernan, David Rosenthal & Mingyu Feng An Analysis of MiddleSchool Math Errors Across Schools.
PIP 1 Pardos, Z. A., Heffernan, N. T., Ruiz, C. Effective skill assessment using
expectation maximization in a multi network temporal Bayesian network.
Tech Reports
WPI-CS-TR-08-08 – waiting for link to website
WPI-CS-TR-08-06
The International Journal of Artificial Intelligence in Education Special Issue on
Authoring Tools. (Submitted)
WPI-CS-TR-08-03 (pdf)
Cost-Effective Content Creation with Variabilization (March 2008) Manasi P. Vartak,
Shane F. Almeida & Neil T. Heffernan
WPI-CS-TR-08-02 (pdf)
Lessons Learned from Scaling Up a Web-Based Intelligent Tutoring System (March
2008) Jozsef Patvarczki, Shane F. Almeida, Joseph E. Beck & Neil T. Heffernan
WPI-CS-TR-07-04 (pdf)
Measuring Student Engagement in an Intelligent Tutoring System (May 2007) Nicholas
M. Lloyd
WPI-CS-TR-06-12 (pdf)
Scaling up the Server-based ASSISTment ITS: Speed and Reliability (Jun 2006) Kai
Rasmussen, Jozsef Patvarczki & Neil T. Heffernan.
WPI-CS-TR-06-08 (pdf)
Common Tutor Object Platform: an e-Learning Software Development Strategy (May
2006) Goss Nuzzo-Jones, Michael Macasek, Jason Walonoski, Kai Rasmussen & Neil T.
Heffernan.
WPI-CS-TR-06-07 (pdf)
Towards Enabling Collaboration in Intelligent Tutoring Systems (May 2006) Michael A.
Macasek & Neil T. Heffernan.
WPI-CS-TR-06-06 (pdf)
Knowledge Engineering for Intelligent Tutoring Systems: Using machine learning
assistance to help humans tag questions to skills based upon the words in the questions
(May 2006) Kevin Kardian & Neil T. Heffernan.
WPI-CS-TR-06-05 (pdf)
Prevention of Off-Task Gaming Behavior in Intelligent Tutoring Systems (May 2006)
Jason Walonoski & Neil T. Heffernan.
WPI-CS-TR-03-31 (pdf)
An Evaluation of the Run-Time Performance of the Model-Tracing Algorithm of Two
Different Production Systems: JESS and TDK (August 2003). Sanket Choksey and Neil
Heffernan.
Dissertation
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-CS01-127. (Pieces published as J1, CP8, CP5, CP4, and CP3)
Service
International
•
Program Committee: Intelligent Tutoring Systems Conference 2008.
•
Demonstrations: Intelligent Tutoring Systems Conference 2008.
•
Program Committee: First International Conference on Educational Data Mining
2008 http://www.educationaldatamining.org/EDM2008CFP.htm
•
Senior Program Committee: International Conference on Artificial Intelligence in
Education 2007.
•
Program Committee: American Association for Artificial Intelligence 2007
(AAAI'07).
•
Co-Chair of “Educational Data Mining Workshop” to be held at the International
Conference on Artificial Intelligence in Education 2007.
•
Reviewed for IEEE Intelligent Systems Journal. 2007.
•
Reviewer for User Modeling and User-Adapted Interaction: The Journal of
Personalization Research 2007.
•
Reviewer for Cognitive Science Conference 2007.
•
Program Committee: International Intelligent Tutoring System Conference 2006.
•
Program Committee: FLAIRS-2006 Special Track on Intelligent Tutoring
Systems 2006.
•
Program Committee: International Conference on Artificial Intelligence in
Education 2005
•
Workshops Co-Chair International Conference on Artificial Intelligence in
Education 2005.
•
Reviewer for International Intelligent Tutoring System Conference 2004.
•
Chair of workshop on Dialog-Based Intelligent Tutoring Systems: State of the art
and new research directions held at the Intelligent Tutoring Systems Conference 2004.
•
Reviewer for International Conference on Artificial Intelligence in Education
2002.
•
Reviewed for International Journal of Computers for Mathematical Learning.
•
On the program committee for numerous workshops held in conjunction with
AIED and ITS conferences.
National Service
•
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.
•
National Science Foundation Reviewer. ROLE. 2005.
•
National Science Foundation Reviewer. In CISE, the Computer Science
directorate, in the Human Computer Interaction program. 2003
Worcester Polytechnic Service
•
Myself and my graduate student helped bring the GRID Portal here to WPI. WPI
is now the only grid portal that connects the major scientific supercomputing grid in
Europe with the GRID in the United States, giving WPI increased recognition.
•
Graduate Research Committee (2 years), Colloquium Committee (2 years, one
year as chair)
Invited Talks
2007-08
•
IT5 International Mind, Brain and Education Society 2007 conference.
http://www.imbes.org/conference/conf07.html
•
IT4 Presented at EDUCASE http://www.educause.edu/e07
2006-07
•
IT3 I was invited to serve on a Boston University panel on making
recommendations about how the No Child Left Behind act should be changed as it is up
for re-authorization this year in Congress.
2005-06
•
Tufts University.
•
UMASS Amherst.
•
Due to my work on authoring tools for intelligent tutoring systems, I was selected
as one of 15 fully-funded invited speakers for the “Authoring Tools for Advanced
Learning Systems with Standards” workshop held by The Institute for Intelligent Systems
and the Advanced Distributed Learning Workforce Co-Lab at the University of Memphis.
•
The University of Georgia paid for me to give a invited talk at their Education
school October 2005.
•
American Education Research Association (AERA) annual meeting in Montreal.
(with Feng) Informing Teachers Live about Student Learning: Reporting in the
ASSISTment System.
2004-05
•
Boston University.
•
Intel Foundation.
•
Mass Insight Education, a business-funded "not-for-profit organization focused on
improving student achievement in Massachusetts' public schools".
•
See also my dissemination efforts with the CIRCLE Summer School.
•
I served on the Concord Consortium's advisor board meeting for a IERI grant Aug
29, 2005.
•
IT2 Invited talk: October 2004, NASA Houston Space Center : " Training For
Tomorrow."
•
IT1 Invited talk: March 2005, NASA Langley: " Advances in Learning
Technologies."
2003-04
•
Massachusetts Institute of Technology.
•
Charles River Analytics.
Grants Awarded
My research was benefited from about 7.5 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.
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" PIHeffernan. $900,000. 2005-2010
GA10 Office of Naval Research: "Demonstrating Affordable Behavior Modeling with
CTAT through Machine Learning and Human Computer Interaction Techniques." PIHeffernan. $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” PIKoedinger. Co-PIs Heffernan, Junker and Ritter. $1.4 million over 4 years. 2003-07.
GA7 National Science Foundation: “Research Experience for K12”. $99,457. PIRundensteiner. 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
Press
Newspaper Articles
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.
Radio and Television
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:
This 55 second audio clip is from Worcester's local radio station, 580 AM. In it, Prof
Heffernan is interviewed about how his $900,000, NSF CAREER award is going to
impact Massachusetts 8th and 10th grade math students. Archived at:
http://web.cs.wpi.edu/Research/trg/public/project/audio/Neil_interview.mp3
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:
http://web.cs.wpi.edu/Research/trg/public/project/videos/NECN_MCAS_story_5-232005.wmv
Citation Index for Neil Heffernan’s Tenure Package (Compiled June 2007- Last updated
Sept 1, 2007)
In this citation index I have attempted to collect the references to my work that I happen
to know of. I filtered out papers where I was one of the authors. This list has over 150
citations in total. I have included URLs to the papers so you could see how they cited my
work, but I am sure the URLs are liable to “break” over time so expect some broken
links.
More Unusual Citation
Zucker’s book
Woolf’s Book
Martha Evans Book
[J5] 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.
1.
Scheuer, O. & Zinn, C. (2007) How did the e-learning session go? : The Student
Inspector. In Rose Luckin and Ken Koedinger (eds.) Proceedings of the 13th
International Conference on Artificial Intelligence in Education, Los Angeles, IOS Press.
pp 487-494.
[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.
1.
Corbett, A. (2002). Cognitive Tutor Algebra I: Adaptive Student Modeling in
Widespread Classroom Use. In a book edited by the National Research Council entitled
Technology and assessment: Thinking ahead: Proceedings of a workshop. Board on
Testing and Assessment, Center for Education, Division of Behavioral and Social
Sciences and Education. Washington, DC: National Academy Press.
http://books.nap.edu/booksearch.php?record_id=10297&term=heffernan&chapter=50-62
2.
Graesser, A.C., Person, N., Harter, D., & TRG (June, 2000). Teaching tactics in
AutoTutor. International Journal of Artificial Intelligence in Education (2001), 12, 257279. http://aied.inf.ed.ac.uk/abstracts/Vol_12/graesser.html
3.
The portions of above paper also seem to have first appeared in a workshop
before appearing in the journal list above. Graesser, A.C., Person, N., Harter, D., & TRG
(June, 2000). Teaching tactics in AutoTutor. Paper presented at the workshop on tutorial
dialogue at the Intelligent Tutoring Systems 2000 Conference, Montreal, Canada.
http://www.cs.pitt.edu/~litman/courses/cs3710/graesser.pdf
4.
Koedinger, (1998) Intelligent Cognitive Tutors as Modeling Tool and
Instructional Model. A Position Paper for the National Council of Teachers of
Mathematics (NCTM) Standards 2000 Technology Conference. June 5-6, 1998.
http://mathforum.org/technology/papers/papers/koeding/koeding2.htm
5.
Koedinger, K.R. (2001). Cognitive Tutors as Modeling Tool and Instructional
Model. In Forbus, K.D. & Feltovich, P.J. (Eds.) Smart Machines in Education: The
Coming Revolution in Educational Technology, (pp. 145-168). Menlo Park, CA:
AAAI/MIT Press.
http://www.psychology.nottingham.ac.uk/staff/com/c8clat/resources/Koedinger2002.pdf
6.
Mark, M. A., & Koedinger, K. R. (1999). Strategic support of algebraic
expression writing. In Kay, J. (Ed.) Proceedings of the Seventh International Conference
on User Modeling, (pp. 149-158). SpringerWein, New York.
http://bistrica.usask.ca/um/UM99/Proc/mark.pdf
7.
Nathan, M. & Koedinger, K. (2000) An Investigation of Teachers' Beliefs of
Students' Algebra Development. Cognition and Instruction, Vol. 18, No. 2. pp. 209-237.
Stable URL: http://links.jstor.org/sici?sici=07370008%282000%2918%3A2%3C209%3AAIOTBO%3E2.0.CO%3B2-P
[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.
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
2.
Baker, R.S., Corbett, A.T., Koedinger, K.R., Wagner, A.Z. (2004) Off-Task
Behavior in the Cognitive Tutor Classroom: When Students "Game The System".
Proceedings of ACM CHI 2004: Computer-Human Interaction, 383-390.
http://www.cs.cmu.edu/~rsbaker/p383-baker-rev.pdf
3.
Corbett, A. (2002). Cognitive Tutor Algebra I: Adaptive Student Modeling in
Widespread Classroom Use. In a book edited by the National Research Council entitled
Technology and assessment: Thinking ahead: Proceedings of a workshop. Board on
Testing and Assessment, Center for Education, Division of Behavioral and Social
Sciences and Education. Washington, DC: National Academy Press.
http://books.nap.edu/booksearch.php?record_id=10297&term=heffernan&chapter=50-62
4.
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.
http://www.nce.ufrj.br/sbie2003/publicacoes/paper22.pdf
5.
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.
http://cat.inist.fr/?aModele=afficheN&cpsidt=15990616
6.
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
7.
Koedinger, (1998) Intelligent Cognitive Tutors as Modeling Tool and
Instructional Model. A Position Paper for the National Council of Teachers of
Mathematics (NCTM) Standards 2000 Technology Conference. June 5-6, 1998.
http://mathforum.org/technology/papers/papers/koeding/koeding2.htm
8.
Koedinger, K.R. (2001). Cognitive Tutors as Modeling Tool and Instructional
Model. In Forbus, K.D. & Feltovich, P.J. (Eds.) Smart Machines in Education: The
Coming Revolution in Educational Technology, (pp. 145-168). Menlo Park, CA:
AAAI/MIT Press.
http://www.psychology.nottingham.ac.uk/staff/com/c8clat/resources/Koedinger2002.pdf
9.
Koedinger, K. R. (2002). Toward evidence for instructional design principles:
Examples from Cognitive Tutor Math 6. Invited paper in Proceedings of PME-NA
XXXIII (the North American Chapter of the International Group for the Psychology of
Mathematics Education).
http://nth.wpi.edu/PapersByOthers/Koedinger_PME_paper_dissem2.pdf
10.
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
11.
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 3139.
[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 978-1-57735124-5. pp. 14- 19
1.
Aleven, V., Popescu, O., & Koedinger, K.R. (2001). Pedagogical Content
Knowledge in a Tutorial Dialogue System to Support Self-Examination. Workshop on
Tutorial Dialogue Systems held as part of the 2001 Artificial Intelligence in Education.
pp. 59-70. http://www.hcrc.ed.ac.uk/aied2001/workshops.html
2.
Aleven, V., Popescu, O., & Koedinger, K. R. (2001). Towards tutorial dialog to
support self-explanation: Adding natural language understanding to a cognitive tutor. In
J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.), Artificial Intelligence in Education:
AI-ED in the Wired and Wireless Future, Proceedings of AI-ED 2001 (pp. 246-255).
Amsterdam, IOS Press. http://www.cs.cmu.edu/People/aleven/AlevenEtAlAIED2001.pdf
3.
Aleven V., Popescu, O. , & Koedinger, K. R. (2001). A Tutorial Dialogue System
with Knowledge-Based Understanding and Classification of Student Explanations. In
Working Notes of the 2nd IJCAI Workshop on Knowledge and Reasoning in Practical
Dialogue Systems, August 5, 2001, Seattle.
http://www.cs.cmu.edu/People/aleven/AlevenEtAlIJCAI2001WS.pdf
4.
Benzmuller, C., Fiedler, A., Gabsdil, M., Horacek, H., Kruijff-Korbayova, I.,
Pinkal, M., Siekmann, J., Tsovaltzi, D. Vo, B.Q., Wolska, M. (2003). Discourse
Phenomena in Tutorial Dialogs on Mathematical Proofs. In Ivana Kruijff-Korbayová and
Claudia Kosny (eds.), Proceedings of DiaBruck'03, the 7th Workshop on the Semantics
and Pragmatics of Language, pp. 165--166, Saarbruecken, Germany. http://www.ags.unisb.de/~tsovaltzi/SB1.pdf
5.
Benzmuller, C., Fiedler, A., Gabsdil, M., Horacek, H., Kruijff-Korbayova, I.,
Pinkal, M., Siekmann, J., Tsovaltzi, D. Vo, B.Q., Wolska, M. (2003). Towards a
Principled Approach to Tutoring Mathematical Proofs. In Andreas Harrer and Katrin
Gaßner (eds.), Proceedings of the KI-03 Workshop on Expressive Media and Intelligent
Tools for Learning, Hamburg, Germany. http://www.ags.uni-sb.de/~tsovaltzi/KI-03.pdf
6.
Benzmuller, C., Fiedler, A., Gabsdil, M., Horacek, H., Kruijff-Korbayova, I.,
Pinkal, M., Siekmann, J., Tsovaltzi, D. Vo, B.Q., Wolska, M. (2003). Tutorial Dialogs on
Mathematical Proofs. In Peter Baumgartner, Paul A. Cairns, Michael Kohlhase, and
Erica Melis (eds.), pp. 12-22, Acapulco, Mexico, 2003. http://www.ags.unisb.de/~chris/papers/W20.pdf
7.
Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and
Computers. Erlbaum: New Jersey pp. 83 & 388. http://www.amazon.com/One-OneTutoring-Humans-Computers/dp/0805843612
8.
Fiedler, A., Gabsdil, M. (2002). Supporting Progressive Refinement of Wizardof-Oz Experiments. In Carolyn Penstein Rose and Vincent Aleven (eds.), , pp. 62-69, San
Sebastian, Spain, 2002. http://www.ags.uni-sb.de/~afiedler/pubs/papers/its-02-ws.pdf
9.
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
10.
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
11.
Popescu, O. (2005). Logic-Based Natural Language Understanding in Intelligent
Tutoring Systems. Dissertation. Language Technologies Institute, School of Computer
Science, Carnegie Mellon University.
12.
Ramachandran, S. & Stottler, R. (2003). A Meta-Cognitive Computer-based Tutor
for High-School Algebra. In Proceedings of World Conference on Educational
Multimedia, Hypermedia and Telecommunications 2003 (pp. 911-914). Chesapeake, VA:
AACE. http://www.stottlerhenke.com/papers/ramachandran_algebra_tutor.pdf
13.
D. Rasseneur, E. Delozanne , P. Jacoboni et B. Grugeon (2002), Learning with
virtual agents: Competition and Cooperation in AMICO, Proceedings of ITS’ 2002,
Lectures Notes in Computer Sciences 2363, Springer, 61-70. http://pepite.univlemans.fr/Telechargement/anglais/3-ITS-2002-Rasseneureal.pdf
14.
Scarlatos, L. (2002). TICLE: using multimedia multimodal guidance to enhance
learning. Information Sciences—Informatics and Computer Science: An International
Journal 140(1) pp. 85-103. New York, NY.
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V0C-44B4J7R1&_user=74021&_coverDate=01%2F31%2F2002&_rdoc=1&_fmt=&_orig=search&_so
rt=d&view=c&_acct=C000005878&_version=1&_urlVersion=0&_userid=74021&md5=
8b6e80a5bfe71840bfc7ee100391a03c
15.
Scarlatos, L., Landy, S.S., Breban, J., Horowitz, R., Sandberg, C. On the
Effectiveness of Tangible Interfaces in Collaborative Learning Environments.
http://www.cs.gc.cuny.edu/tr/files/TR-2002004.pdf
16.
Tsovaltzi, D., Fiedler, A. (2003). An Approach to Facilitating Reflection in a
Mathematics Tutoring System. In aied2003 (Artificial Intelligence in Education)
Supplementary Proceedings,Vol.V. workshop on Learner Modelling for Reflection,
Sydney, Australia, pp. 278-287, 2003.
http://www.it.usyd.edu.au/~aied/vol5/vol5_tsovaltzi.pdf
17.
Tsovaltzi, D., Fiedler, A. (2003). Enhancement and Use of a Mathematical
Ontology in a Tutorial Dialogue System. In Proceedings of the IJCAI Workshop on
Knowledge and Reasoning in Practical Dialogue Systems, Acapulco, Mexico, pp. 19-28.
http://www.ida.liu.se/labs/nlplab/ijcai-ws-03/papers/Tsovaltzi.pdf
[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.
1.
Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R. M. (2003). Help
seeking and help design in interactive learning environments. Review of Educational
Research, 73(2), 277-320. http://www.msu.edu/user/mccrory/pubs/Alevenetal.pdf
2.
Barnes, T., D. Bitzer & M. Vouk. (2005). The q-matrix method: Mining student
response data for knowledge. Proceedings of the AAAI 20th National Conference on
Artificial Intelligence Educational Data Mining Workshop (AAAI2005), Pittsburgh, PA,
July 9-13.
http://nth.wpi.edu/classes/cs525t_tutoring_systems/PaperForClass/WS205BarnesT.pdf
3.
Cox, R, & Pang, J. (2007) VL-PATSy: Facilitating Vicarious Learning via
Intelligent Resource Provision. In R. Luckin, Koedinger & Greer (Eds.) Artificial
Intelligence in Education: Building Technology Rich Learning Contexts that Work. IOS
Press. pp. 85-92.
4.
Crowley, R.S., Medvedeva, O. (2005) An Intelligent Tutoring System for Visual
Classification Problem Solving. Artificial Intelligence in Medicine.
http://slidetutor.upmc.edu/papers/Crowley%20AIM%20828.pdf
5.
Evens, M. & Michael, J. (2006) One-on-One Tutoring by Humans and
Computers. Erlbaum: New Jersey pp. 388. http://www.amazon.com/One-One-TutoringHumans-Computers/dp/0805843612
6.
Horacek, H. & Wolska, M. (2007) Generating Responses to Formally Flawed
Problem-Solving Statements. In R. Luckin, Koedinger & Greer (Eds.) Artificial
Intelligence in Education: Building Technology Rich Learning Contexts that Work. IOS
Press. pp. 17-24.
7.
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
8.
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://csdl2.computer.org/comp/proceedings/hicss/2006/2507/02/250720046b.pdf
9.
Litman, D.J., Rose, C.P., Forbes-Riley, K., VanLehn, K., Bhembe, D., Silliman,
S. (2006). Spoken Versus Typed Human and Computer Dialogue Tutoring. International
Journal of Artificial Intelligence in Education 16(2). pp. 145-170.
http://www.cs.pitt.edu/~litman/ijaied06.pdf
10.
Martens, A., Harrer, A. (2004). Lehr-/Lernsysteme – Welche Rolle spielt die
Kunstliche Intelligenz gestern, heute und morgen? In Teaching and Training Systems –
the role of intelligence in past, present, and future. pp. 396-409
http://www.informatik.uni-rostock.de/~martens/Papers/MaHa_gi_ki04.pdf
11.
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
12.
Peters, S., Bratt, E.O., Clark, B., Pon-Barry, H., Schultz, K. (2004) Intelligent
Systems for Training Damage Control Assistants. In Proceedings of I/ITSEC 2004.
Orlando FL, USA. http://www-csli.stanford.edu/semlab-hold/muri/papers/1908.PDF
13.
Pon-Barry, H., Clark, B., Bratt, E.O., Schultz, K., & Peters, S. (2004). Evaluating
the Effectiveness of SCoT: a Spoken Conversational Tutor.
In Proceedings of ITS 2004 Workshop on Dialogue-based Intelligent Tutoring Systems:
State of the Art and New Research Directions. Maceio, Brazil. 23-32.
http://godel.stanford.edu/old/muri/papers/ITS_2004_Workshop.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
15.
Rose, C.P., Gaydos, A., Hall, B.S., Roque, A., VanLehn, K. (2003). Overcoming
the Knowledge Engineering Bottleneck for Understanding Student Language Input. In
Ulrich Hoppe, Felisa Verdejo, and Judy Kay (eds.) Artificial Intelligence in Education.
Amsterdam: IOS Press. 315-322. http://www.cs.cmu.edu/~cprose/tools.pdf
16.
Rose, C.P., Litman, D., Bhembe, D., Forbes, K., Silliman, S., Srivastava, R.,
VanLehn, K. (2003). A comparison of tutor and student behavior in speech versus text
based tutoring. Proceedings of the HLT-NAACL 03 Workshop on Building educational
applications using natural language processing – Volume 2. pp. 30-37
http://acl.ldc.upenn.edu/W/W03/W03-0205.pdf
17.
Rosé, C. P., & VanLehn, K. (2005). An Evaluation of a Hybrid Language
Understanding Approach for Robust Selection of Tutoring Goals. International Journal of
Artificial Intelligence in Education, 15(4), 325-355.
http://iospress.metapress.com/app/home/contribution.asp?referrer=parent&backto=issue,
4,4;journal,7,15;linkingpublicationresults,1:110564,1
18.
Tchetagni, J., Nkambou, R. and Bourdeau, J. (2007). Explicit Reflection in
Prolog-Tutor. 17, 169-215. http://aied.inf.ed.ac.uk/abstract/Vol_17/Tchetagni07.html
19.
Thomsen-Gray, Z., Schultz, K., Clark, B., Bratt, E.O., Peters, S. (2003).
Intelligent Tutoring for Non-Deterministic and Dynamic Domains. In Ulrich Hoppe,
Felisa Verdejo, and Judy Kay (eds.) Artificial Intelligence in Education. Amsterdam: IOS
Press. 506-508. http://godel.stanford.edu/old/muri/papers/aied-final.pdf
20.
Wiemer-Hastings,P. et al. (2000). Research Methods Tutoring in the Classroom.
De Paul University. Chicago,IL. USA http://reed.cs.depaul.edu/peterwh/papers/WiemerHastings2003rmt.pdf
21.
Woolf, B. A draft version of a text book called Building Intelligent Tutors, to be
published by Elsevier, gives two pages to this work.
[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.
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-TutoringHumans-Computers/dp/0805843612
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/kaleidoscopeia/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=cbeacb9177424c7d929dd8
51d9364f25&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.unitrier.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/kumardialogue.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-06105.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-05MachineEthics.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, 2830 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. 638645. 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 WebBased 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 CMUML-06-105, School of Computer Science, Carnegie Mellon University. http://reportsarchive.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/ASPIREITS06.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. 638645. 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://wwwclips.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-TutoringHumans-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-TutoringHumans-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 3139.
8.
Manske, M., Conati, C. (2005) Modeling Learning in Educational Games.
Proceedings of the International Conference on Artificial Intelligence in Education, 411418. 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: serviceoriented 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. 2734 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 CMUML-06-105, School of Computer Science, Carnegie Mellon University. http://reportsarchive.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-OneTutoring-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.unisb.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-TutoringHumans-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 3139.
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=B6V034JW10WR2&_user=10&_coverDate=07%2F31%2F2007&_rdoc=1&_fmt=&_orig=search&_sort=d
&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=f46e1fe
62b7d3422a81f1999604158cf
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-CS01-127.
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-TutoringHumans-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/cmp
6.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