Advanced Interactive Learning Environments UG4/MSc 2011-2012
READINGS, LINKS and OTHER Materials
Last updated: 1st March 2012
1. Syllabus
The issues addressed will include the following:
Previous development of teaching systems and limitations; adaptivity in relation to the domain and the learner;
Methodology: empirically informed and user centred design; involving students and teachers in the design process;
Modelling and simulating domain knowledge;
Modelling the user: diagnosis, errors and misconceptions; modelling affect;
Pedagogical Issues: theoretical and educational basis of teaching tools; using Pedagogical Agents;
Models of interaction and communication; Educational dialogue;
Evaluating the design and effectiveness of educational software.
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2. READINGS AND MATERIALS:
Course material can basically be divided into:
A. CORE ESSENTIAL material - these will comprise:
- the content of the lectures
- the content of the seminars
- you will expected to know about a number of core systems - these include those covered in the seminars and others as indicated
- Required Reading that may be set each week
It will be assumed that you have read this material.
B. USEFUL BACKGROUND material. This will be indicated as
Background Reading, and should help improve your understanding overall, and will provide additional examples. This will also include reference to other systems in addition to those indicated as 'core'.
C. REFERENCES AND OTHER MATERIALS: this will be links to various resources, references cited in lectures and other relevant literature.
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3. GENERAL OVERVIEWS
There is a recent textbook that covers a lot of material relevant to this course:
Woolf, B. P. (2009), Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning, Morgan Kaufmann Publishers/Elsevier.
This gives background to many systems and techniques used in Artificial Intelligence and Education. It is a good starting point for researching previous work in the field.
Another more recent text is:
Nkambou, R., Mizoguchi, R. and Bourdeau, J. (editors) (2010) Advances in Intelligent Tutoring Systems (Studies in
Computational Intelligence) Springer
Two earlier texts that provide good summaries of classic systems are:
Sleeman, D. & Brown, J.S. (eds.) (1982), Intelligent Tutoring Systems, Academic Press.
Wenger, E. (1987) Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Francisco: Morgan Kaufmann.
Three reports written for the UK’s TLRP Technology Enhanced Learning – AIED Theme. May 2011.
Underwood, J. and Luckin, R. (2011) What is AIED and why does Education need it?
Useful overview papers are:
Joseph Beck, Mia Stern, and Erik Haugsjaa (2001). Applications of AI in Education,
ACM
Crossroads Student Magazine, Fall 1996, 3.1, Issue on Artificial Intelligence. online at
http://portal.acm.org/citation.cfm?id=332148.332153&coll=portal&dl=ACM
Du Boulay, B. and Luckin, R. (2001) Modelling human teaching tactics and strategies for tutoring systems.
International Journal of Artificial Intelligence in Education, 12(3):235-256, 2001. See this paper also fo referencs from the lecture. Available as:
http://www.cogs.susx.ac.uk/users/bend/papers/ijaiedteachers.pdf
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Some other useful links:
The International Journal of Artificial Intelligence in Education (IJAIED) is the official journal of the International AIED Society. IJAIED publishes papers and other items concerned with the application of artificial intelligence techniques and concepts to the design of systems to support learning.
The main conferences in the area are the
AIED conference and the
ITS conference - see the papers form these (usually published by Springer) for the most recent work in the area. Other organisations that have journals and conferences of interest include
User Modeling, Adaptation and Personalization, and
Educational Data Mining. Also see the
International Society of the Learning Sciences which has various affiliated
journals and conferences as
Computer Supported Collaborative Learning, and
Learning Sciences.
LearnLab: Pittsburgh Science of Learning Center (PSLC)
"Learnlab is a facility designed to dramatically increase the ease and speed with which learning researchers can create the rigorous, theory-based experiments that pave the way to an understanding of robust learning. Run jointly by Carnegie Mellon University and the University of Pittsburgh, LearnLab makes use of advanced technologies to facilitate the design of experiments that combine the realism of classroom field studies and the rigor of controlled theory-based laboratory studies.
PSLC's LearnLab is a national resource for learning research that includes:
- Authoring tools for online courses, experiments, and integrated computational learner models
- Support for running in vivo learning experiments
- Longitudinal microgenetic data from entire courses
- Data analysis tools, including software for learning curve analysis and semi-automated coding of verbal data."
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4. CURRENT AND RECENT RESEARCH GROUPS AND SYSTEMS
1. Adventure Author
See the Adventure Author homepage:
http://judyrobertson.typepad.com/adventure_author/about-adventure-author.html
For various papers see:
http://judyrobertson.typepad.com/adventure_author/publications.html
Goolnik, S., Robertson, J. and Good, J. (2006). Learner Centred Design in the Adventure Author Project,
International Journal of Artificial Intelligence in Education, 16, 381-413. available from
http://aied.inf.ed.ac.uk/abstract/Vol_16/Goolnik06.html
McFarlane, A., Sparrowhawk, A. and Heald, Y. (2002) The role of games in education,
A research report to the DfES,
http://www.teem.org.uk
Robertson, J., & Good, J. (2003). Using a Collaborative Virtual Role-Play Environment to Foster Characterisation in Stories.
Journal of Interactive Learning Research, 14(1), 5-29.
Robertson, J., & Good, J. (2005a). Story creation in virtual game worlds.
Communications of ACM, 48, 61-65.
Robertson, J., & Good, J. (2005b). Adventure Author: An Authoring Tool for 3D Virtual Reality Story Construction.
Proceedings of the AIED-05 Workshop on Narrative Learning Environments, pp. 63-69
Robertson, J., & Good, J. (2005c) Children's Narrative Development Through Computer Game Authoring.
TechTrends, Volume 49 (5), pp. 43-59.
Robertson, J. and Howells, C. (2008).
Computer Game Design: Opportunities for Successful Learning.Computers & Education 50 (2008) 559–578
Robertson, J., & Oberlander, J. (2002). Ghostwriter: drama in a virtual environment.
Journal of Computer Mediated Communication. 8(1).th Retrieved 14 February 2006
http://jcmc.indiana.edu/vol8/issue1/robertson/robertson.html
2. Affective learning Companion (group 3)
For an overview see:
http://affect.media.mit.edu/projects.php?id=178
For more details on the Learning Companion and related references see:
http://affect.media.mit.edu/projectpages/lc/
3. Ambient Wood
For a general project description see:
http://www.informatics.sussex.ac.uk/research/groups/interact/projects/Equator/ambient_wood.htm
Rogers, Y., Price, S., Harris, E., Phelps, T., Underwood, M., Wilde, D. & Smith, H. (2002) Learning through digitally-augmented physical experiences: Reflections on the Ambient Wood project. (Equator working paper)
for this paper see
http://www.informatics.sussex.ac.uk/research/groups/interact/publicationArchives.htm under 2002
This list of publications includes the following references, but also those of other projects.
http://www.informatics.sussex.ac.uk/research/groups/interact/publications.htm
Several of direct relevance (though there may be some overlap within them) are:
Randell, C., Price, S., Rogers, Y., Harris, E., & Fitzpatrick, G. (2004). The Ambient Horn: designing a novel audio-based learning experience. Personal and Ubiquitous Computing, 8(3-4), 144-161.
http://www.informatics.sussex.ac.uk/research/groups/interact/publications/AHorn2004.pdf
Price, S., & Randell, C. (2004) Ambient Sounds in the Woods. Position paper presented at Mobile HCI 2004, 6th International Symposium, Glasgow, UK, September 13-16
http://www.informatics.sussex.ac.uk/research/groups/interact/publications/mob_HCI_04.pdf
Rogers, Y., Price, S., Fitzpatrick, G., Fleck, R., Harris, E., Smith, H., Randell, C., Muller, H., O'Malley, C., Stanton, D., Thompson, M., & Weal, M. (2004). Ambient wood: designing new forms of digital augmentation for learning outdoors. In Proceedings of 2004 conference on Interaction design and children: building a community (IDC 2004), Maryland, USA, June 1-3, 3-10.
http://www.informatics.sussex.ac.uk/research/groups/interact/publications/Rogers_IDC2004.pdf
Rogers, Y., & Price, S. (2004). Extending and Augmenting Scientific Enquiry through Pervasive Learning Environments. Children Youth and Environments, 14(2), 67-83.
http://www.informatics.sussex.ac.uk/research/groups/interact/publications/CYE.pdf
Harris, E., Fitzpatrick, G., Rogers, Y., Price, S., Phelps, T., & Randell, C. (2004). From snark to park: lessons learnt moving pervasive experiences from indoors to outdoors. In Proceedings of 5th Australasian User Interface Conference, Dunedin, New Zealand, 39-48.
http://www.informatics.sussex.ac.uk/research/groups/interact/publications/Eric2004.pdf
4. The ANDES tutor:
The Andes project homepage
VanLehn, K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., and Wintersgill, M. (2005).
The Andes Physics Tutoring System: Lessons Learned. International Journal of Artificial Intelligence and Education, 15 (3).
Vanlehn, K., Lynch, C., Schulze, K., Shapiro, J. A., Shelby, R. H., Taylor, L., Treacy, D. J., Weinstein, A., and Wintersgill, M. C. (2005).
The Andes physics tutoring system: Five years of evaluations. In: G. I. McCalla and C.-K. Looi (Eds.),
Proceedings of the Artificial Intelligence in Education Conference . Amsterdam: IOS.
VanLehn, K., Bhembe, D., Chi, M., Lynch, C., Schulze, K., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., & Wintersgill, M. (2004) .
Implicit versus explicit learning of strategies in a non-procedural cognitive skill. In: Lester, J.C., Vicari, R.M., Paraguacu, F. (Eds.),
7th Conference on Intelligent Tutoring Systems, Berlin: Springer, pages 521-530.
Conati, C., Gertner, A., & VanLehn, K. (2002).
Using Bayesian networks to manage uncertainly in student modeling. User Modeling &User-Adapted Interaction, 12(4), 371-417. Winner of the 2002 James R. Chen Award for best article of the year.
VanLehn, K, Lynch, C., Taylor, L., Weinstein, A., Shelby, R., Schulze, K., Treacy, D. & Wintersgill, M. (2002)
Minimally invasive tutoring of complex physics problem solving. In: Cerri, SA, Gouarderes, G, Paraguacu, F (Eds.)
Intelligent Tutoring Systems, 2002, 6th International Conference, Berlin: Springer, pages 367-376
5. animalwatch
For an overview of Animalwatch see:
http://www.cs.arizona.edu/~beal/projects/aw/
Various papers are in the list of publications on Carole Beal's publications page:
http://www.cs.arizona.edu/~beal/publications/
In particular see:
Cohen, P. R., Beal, C. R., & Adams, N. M. (2008). The design, deployment and evaluation of the AnimalWatch
intelligent tutoring system. Accepted for presentation at the 5th Prestigious Applications of Intelligent Systems
(PAIS) conference, July 21-25, Patras Greece.
Beal, C. R., Arroyo, I., Cohen, P. R., & Woolf, B. P. (2010). Evaluation of AnimalWatch: An intelligent tutoring system for arithmetic and fractions. Journal of Interactive Online Learning, 9, 64-77.
http://www.ncolr.org/jiol/issues/showissue.cfm?volID=9&IssueID=28
6. AutoTutor Emotions
For an overview see:
http://sites.google.com/site/graesserart/projects/autotutor-emotions
This has a link to:
http://emotion.autotutor.org/
The relevant papers referenced are available as pdfs from:
http://sites.google.com/site/graesserart/publications
In particular see papers jointly authored with Sidney D'Mello.
There is a demo of the ARIES system (teaching scientific enquiry) that Autotuto Emotions augments at:
http://rhea.memphis.edu/ARIES-Demo/ARIES-AIED-3.html
7. Crystal Island - outbreak
See webpages of project,
http://www.intellimedia.ncsu.edu/ci8.html and the list of publications.
Also pages of project members: Jonathan Rowe,
http://www4.ncsu.edu/~jprowe/, James Lester and for papers. In particular see:
Jonathan Rowe, Lucy Shores, Bradford Mott, and James Lester.
Integrating Learning and Engagement in Narrative-Centered Learning Environments. In
Proceedings of the Tenth International Conference on Intelligent Tutoring Systems, Pittsburgh, Pennsylvania, pp. 166-177, 2010.
Jonathan Rowe, Bradford Mott, Scott McQuiggan, Jennifer Robison, Sunyoung Lee, and James Lester (2009). Crystal Island: A Narrative-Centered Learning Environment for Eighth Grade Microbiology. In
Proceedings of the AIED'09 Workshop on Intelligent Educational Games, Brighton, UK, 2009.
[pdf]
Crystal Island Videos:
http://www.youtube.com/watch?v=aduzGkj8J2k&feature=mfu_in_order&list=UL
http://www.youtube.com/watch?v=r1waTnT4Y5s&feature=mfu_in_order&list=UL
http://www.youtube.com/watch?v=r1waTnT4Y5s&feature=mfu_in_order&listUL
ttp://www.youtube.com/watch?v=giwBQqSGyc&feature=mfu_in_order&list=UL
8. GEOMETRY EXPLANATION TUTOR:
http://web.cs.cmu.edu/~aleven/publications.html (Aleven's publications page)
Roll, I., Aleven, V., McLaren, B., & Koedinger, K. (2007). Designing for metacognition – applying Cognitive Tutor principles to metacognitive tutoring. Metacognition and Learning, 2(2-3), 125-140.
http://www.cs.cmu.edu/~aleven/Papers/2007/Roll_ea_MetacognitionLearning2007.pdf
Aleven V., Popescu, O., Ogan, A. & Koedinger, K. R. (2003). A Formative Classroom Evaluation of a Tutorial Dialogue System that Supports Self-Explanation. In V. Aleven, U. Hoppe, J. Kay, R. Mizoguchi, H.Pain, F. Verdejo, & K. Yacef (Eds.), Supplemental
Proceedings of the 11th International Conference on Artificial Intelligence in Education, AIED2003, Volume VI: Workshop on Tutorial Dialogue Systems: with a view toward the classroom (pp. 345-355). School of Information Technologies, University of Sydney.
available from:
http://www.cs.usyd.edu.au/%7Eaied/Supp_procs.html#vol6
Octav Popescu, Vincent Aleven, Kenneth Koedinger (2003). A Knowledge-based Approach to Understanding Students' Explanations. In V. Aleven, U. Hoppe, J. Kay, R. Mizoguchi, H.Pain, F. Verdejo, & K. Yacef (Eds.),
Supplemental Proceedings of the 11th International Conference on Artificial Intelligence in Education, AIED2003, Volume VI: Workshop on Tutorial Dialogue Systems: with a view toward the classroom. School of Information Technologies, University of Sydney.
available from:
http://www.cs.usyd.edu.au/%7Eaied/Supp_procs.html#vol6
Aleven V. & Koedinger, K. R. (2001). Investigations into Help Seeking and Learning with a Cognitive Tutor. In R. Luckin (Ed.),
Papers of the AIED-2001 Workshop on Help Provision and Help Seeking in Interactive Learning Environments (pp. 47-58). Available via
http://www.cogs.susx.ac.uk/users/bend/aied2001/helpworkshop.html see Programme for pdf of paper.
A general paper as background to the Carnegie-Mellon Tutors is:
http://act-r.psy.cmu.edu/papers/Lessons_Learned-abs.html
9. PATSy
A good starting point for the PATSy project is:
http://www.tlrp.org/proj/phase111/cox.htm
Various publications can be found at:
http://www.tlrp-archive.org/cgi-bin/search_oai_all.pl?pn=25&no_menu=1&short_menu=1
More detail about PATSy can be found at
http://www.patsy.ac.uk/
10. REDEEM
REDEEM: Creating Reusable Intelligent Tutoring Systems
For a general description see:
http://www.psychology.nottingham.ac.uk/research/credit/projects/redeem/
See Shaaron Ainsworth's publications page for relevant papers:
http://www.psychology.nottingham.ac.uk/staff/Shaaron.Ainsworth/publications.html
11. SAM: virtual peers and autism
See the work of
Justine Cassell at Northwestern University on Story-Listening systems for Children. In particular see her work on authorable virtual peers in relation to Innovative Technologies for Autism
http://www.articulab.justinecassell.com/projects/samautism/index.html
Publications are listed at
http://www.articulab.justinecassell.com/publications/index.html but you will need to see which are most relevant.
12. SIMFOREST
SimForrest: see http://ddc.hampshire.edu/simforest/about/about.html
** Tom Murray, Larry Winship, Roger Bellin, Matt Cornell (2001). Toward Glass Box Educational Simulations: Reifying Models for Inspection and Design.
AIED-2001 workshop: External Representations in AIED. (extended version)
[See: http://ddc.hampshire.edu/simforest/about/AIED2001WSGlassBoxFull.doc]
** Murray, T. (2004).
Classroom Strategies for Simulation-Based Collaborative Inquiry Learning. (Extended version)
Proceedings of ICLS-2004, San Mateo, June, 2004.
[
See: http://ddc.hampshire.edu/simforest/about/2004ICLS_SimForest.ext.doc]
Ester Shartar, Scientific Inquiry What is it?(http://ddc.hampshire.edu/simforest/about/inquiry.html)
13. STANDUP
Standup Project: see http://www.csd.abdn.ac.uk/research/standup/
14. Tactical Language and culture training systems
For an overview of the work of Lewis Johnson and Alelo Inc. see
: http://www.alelo.com/
in particular, http://www.alelo.com/technology.html and http://www.alelo.com/language_culture.html
This has a link to: http://www.alelo.com/publications.html which has a number of relevant papers. There are also a number of videos on youtube, including:
Alelo's Virtual Cultural Awareness Trainer (VCAT)
http://www.youtube.com/watch?v=hZ2CLv6JyXo&feature=BF&list=ULLR-c8JEL1J0&index=5
Alelo's Virtual Role Players (VRP) for Bohemia's VBS2 Mission Rehearsal software
http://www.youtube.com/watch?v=JjZd34_RF0g&feature=mfu_in_order&list=UL
15. Teachable agents
For the the work of Daniel Schwartz and the Teachable Agents group at Stanford University see
http://aaalab.stanford.edu/teachable.html
and Gautam Biswas at Vanderbilt University (see Betty’s Brain and other teachable agents )
http://www.teachableagents.org/
16. VICARIOUS LEARNING
Vicarious Learning Project: see http://www.tlrp.org/proj/phase111/cox.htm
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5. CLASSIC INTELLIGENT TEACHING TOOLS
There are relevant sections that refer to LOGO, Sophie, Guidon, Quest, Envision, Qualitative Process Theory, Lisp Tutor, BUGGY/DEBUGGY/IDEBUGGY, WEST, Steamer, Scholar, Sophie, WHY, MenoTutor and Cognitive Apprenticeship in:
Sleeman, D. & Brown, J.S. (eds.) (1982), Intelligent Tutoring Systems, Academic Press.
Wenger, E. (1987) Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Francisco: Morgan Kaufmann.
They are also discussed at various points in:
Woolf, B. P. (2009), Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning, Morgan Kaufmann Publishers/Elsevier.
Other papers that describe classic research in this area are:
Anderson, J. R., Farrell, R., and Sauers, R. (1984). Learning to program in LISP.
Cognitive Science, 8, 87-129.
Anderson, J. R. and Reiser, B. J. (1985). The LISP tutor.
BYTE, 10(4):159–175.
Anderson, J.R., Boyle,F.B., Farrell,R. and Reiser, B.J. (1987), Cognitive Principles in the Design of Computer Tutors, Chapter 4 of Morris. P. (ed.)
Modelling Cognition. Wiley.
Anderson, J. R., Corbett, A. T., Koedinger, K. R., and Pelletier, R. (1995). Cognitive tutors: Lessons learned.
The Journal of the Learning Sciences, 4(2):167–207.
Brown, J. S. and R. Burton (1975) Multiple Representations of Knowledge for Tutorial Reasoning in D. G. Bobrow and A. M. Collins (Eds.),
Representation & Understanding: Studies in Cognitive Science, New York: Academic Press, 1975.
Brown, J.S. , R. Burton, A. Bell, (1975) SOPHIE: A Step Toward Creating a Reactive Learning Environment,
International Journal of Man-Machine Studies, Vol. 7.
Brown, J.S. and R.R.Burton, (1978) Diagnostic models for procedural bugs in basic mathematical skills,
Cognitive Science, 2, pp.155-192
Brown, J.S. & VanLehn, K. (1980). Repair theory: A generative theory of bugs in procedural skills.
Cognitive Science, 4, 379-426.
Brown, J.S., R. R. Burton and J. de Kleer (1982) Pedagogical, Natural Language and Knowledge Engineering Techniques in Sophie I, II, and III, in D. Sleeman and J. S. Brown (Eds.),
Intelligent Tutoring Systems, London, England: Academic Press.
Burton, R.R. (1982) Diagnosing bugs in a simple procedural skill, in (eds.) D.Sleeman and J.S.Brown,
Intelligent Tutoring Systems, Academic Press, pp.157-184.
Burton, R.R. and Brown, J.S., (1976) A Tutoring and Student Modeling Paradigm for Gaming Environments
, Proceedings for the Symposium on Computer Science and Education, Anaheim, CA, February 1976.
Burton,R.R. and Brown, J.S., (1979) An Investigation of Computer Coaching for Informal Learning Activities,
International Journal of Man-Machine Studies, Vol. 11, January 1979.
Burton,R.R. and Brown, J.S., (1982) An investigation of computer coaching for informal learning activities, in Sleeman, D.H. and Brown, J.S. (eds),
Intelligent Tutoring Systems, 79-98, London: Academic Press.
Carbonell, J. R. (1970). AI in CAI: An artificial intelligence approach to computer-assisted instruction.
IEEE Transactions on Man-Machine Systems, 11(4), 190-202.
Clancey, W.J, (1979). Transfer of Rule-Based Expertise through a Tuturial Dialogue. Doctoral dissertation, Stanford University. STAN-CS-769.
Clancey, W.J. (1982) Tutoring Rules for Guiding a Case Method Dialogue,
Intelligent Tutoring Systems edited by Sleeman, D. & Brown, J.S., Academic Press.
Clancey, W.J. (1983) GUIDON,
Journal of Computer Based Instruction, 10:(1+2) 8-15.
Clancey, W. J. (1986a). From Guidon to Neomycin and Heracles in twenty short lessons. AI Magazine, 7(3), 40-60.
Clancey,W. J. (1986b) Qualitative Student Models', in
First Annual Review of Computer Science, ACM, pp. 381-450.
Clancey,W. J. (1987) Knowledge-based Tutoring: The GUIDON Program, MIT Press.
Coller, L. D., Pizzini, Q. A., Wogulis, J., Munro, A. and Towne, D. M. (1991) Direct manipulation authoring of instruction in a model-based graphical environment. In L. Birnbaum (Ed.),
The International Conference on the Learning Sciences: Proceedings of the 1991 conference, Evanston, Illinois: Association for the Advancement of Computing in Education.
Collins, A., Warnock, E. H., Aiello, N., and Miller, M. L. (1975). Reasoning from incomplete knowledge. In Bobrow, D. G. and Collins, A., editors,
Representation and Understanding, pages 383–415. Academic Press, New York.
Collins, A., Brown, J.S. & Newman, S.E. (1986) Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics BBN Technical Report No. 6459 BBN Laboratories Incorporated, Cambridge, Mass. and in Resnick, L.B. (ed.),
Knowing, Learning and Instruction: Essays in honour of Robert Glaser, LEA, 1989.
Collins, A. and Brown, J. S. (1988). The computer as a tool for learning through reflection. In Mandl, H. and Lesgold, A., editors, Learning Issues for Intelligent Tutoring Systems, pages 1–18. Springer- Verlag, New York.
Collins, A. and Stevens, A. L. (1991). A cognitive theory of inquiry teaching. In Goodyear, P., editor,
Teaching Knowledge and Intelligent Tutoring, pages 203–230. Ablex Publishing Corporation, Norwood, New Jersey.
Corbett, A.T. and Anderson, J.R., (1990) The Effect of Feedback Control on Learning to Program with the Lisp Tutor,
Proceedings of the 12th Annual Conference of the Cognitive Science Society, LEA, New Jersey, 1990
Corbett , A. & Anderson, J. (1992). LISP intelligent tutoring system: Research in skill acquisition. In J. H. Larkin and R. W. Chabay, editors,
Computer-Assisted Instruction and Intelligent Tutoring Systems: Shared Goals and Complementary Approaches, pages 73-109. Lawrence Erlbaum
Forbus, K. (1984), Qualitative process theory. Artificial Intelligence, 24, pp 85-168.
de Kleer, J . and Brown, J . (1984) A qualitative physics based on confluences, Artificial Intelligence, 24.
de Kleer, J. and Brown, J.S. (1992). Model-based Diagnosis in SOPHIE III,
Readings in Model-based Diagnosis, Hamscher, Walter; Console, Luca; de Kleer, Johan, (Eds.). San Mateo: Morgan Kaufmann Publishers; pp. 179 - 205.
Elsom-Cook, M. (1990) Guided Discovery Tutoring: A Framework for ICAI Research, Paul Chapman Publishing.
Feurzeig, W., Papert, S., Bloom, M., Grant, R., & Solomon, C. (1969) Programming language as a conceptual framework for teaching mathematics: final report on the first fifteen months of the Logo Project, submitted to the
U.S. National Science Foundation, Bolt, Beranek & Newman Inc. Report # 1889, November 30, 1969. Cambridge, MA: Bolt Beranek and Newman.
Hartley, J.R. and Sleeman, D. H. (l973). Towards more intelligent teaching systems,
Int. J. of Man-Machine Studies, 5, pp.2l5-236.
Hollan, J., Hutchins, E., and Weitzman, L. (1984). STEAMER: An interactive inspectable simulation-based training system. AI Magazine, 5, 2, 15-27.
Ohlsson, S. (1986) Some principles of intelligent tutoring, Instructional Science, 14, 293-326.
Ohlsson, S. (1987). Some principles of intelligent tutoring. In Lawler, R. W. and Yazdani, M., editors,
Learning Environments and Tutoring Systems: Learning Environments and Tutoring Systems, volume 1, pages 203–237. Ablex Publishing, Norwood, New Jersey.
Richer, M. and Clancey, W.J. (1985) GUIDON-WATCH: A graphic interface for viewing a knowledge-based system.
IEEE Computer Graphics and Applications, 5(11):51-64. Also STAN-CS-85-1068, KSL 85-20.
Shortliffe, E.H. (1976) Computer-Based Medical Consultations: MYCIN. New York: American Elsevier.
Shute, V. J., and Psotka, J. (1994). Intelligent Tutoring Systems: Past, Present and Future. In D. Jonassen (Ed.),
Handbook of Research on Educational Communications and Technology, Scholastic Publications.
http://train.galaxyscientific.com/icaipage/its/its.htm
Stevens, A.L. & Collins, A (1977) The Goal Structure of a Socratic Tutor
BBN Technical Report No. 3518, Bolt Beranek and Newman Inc., Cambridge, Mass.
VanLehn, K. (1987). Learning one subprocedure per lesson.
Artificial Intelligence, 31(1):1–40.
Towne, D. M. and Munro, A. (1988) The intelligent maintenance training system. In J. Psotka, L. D. Massey, and S. A. Mutter (Eds.),
Intelligent tutoring systems: Lessons learned, pp 478-530. Hillsdale, NJ: Erlbaum, 1988.
Towne, D. M. and Munro, A. (1991) Simulation-based instruction of technical skills.
Human Factors, 33, 325-341.
Towne, D. M. and Munro, A. (1992) Two approaches to simulation composition for training. In M. Farr and J. Psotka (Eds.),
Intelligent instruction by computer: Theory and practice. London: Taylor and Francis, 1992.
VanLehn,K. (1987) Learning one sub-procedure per lesson,
Artificial Intelligence, 31, 1, pp.1-40.
White, B. Y., & Frederiksen, J. R. (1986). Progressions of quantitative models as a foundation for intelligent learning environments. Technical Report # 6277, BBN.
White, B. and Frederiksen, J. (1987) Qualitative Models and Intelligent Learning Environments, in Lawler, R. and Yazdani, M. (eds.), Artificial Intelligence and Education (vol. 1): Learning Environments and Tutoring Systems, Academic Press.
Woolf, B.P. and McDonald, D.D (1984). Context-dependent transitions in tutoring discourse.
Proceedings of the National Conference on Artificial Intelligence, Austin, Texas, pp.355-361.
Woolf, B.P., Blegen, D., Jansen, J.H., and Verloop, A., Teaching a Complex Industrial Process,
Proceedings of the National Conference on Artificial Intelligence, Philadelphia, Vol. II, 1986, pp. 722-728. [Recovery Boiler Tutor]
Woolf, B.P. (1988) Representing Complex Knowledge in an Intelligent Machine Tutor, in
Artificial and Human Learning, edited by Self, J., Chapman and Hall Computing.
________________________________________________
6. OTHER EXAMPLES USED IN LECTURES
Example from CBBC Schools: Alien Cookbook - teaches numeracy (5 to 7 year olds)
http://www.bbc.co.uk/schools/starship/maths/aliencookbook.shtml
________________________________________________
7. USER CENTRED AND PARTICIPATORY DESIGN
Druin
Conlon, T. & Pain, H. (1996). Persistent Collaboration: A Methodology for Applied AIED.
Journal of Artificial Intelligence in Education, Vol 7 No. 3/4 219-252.
Conlon, T. (1999). Alternatives to Rules for Knowledge-based Modelling.
Instructional Science Vol 27 No 6, pp 403-430.
References:
Conlon, T. & Bowman, N. (1995). Expert Systems, Shells, and Schools: Present Practice, Future Prospects.
Instructional Science, 23, 111
Conlon, T. (1995). Automated Analysis for Knowledge Based Modelling,
Workshop on Automated Program Analysis, Vanneste, P.; Bertels, K.; De Decker, B. (eds.) AACE, Washington, DC, pp 31-37
Cox, R. and Brna, P. (1995). Supporting the use of external representations in problem solving: the need for flexible learning
environments.
Journal of Artificial Intelligence in Education, 6(2/3).
de Vicente, A., Pain, H. (2002) Informing the detection of the students' motivational state: an empirical study. In S. A. Cerri, G.
Gouarderes, F. Paraguacu, editors,
Proceedings of the Sixth International Conference on Intelligent Tutoring Systems, volume 2363 of Lecture Notes in Computer Science, pages 933-943, Berlin. Heidelberg. Springer.
Hartley, J.R. and Sleeman, D. H. (l973). Towards more intelligent teaching systems,
Int. J. of Man-Machine Studies, 5, pp.2l5-236.
Hix, D. and Hartson, H. R. (1993).
Developing User Interfaces: Ensuring Usability through Product & Process. New York, John Wiley and Sons
Cercone, N., and McCalla, G. (1987) What is Knowledge Representation. The Knowledge Frontier: Essays in the Representation of Knowledge. N. Cercone and G. McCalla (eds), Springer-Verlag, 1-43.
Porayska-Pomsta, K. and Pain, H. (2004). Providing Cognitive and Affective Scaffolding Through Teaching Strategies: Applying
Linguistic Politeness to the Educational Context.
Intelligent Tutoring Systems 2004: 77-86
TLRP Vicar project http://www.tlrp.org/proj/phase111/cox.htm
________________________________________________
8. FORMATIVE AND SUMMATIVE EVALUATION
Shaaron Ainsworth 2003 tutorial slides: http://sydney.edu.au/engineering/it/~aied/Ainsworth_tutorial.pdf
Ainsworth (2003): Tutorial on Evaluation Methods for Learning Environments, presented at the AIED 2003 conference.
http://www.psychology.nottingham.ac.uk/staff/sea/Evaluationtutorial.ppt
Dix, A., Finlay, J., Abowd, G. and Beale, R. (2004). Evaluation Techniques. Chapter 9 of:
Human-Computer Interaction, (3rd edition) Pearson/Prentice Hall, Harlow, England. pp 318-364
References:
Ainsworth, S. E., Bibby, P., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics.
Journal of the Learning Sciences, 11(1), 25-61.
Ainsworth, S. E., & Grimshaw, S. K. (2002). Are ITSs created with the REDEEM authoring tool more effective than "dumb" courseware? In S. A. Cerri & G. Gouard�res & F. Paragua�u (Eds.),
6th International Conference on Intelligent Tutoring Systems (pp. 883-892). Berlin: Springer-Verlag.
Ainsworth, S. E., Wood, D., & O'Malley, C. (1998). There is more than one way to solve a problem: Evaluating a learning environment that supports the development of children's multiplication skills.
Learning and Instruction, 8(2), 141-157.
Arroyo, I., Beck, J. E., Woolf, B. P., Beal, C. R., & Schultz, K. (2000). Macroadapting animalwatch to gender and cognitive differences with respect to hint interactivity and symbolism. In G. Gauthier & C. Frasson & K. VanLehn (Eds.),
Intelligent Tutoring Systems: Proceedings of the 5th International Conference ITS 2000 (Vol. 1839, pp. 574-583). Berlin: Springer-Verlag.
Cohen, P. (1995) Empirical Methods for Artificial Intelligence, MIT Press, 1995.
Conlon, T. and Pain, H. (1996). Persistent collaboration: a methodology for applied AIED,
Journal of Artificial Intelligence in Education, 7, 219-252.
Corbett, A.T. and Anderson, J.R., (1990) The Effect of Feedback Control on Learning to Program with the Lisp Tutor,
Proceedings of the 12th Annual Conference of the Cognitive Science Society, LEA, New Jersey, 1990
Corbett , A. & Anderson, J. (1992). LISP intelligent tutoring system: Research in skill acquisition. In J. H. Larkin and R. W. Chabay, editors,
Computer-Assisted Instruction and Intelligent Tutoring Systems: Shared Goals and Complementary Approaches, pages 73-109. Lawrence Erlbaum
Cox, R., & Brna, P. (1995). Supporting the use of external representations in problem solving: The need for flexible learning environments.
Journal of Artificial Intelligence in Education, 6((2/3)), 239-302.
Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43.
Lesgold, A., Lajoie, S., Bunzo, M., & Eggan, G. (1992). Sherlock: A coached practice environment for an electronics troubleshooting job. In J. Larkin & R. Chabay (Eds.),
Computer Based Learning and Intelligent Tutoring (pp. 202-274). Hillsdale, NJ: LEA.
Lester, J. C., Converse, S. A., Stone, B. A., Kahler, S. A., and Barlow, S. T. (1997). Animated pedagogical agents and problem- solving effectiveness: A large-scale empirical evaluation. In du Boulay, B. and Mizoguchi, R.,
Proceedings of the AI-ED 97 World Conference on Artificial Intelligence in Education,, pages 23–30, Kobe, Japan. IOS Press.
Greer, J.E., McCalla, G.I., Cooke, J.E., Collins,J.A., Kumar, V.S., Bishop, A.S., Vassileva, J.I. (2000) Integrating Cognitive Tools for Peer Help: the Intelligent IntraNet Peer Help-Desk Project, in S. Lajoie (Ed.)
Computers as Cognitive Tools: The Next Generation, Lawrence Erlbaum , 69-96.
Luckin, R., & du Boulay, B. (1999). Ecolab: The Development and Evaluation of a Vygotskian Design Framework
. International Journal of Artificial Intelligence in Education, 10, 198-220.
Luckin, R., Plowman, L., Laurillard, D., Stratfold, M., Taylor, J., & S, C. (2001). Narrative evolution: learning from students' talk about species variation.
International Journal of AIED, 12, 100-123.
Luger, G. F. and Stubblefield, W. A., (1989) Artificial Intelligence and the Design of Expert Systems, Benjamin Cummings, 1989.
Mark, M.A. and Greer, J.E. (1993). Evaluation methodologies for intelligent tutoring systems,
Journal of Artificial Intelligence in Education, 4, 129-153.
Meyer, T. N., Miller, T. M., Steuck, K., & Kretschmer, M. (1999). A multi-year large-scale field study of a learner controlled intelligent tutoring system. In S. Lajoie & M. Vivet (Eds.),
Artificial Intelligence in Education - (Vol. 50, pp. 191-198).
Shute, V. J. (1995). SMART evaluation: Cognitive diagnosis, mastery learning and remediation. In J. Greer (Ed.),
Proceedings of AI-ED 95 (pp. 123-130). Charlottesville, VA: AACE.
Shute, V. J., & Glaser, R. (1990). A large-scale evaluation of an intelligent discovery world: Smithtown
. Interactive Learning Environments, 1, 51-77.
Shute, V. J., & Regian, W. (1993). Principles for evaluating intelligent tutoring systems.
Journal of Artificial Intelligence in Education, 4(2/3), 243-271.
Squires, D., & Preece, J. (1999). Predicting quality in educational software: Evaluating for learning, usability and the synergy between them.
Interacting with Computers, 11(5), 467-483.
Van Labeke, N., & Ainsworth, S. E. (2002). Representational decisions when learning population dynamics with an instructional simulation. In S. A. Cerri & G. Gouard�res & F. Paragua�u (Eds.),
Intelligent Tutoring Systems: Proceedings of the 6th International Conference ITS 2002 (pp. 831-840). Berlin: Springer-Verlag.
________________________________________________
9. INTERACTION AND EDUCATIONAL DIALOGUE
Brown, J.S., Burton, R. and Kleer , J. de (1982), Pedagogical, Natural Language and Knowledge Engineering Techniques in Sophie I, II, and III, in D. Sleeman and J. S. Brown (Eds.),
Intelligent Tutoring Systems, London, England: Academic Press.
Carbonell, J. R. (1970). AI in CAI: An artificial intelligence approach to computer-assisted instruction.
IEEE Transactions on Man-Machine Systems, 11(4), 190-202.
Hollan, J., Hutchins, E., AND Weitzman, L. (1984). STEAMER: An interactive inspectable simulation-based training system.
AI Magazine, 5, 2, 15-27.
Porayska-Pomsta, K. and Pain, H. (2004). Providing Cognitive and Affective Scaffolding Through Teaching Strategies: Applying Linguistic Politeness to the Educational Context.
Intelligent Tutoring Systems 2004: 77-86
See
http://www.cogsci.ed.ac.uk/~jmoore/tutoring/papers.html for various Beetle papers.
References:
Bloom, B.S. (ed.) (1956),
Taxonomy of educational objectives: The classification of educational goals. Handbook I, cognitive domain. London: Longman.
Brown, J.S., Burton, R, and Bell, A. (1975). SOPHIE: A Step Toward Creating a Reactive Learning Environment,
International Journal of Man-Machine Studies, Vol. 7, 1975.
Brown, P. & Levinson, S.C. (1987).
Politeness: Some universals in language use. New York: Cambridge University Press.
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P. and Glaser, R. (1989). Self-Explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(2): 145-182.
Chi, M. T. H., de Leeuw, N., Chiu, M-H. and Lavancher, C. (1994), Eliciting self-explanations improves understanding. Cognitive Science, 18(3): 439-477.
Chi, M. T. H., Siler, S.A., Jeong, H., Yamauchi, T. and Hausmann, R.G. (2001), Learning from Human Tutoring, Cognitive Science, 25: 471-533
De dVicente, A. & Pain, H. (2002). Informing the detection of the students’ motivatonal state: An empirical study. In S.A. Cerri, G. Gouard�res, & F. Paragua�u (Eds.),
Intelligent Tutoring Systems, 933-943. Berlin: Springer.
Fox. B.A. (1993), The Human Tutorial Dialogue Project: Issues in the design of instructional systems. Lawrence Erlbaum Associates, Hillsdale, NJ.
Graesser, A. C. and Person, N. K. (1994) Question asking during tutoring. American Educational Research Journal, 31 (1): 104-137.
Johnson, W.L. (2003). Interaction tactics for socially intelligent pedagogical agents.
Int’l Conf. on Intelligent User Interfaces, 251-253. New York: ACM Press.
Johnson, W.L., Rickel, J.W., and Lester, J.C. (2000): Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments. International Journal of Artificial Intelligence in Education 11, (2000) 47-78
Lepper, M. R. and Chabay, R. W. (1988) Socializing the intelligent tutor: Bringing empathy to computer tutors. In H. Mandl and A. Lesgold, editors, Learning Issues for Intelligent Tutoring Systems, pp 114-137. Springer-Verlag, New York.
Lepper, M.R., Woolverton, M., Mumme, D., & Gurtner, J. (1993). Motivational techniques of expert human tutors: Lessons for the design of computer-based tutors. In S.P. Lajoie and S.J. Derry (Eds.),
Computers as cognitive tools, 75-105. Hillsdale, NJ: Lawrence Erlbaum Associates.
Lester,J.C., Towns, S.G. and FitzGerald, P.J (1999) Achieving Affective Impact: Visual Emotive Communication in Lifelike Pedagogical Agents,
International Journal of Artificial Intelligence in Education, 10, 278-291
Merrill, D. C., Reiser, B. J., Ranney, M. and Trafton, J. G. (1992), Effective tutoring techniques: Comparison of human tutors and intelligent tutoring systems. Journal of the Learning Sciences, 2 (3): 277-305.
Ohlsson, S. and Rees, E. (1991), The function of conceptual understanding in the learning of arithmetic procedures. Cognition and Instruction, 8, 103-179.
Pilkington, R.M. (1999). Analysing educational discourse: The DISCOUNT scheme.
Technical report 99/2, Computer-Based Learning Unit, University of Leeds.
Porayska-Pomsta, K. (2004). Influence of Situational Context in Language Production: Modelling Teachers’ Corrective Responses. Ph.D. thesis, University of Edinburgh.
Rickel, J., and Johnson, W.L., (1999). Animated Agents for Procedural Training in Virtual Reality: Perception, Cognition, and Motor Control.
Applied Artificial Intelligence 13:343-382. See also:
http://www.isi.edu/isd/carte/carte-projects.htm
http://www.isi.edu/isd/VET/steve-demo.html
Richer, M. and Clancey, W.J. (1985) GUIDON-WATCH: A graphic interface for viewing a knowledge-based system.
IEEE Computer Graphics and Applications, 5(11):51-64. Also STAN-CS-85-1068, KSL 85-20.
Wenger, E. (1987) Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Francisco: Morgan Kaufmann.
Woolf, B. and J. Allen, (2000) Spoken language tutorial dialogue. In
Proceedings of the AAAI Fall Symposium on Building Dialogue Systems for Tutorial Applications.
________________________________________________
10. BUILDING AND EXPLORING DOMAIN MODELS
Conlon, T. (2000). A Cognitive Tool for Classification Learning. Revised version of paper presented at the
Ninth International Peg Conference (PEG99) on Intelligent Computer and Communications Technology, Exeter, UK, July 1999. Also available at http://www.parlog.com/impaper/index.html
Clancey, W. J. (1986). From Guidon to Neomycin and Heracles in twenty short lessons.
AI Magazine, 7(3), 40-60.
References:
Brown, J. S. and R. Burton (1975) Multiple Representations of Knowledge for Tutorial Reasoning in D. G. Bobrow and A. M. Collins (Eds.),
Representation & Understanding: Studies in Cognitive Science, New York: Academic Press, 1975.
Brown, J.S. , R. Burton, A. Bell, (1975) SOPHIE: A Step Toward Creating a Reactive Learning Environment,
International Journal of Man-Machine Studies, Vol. 7.
Brown, J.S., R. R. Burton and J. de Kleer (1982) Pedagogical, Natural Language and Knowledge Engineering Techniques in Sophie I, II, and III, in D. Sleeman and J. S. Brown (Eds.),
Intelligent Tutoring Systems, London, England: Academic Press.
Clancey, W.J. (1983) GUIDON,
Journal of Computer Based Instruction, 10:(1+2) 8-15.
Clancey,W. J. (1987) Knowledge-based Tutoring: The GUIDON Program, MIT Press.
Coller, L. D., Pizzini, Q. A., Wogulis, J., Munro, A. and Towne, D. M. (1991) Direct manipulation authoring of instruction in a model-based graphical environment. In L. Birnbaum (Ed.),
The International Conference on the Learning Sciences: Proceedings of the 1991 conference, Evanston, Illinois: Association for the Advancement of Computing in Education.
Cox, R. and Brna, P. (1995). Supporting the use of external representations in problem solving: the need for flexible learning environments.
Journal of Artificial Intelligence in Education, 6(2/3).
de Kleer, J. and Brown, J.S. (1992). Model-based Diagnosis in SOPHIE III,
Readings in Model-based Diagnosis, Hamscher, Walter; Console, Luca; de Kleer, Johan, (Eds.). San Mateo: Morgan Kaufmann Publishers; pp. 179 - 205.
Elsom-Cook, M. (1990) Guided Discovery Tutoring: A Framework for ICAI Research, Paul Chapman Publishing.
Feurzeig, W., Papert, S., Bloom, M., Grant, R., & Solomon, C. (1969) Programming language as a conceptual framework for teaching mathematics: final report on the first fifteen months of the Logo Project, submitted to the
U.S. National Science Foundation, Bolt, Beranek & Newman Inc. Report # 1889, November 30, 1969. Cambridge, MA: Bolt Beranek and Newman.
Lester, J.C., Towns, S.G. and FitzGerald, P.J. (1999). Achieving Affective Impact: Visual Emotive Communication in Lifelike Pedagogical Agents, International Journal of Artificial Intelligence in Education, 10, 278-291.
Munro, A., Johnson, M.C., Pizzini, Q.A., Surmon, D.S, Towne, D.M. and Wogulis, J.L. (1997). Authoring Simulation-Centered Tutors with RIDES, International Journal of Artificial Intelligence in Education, 8, pp 284-316.
also at
HTTP://btl.usc.edu/RIDES
See RIDES web page for other RIDES and RAPIDS related examples.
Shortliffe, E.H. (1976) Computer-Based Medical Consultations: MYCIN. New York: American Elsevier.
Towne, D. M. and Munro, A. (1988) The intelligent maintenance training system. In J. Psotka, L. D. Massey, and S. A. Mutter (Eds.),
Intelligent tutoring systems: Lessons learned, pp 478-530. Hillsdale, NJ: Erlbaum, 1988.
Towne, D. M. and Munro, A. (1991) Simulation-based instruction of technical skills.
Human Factors, 33, 325-341.
Towne, D. M. and Munro, A. (1992) Two approaches to simulation composition for training. In M. Farr and J. Psotka (Eds.),
Intelligent instruction by computer: Theory and practice. London: Taylor and Francis, 1992.
Rickel, J., and Johnson, W.L., (1999) Animated Agents for Procedural Training in Virtual Reality: Perception, Cognition, and Motor Control.
Applied Artificial Intelligence 13:343-382.
See also:
http://www.isi.edu/isd/carte/carte-projects.htm
http://www.isi.edu/isd/VET/steve-demo.html
________________________________________________
11. QUALITATIVE REASONING
SimForrest: see http://ddc.hampshire.edu/simforest/about/about.html
Tom Murray, Larry Winship, Roger Bellin, Matt Cornell (2001). Toward Glass Box Educational Simulations: Reifying Models for Inspection and Design.
AIED-2001 workshop: External Representations in AIED. (extended version)
[See: http://ddc.hampshire.edu/simforest/about/AIED2001WSGlassBoxFull.doc]
Murray, T. (2004).
Classroom Strategies for Simulation-Based Collaborative Inquiry Learning. (Extended version)
Proceedings of ICLS-2004, San Mateo, June, 2004.
[
See: http://ddc.hampshire.edu/simforest/about/2004ICLS_SimForest.ext.doc]
Ester Shartar, Scientific Inquiry What is it?(http://ddc.hampshire.edu/simforest/about/inquiry.html)
References:
Forbus, K. (1984), Qualitative process theory. Artificial Intelligence, 24, pp 85-168.
de Kleer, J . and Brown, J . (1984) A qualitative physics based on confluences, Artificial Intelligence, 24.
Salles, P., Bredeweg, B. and Winkels, R. (1997). Deriving Explanations form Qualitative Models, in B. du Boulay and R. Mizoguchi (eds.), Artificial Intelligence in Education: Knowledge and Media in Learning Systems, (Proceedings of AIED-97, Kobe, Japan), pages 474-481, IOS Press, Amsterdam.
Wenger, E. (1987) Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Francisco: Morgan Kaufmann.
White, B. Y., & Frederiksen, J. R. (1986). Progressions of quantitative models as a foundation for intelligent learning environments. Technical Report # 6277, BBN.
White, B. and Frederiksen, J. (1987) Qualitative Models and Intelligent Learning Environments, in Lawler, R. and Yazdani, M. (eds.), Artificial Intelligence and Education (vol. 1): Learning Environments and Tutoring Systems, Academic Press.
________________________________________________
12. STUDENT MODELLING
Sentance, S. (1997), A Rule Network for English Article Usage within an Intelligent Language Tutoring System ,
Computer
Assisted Language Learning, 10:2, 173 - 200
Extract from notes on ArtCheck
Burton,R.R. and Brown, J.S., (1982) An investigation of computer coaching for informal learning activities, in Sleeman, D.H. and Brown, J.S. (eds),
Intelligent Tutoring Systems, 79-98, London: Academic Press.
Burton, R.R. (1982) Diagnosing bugs in a simple procedural skill, in (eds.) D.Sleeman and J.S.Brown,
Intelligent Tutoring Systems, Academic Press, pp.157-184.
Clancey, W.J. (1983) GUIDON,
Journal of Computer Based Instruction, 10:(1+2) 8-15.
See also:
http://affect.media.mit.edu/publications.php
de Vicente, A., Pain, H. (2002) Informing the detection of the students' motivational state: an empirical study. In S. A. Cerri, G. Gouarderes, F. Paraguacu, editors,
Proceedings of the Sixth International Conference on Intelligent Tutoring Systems, volume 2363 of Lecture Notes in Computer Science, pages 933-943, Berlin. Heidelberg. Springer.
References:
Brown, J.S. and R.R.Burton, (1978) Diagnostic models for procedural bugs in basic mathematical skills,
Cognitive Science, 2, pp.155-192
Brown, J.S. & VanLehn, K. (1980). Repair theory: A generative theory of bugs in procedural skills.
Cognitive Science, 4, 379-426.
Brna, P., Self, J., Bull, S. and Pain, H. (1999). Negotiated collaborative assessment through collaborative student modelling. Proceedings of Workshop on Open, Interactive, and Other Overt Approaches to Learner Modelling,
AI-ED'99, Le Mans, France.
Burleson, W. and . Picard, R.W. (2004), Affective Agents: Sustaining Motivation to Learn Through Failure and a State of Stuck,
Social and Emotional Intelligence in Learning Environments Workshop In Conjunction with the 7th International Conference on Intelligent Tutoring Systems, August 31, 2004, Maceio - Alagoas, Brasil.
Burleson, W. (2006), Affective Learning Companions: Strategies for Empathetic Agents with Real-Time Multimodal Affective Sensing to Foster Meta-Cognitive and Meta-Affective Approaches to Learning, Motivation, and Perseverance, MIT PhD Thesis, September 2006.
Burton,R.R. and Brown, J.S., (1979) An Investigation of Computer Coaching for Informal Learning Activities,
International Journal of Man-Machine Studies, Vol. 11, January 1979.
Burton, R.R. and Brown, J.S., (1976) A Tutoring and Student Modeling Paradigm for Gaming Environments
, Proceedings for the Symposium on Computer Science and Education, Anaheim, CA, February 1976.
Clancey, W.J, (1979). Transfer of Rule-Based Expertise through a Tuturial Dialogue. Doctoral dissertation, Stanford University. STAN-CS-769.
Clancey,W. (1986) Qualitative Student Models', in
First Annual Review of Computer Science, ACM, pp. 381-450.
Conati, C. and Maclaren, H. (2004) Evaluating A Probabilistic Model of Student Affect.
Proceedings of the 7th Int. Conference on Intelligent Tutoring Systems, Maceio, Brazil
Cordova, D. I., & Lepper, M. R. (1996). Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice.
Journal of Educational Psychology, 88, 715-730.
de Vicente, A., Pain, H. (1999) Motivation self-report in ITS. In Lajoie, S. P. and Vivet, M., editors,
Proceedings of the Ninth World Conference on Artificial Intelligence in Education, pages 648-650, Amsterdam. IOS Press.
de Vicente, A. and Pain, H. (2000) A Computational Model of Affective Educational Dialogues.
Papers from the 2000 AAAI Fall Symposium: Building Dialogue Systems for Tutorial Applications, North Falmouth, Massachusetts, November 3-5, 2000. Technical Report FS-00-01, AAAI Press, Menlo Park, CA, USA. pp 113-121.
Goldstein, I.P. and Carr, B. (1977) The computer as coach: an athletic paradigm for intelligent education.
Proceedings of the ACM, 1977.
Goldstein, I.P. (1979). The Genetic Graph: A Representation of Procedural Knowledge.
International Journal of Man-Machine Studies, 1,11,(pp. 51-78).
Goldstein, I.P. (1982) The Genetic Graph: a Representation for the Evolution of Procedural Knowledge. In D. Sleeman and J.S. Brown, editors,
Intelligent Tutoring Systems, pages 51-78. Academic Press, London, 1982.
Kass, R. and Finin, T. (1988). The Need for User Models in Generating Expert System Explanations,
Technical Report MS-CIS-88-37, University of Pennsylvania.
Keller, J.M. (1983). Motivational design of instruction. In C.M. Reigeluth (Ed.).
Instructional design theories and models: An overview of their current status. Hillsdale, NJ: Erlbaum.
LeActiveMath http://www.leactivemath.org/
Lepper, M. R., Woolverton, M., Mumme, D. L., & Gurtner, J. (1993). Motivational Techniques of Expert Human Tutors: Lessons for the Design of Computer-Based Tutors. In S. P. Lajoie & S. J. Derry (Eds.),
Computers as Cognitive Tools (pp. 75-105). Hillsdale, NJ: Erlbaum
Malone, T. W., and M.R. Lepper. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R.E. Snow and M.J. Farr (Eds.),
Aptitude, Learning and Instruction III: Conative and Affective Process Analyses. Hillsdale, N.J.: Erlbaum, 1987.
Morales, R., Pain, H. and Conlon, T. (2000). Understandable learner models for a sensorimotor control task. In
Intelligent Tutoring Systems: Fifth International Conference, ITS 2000, G. Gauthier, C. Frasson and K. VanLehn, eds. no. 1839 in Lecture Notes in Computer Science. Springer-Verlag, Montreal, Canada. pp 222-231
Mota, S. and Picard, R.W. (2003), Automated Posture Analysis for Detecting Learner's Interest Level,
Workshop on Computer Vision and Pattern Recognition for Human-Computer Interaction, CVPR HCI, June, 2003.
Porayska-Pomsta, K. (2003) Influence of Situational Context on Language Production: Modelling Teachers' Corrective Responses. Unpublished PhD Thesis, University of Edinburgh.
Porayska-Pomsta, K. and Pain. H. (2004) Exploring Methodologies for Building Socially and Emotionally Intelligent Learning Environments,
Proceedings of the Workshop on Social and Emotional Intelligence in Learning Environments (SEILE), ITS 2004, Maceio, Brazil.
Porayska-Pomsta, K. and Pain, H. (2004). Providing Cognitive and Affective Scaffolding Through Teaching Strategies: Applying Linguistic Politeness to the Educational Context.
Intelligent Tutoring Systems 2004: 77-86
Sentance, S.E. (1993) Recognising and responding to English article usage errors: an ICALL based approach. Unpublished PhD thesis. University of Edinburgh.
Sleeman, D. and Brown, J.S. (1982), (eds)
Intelligent Tutoring Systems, Academic Press.
Shortliffe, E.H. (1976) Computer-Based Medical Consultations: MYCIN. New York: American Elsevier.
VanLehn,K. (1987) Learning one sub-procedure per lesson,
Artificial Intelligence, 31, 1, pp.1-40.
Wenger, E. (1987) Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Francisco: Morgan Kaufmann.
________________________________________________
13. TEACHING AND LEARNING STRATEGIES
Du Boulay, B. and Luckin, R. (2001) Modelling human teaching tactics and strategies for tutoring systems.
International Journal of Artificial Intelligence in Education, 12(3):235-256, 2001. See this paper also fo referencs from the lecture. Available as:
http://www.cogs.susx.ac.uk/users/bend/papers/ijaiedteachers.pdf
VanLehn, K. (2006) The behavior of tutoring systems. International Journal of Artificial Intelligence in Education. 16, pp 227-265
Also read:
du Boulay, B. (2006).
Commentary on Kurt VanLehn's "The Behavior of Tutoring Systems". International Journal of Artificial Intelligence in Education. 16, 267-270.
Lester, J. (2006).
Reflections on the KVL Tutoring Framework: Past, Present, and Future. International Journal of Artificial Intelligence in Education. 16, 271-276.
Also see
slides of example systems (mostly classic ones).
References:
Akhras, F. N. and Self, J. A. (2000). System intelligence in constructivist learning.
International Journal of Artificial Intelligence in Education, 11.
Anderson, J. R. & Reiser, B. J. (1985) The LISP Tutor
BYTE, 10, 4.
Anderson, J. R., Farrell, R., and Sauers, R. (1984). Learning to program in LISP.
Cognitive Science, 8, 87-129.
Anderson, J. R. and Reiser, B. J. (1985). The LISP tutor.
BYTE, 10(4):159–175.
More general Anderson paper:
Anderson, J.R., Boyle,F.B., Farrell,R. and Reiser, B.J. (1987), Cognitive Principles in the Design of Computer Tutors, Chapter 4 of Morris. P. (ed.)
Modelling Cognition. Wiley.
Anderson, J. R., Corbett, A. T., Koedinger, K. R., and Pelletier, R. (1995). Cognitive tutors: Lessons learned.
The Journal of the Learning Sciences, 4(2):167–207.
Arroyo, I., Beck, J. E., Woolf, B. P., Beal, C. R., and Schultz, K. (2000). Macroadapting animalwatch to gender and cognitive differences with respect to hint interactivity and symbolism. In
Intelligent Tutoring Systems: 5th International Conference, ITS2000, Montreal, number 1839 in Lecture Notes in Computer Science, pages 574–583. Springer, Berlin.
Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6):4–16.
WEST paper:
Burton, R.R. & Brown, J.S. (1982) An Investigation of Computer Coaching for Informal Learning Activites, in
Intelligent Tutoring Systems, edited by Sleeman, D. & Brown, J.S., Academic Press.
Chan, T.-W. and Chou, C.-Y. (1997). Exploring the design of computer supports for reciprocal tutoring.
International Journal of Artificial Intelligence in Education, 8(1):1–29.
GUIDON:
Clancey, W.J. (1983) GUIDON,
Journal of Computer Based Instruction, 10:(1+2) 8-15.
Clancey, W.J. (1982) Tutoring Rules for Guiding a Case Method Dialogue,
Intelligent Tutoring Systems edited by Sleeman, D. & Brown, J.S., Academic Press.
Clancey, W.J. (1987) Knowledge-Based Tutoring: the GUIDON Program, MIT Press.
Collins, A., Warnock, E. H., Aiello, N., and Miller, M. L. (1975). Reasoning from incomplete knowledge. In Bobrow, D. G. and Collins, A., editors,
Representation and Understanding, pages 383–415. Academic Press, New York.
Collins, A. and Brown, J. S. (1988). The computer as a tool for learning through reflection. In Mandl, H. and Lesgold, A., editors,
Learning Issues for Intelligent Tutoring Systems, pages 1–18. Springer- Verlag, New York.
Collins, A., Neville, P., and Bielaczyc, K. (2000). The role of different media in designing environments.
International Journal of Artificial Intelligence in Education, 11(2):144–162.
Collins, A. and Stevens, A. L. (1991). A cognitive theory of inquiry teaching. In Goodyear, P., editor,
Teaching Knowledge and Intelligent Tutoring, pages 203–230. Ablex Publishing Corporation, Norwood, New Jersey.
Collins, A., Brown, J.S. & Newman, S.E. (1986) Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics BBN Technical Report No. 6459 BBN Laboratories Incorporated, Cambridge, Mass. and in Resnick, L.B. (ed.),
Knowing, Learning and Instruction: Essays in honour of Robert Glaser, LEA, 1989.
Graesser, A. C., Person, N., Harter, D., and the Tutoring Research Group (2000). Teaching tactics in autotutor. In
Modelling Human Teaching Tactics and Strategies: Workshop W1 at ITS’2000, Montreal.
Grandbastien, M. (1999). Teaching expertise is at the core of ITS research.
International Journal of Artificial Intelligence in Education, 10(3–4):335–349.
Greer, J., McCalla, G., Collins, J., Kumar, V., Meagher, P. and Vassileva, J. (1998).Supporting peer help and collaboration in distributed workplace environments. International Journal of Artificial Intelligence in Education, vol. 9, pp 159-177.
Johnson, W.L., Rickel, J.W. and Lester, J.C. (2000). Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments. International Journal of Artificial Intelligence in Education, 11:47-78.
Koedinger, K. R., Anderson, J. R., Hadley, W. H., and Mark, M. A. (1997). Intelligent tutoring goes to school in the big city.
International Journal of Artificial Intelligence in Education, 8(1):30–43.
Koedinger, K. R., Corbett, A. T., Ritter, S., and Shapiro, L. J. (2000).
Carnegie learning’s cognitive tutor: Summary research results. Summary of research results available from CARNEGIE learning, Pittsburgh, www.carnegielearning.com.
Lajoie, S. P., and Lesgold, A. (1992). Apprenticeship training in the workplace: A computer-coached practice environment as a new form of apprenticeship. In M. Farr and J. Psotka (Eds.),
Intelligent instruction by computer: Theory and practice pp. 15-36. New York, NY: Taylor and Francis.
Lajoie, S. P., Wiseman, J., and Faremo, S. (2000). Tutoring strategies for effective instruction in internal medicine. In
Modelling Human Teaching Tactics and Strategies: Workshop W1 at ITS’2000, Montreal.
Lepper, M. R., Woolverton, M., Mumme, D. L., and Gurtner, J.-L. (1993). Motivational techniques expert human tutors: Lessons for the design of computer-based tutors. In Lajoie, S. P. and Derry, S. editors,
Computers as Cognitive Tools, pages 75–105. Lawrence Erlbaum, Hillsdale, New Jersey.
McArthur, D., Stasz, C. and Zmuidzinas, M. (1990) Tutoring Techniques in Algebra.
Cognition and Instruction, Volume
7, Issue
3 September 1990 , pages 197 - 244
Murray, T. (1999). Authoring Intelligent Tutoring Systems: An analysis of the state of the art. International Journal of Artificial Intelligence in Education, Vol 10 1, pp. 98-129.
Ohlsson, S. (1986) Some principles of intelligent tutoring, Instructional Science, 14, 293-326.
Ohlsson, S. (1987). Some principles of intelligent tutoring. In Lawler, R. W. and Yazdani, M., editors,
Learning Environments and Tutoring Systems: Learning Environments and Tutoring Systems, volume 1, pages 203–237. Ablex Publishing, Norwood, New Jersey.
Rickel, J., and Johnson, W.L., (1999) Animated Agents for Procedural Training in Virtual Reality: Perception, Cognition, and Motor Control.
Applied Artificial Intelligence 13:343-382.
See also:
http://www.isi.edu/isd/carte/carte-projects.htm http://www.isi.edu/isd/VET/steve-demo.html
Shute, V. J., and Psotka, J. (1994). Intelligent Tutoring Systems: Past, Present and Future. In D. Jonassen (Ed.),
Handbook of Research on Educational Communications and Technology, Scholastic Publications.
http://train.galaxyscientific.com/icaipage/its/its.htm
Shute, V. J. (1995). SMART: Student modelling approach for responsive tutoring.
User Modelling and User-Adapted Interaction, 5(1):1–44.
Spensley, F. & Elsom-Cook, M. (1988) Dominie: Teaching and Assessment Strategies,
CAL Research Group Technical Report No. 74, Open University, U.K.
Stevens, A.L. & Collins, A (1977) The Goal Structure of a Socratic Tutor
BBN Technical Report No. 3518, Bolt Beranek and Newman Inc., Cambridge, Mass.
VanLehn, K. (1987). Learning one subprocedure per lesson.
Artificial Intelligence, 31(1):1–40.
VanLehn, K., Ohlsson, S., and Nason, R. (1994). Applications of simulated students.
Journal of Artificial Intelligence in Education, 5(2):135–175.
Winne, P. H. (1997). Experimenting to bootstrap self-regulated learning.
Journal of Educational Psychology, 89(3):397–410.
Woolf, B.P. and McDonald, D.D (1984). Context-dependent transitions in tutoring discourse.
Proceedings of the National Conference on Artificial Intelligence, Austin, Texas, pp.355-361.
Woolf, B.P., Blegen, D., Jansen, J.H., and Verloop, A., Teaching a Complex Industrial Process,
Proceedings of the National Conference on Artificial Intelligence, Philadelphia, Vol. II, 1986, pp. 722-728. [Recovery Boiler Tutor]
Woolf, B.P. (1988) Representing Complex Knowledge in an Intelligent Machine Tutor, in
Artificial and Human Learning, edited by Self, J., Chapman and Hall Computing.
Workshop on Modelling Human Teaching Tactics And Strategies, Held in Conjunction with ITS 2000. See
http://www.cogs.susx.ac.uk/users/bend/its2000/webpagenode1.html
Andrew Littlejohn and Diana Hicks. A to Z of Methodology - From the Cambridge English for Schools Teacher's Books. Copyright Cambridge University Press. Gives a list of methods and explains each briefly in the context of English teaching.
http://ourworld.compuserve.com/homepages/A_Littlejohn/az.htm
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Other possibly useful references: TO BE UPDATED:
Conati, C., & VanLehn, K. (2000).Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation. International Journal of Artificial Intelligence in Education, 11, 389-415.
Gilmore, D. J. (1996). The relevance of HCI guidelines for educational interfaces.
Machine-Mediated Learning, 5(2), 119-133
.
MacLaren, & Koedinger, K (2002): When and Why Does Mastery Learning Work: Instructional Experiments with ACT-R "SimStudents".
ITS 2002 355-366
Murray, T. (1993). Formative Qualitative Evaluation for "Exploratory" ITS research.
Journal of Artificial Intelligence in Education, 4(2/3), 179-207.
Person, N.K., Graesser, A.C., Kreuz, R.J., Pomeroy, V., & TRG (2001). Simulating human tutor dialog moves in AutoTutor.
International Journal of Artificial Intelligence in Education. 12, 23-39.
Rogers, Y., Price, S., Harris, E., Phelps, T., Underwood, M., Wilde, D. & Smith, H. (2002) Learning through digitally-augmented physical experiences: Reflections on the Ambient Wood project. (Equator working paper) (see http://www.cogs.susx.ac.uk/interact/papers/pdfs/Playing%20and%20Learning/Tangibles%20and%20virtual%20environments/Rogers_Ambient_Wood2.pdf)
VanLehn, K., Ohlsson, S., & Nason, R. (1994). Applications of simulated students: An exploration
. Journal of AI in Education, 5, 135-175.
Wood, D. J., Underwood, J. D. M., & Avis, P. (1999). Integrated Learning Systems in the Classroom.
Computers and Education, 33(2/3), 91-108
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