Advanced Interactive Learning
Environments UG4/MSc 2011-2012
will be updated
throughout course
READINGS, LINKS and OTHER Materials
Last updated: 16th February 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.
________________________________________________
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.
________________________________________________
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.
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
________________________________________________
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."
________________________________________________
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
________________________________________________
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,
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Social
and Emotional Intelligence in Learning Environments
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31,
2004,
Maceio - Alagoas, Brasil.
Burleson, W. (2006), Affective
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Multimodal Affective Sensing to Foster
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and Perseverance, MIT PhD Thesis, September
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________________________________________________
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.
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to gender and cognitive
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Bloom, B. S. (1984). The 2
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Educational
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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
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GUIDON:
Clancey, W.J. (1983) GUIDON,
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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
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from
incomplete
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Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and
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D., and the Tutoring Research Group (2000). Teaching tactics in
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Grandbastien, M. (1999).
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International Journal of Artificial
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Greer, J.,
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Johnson,
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(1997). Intelligent tutoring goes to school in the big city.
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Apprenticeship training in the workplace: A computer-coached practice
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in internal medicine. In
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at ITS’2000, Montreal.
Lepper, M. R., Woolverton, M., Mumme,
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expert human tutors: Lessons for the design of
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Rickel, J., and Johnson, W.L., (1999)
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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.),
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http://train.galaxyscientific.com/icaipage/its/its.htm
Shute, V. J. (1995). SMART: Student modelling approach for
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User Modelling
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Spensley, F. & Elsom-Cook, M. (1988) Dominie: Teaching and
Assessment Strategies,
CAL Research
Group Technical Report No. 74, Open
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Stevens, A.L. & Collins, A (1977) The Goal Structure of a
Socratic Tutor
BBN Technical Report
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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.
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Woolf, B.P. and McDonald, D.D (1984). Context-dependent
transitions in tutoring discourse.
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Woolf, B.P., Blegen, D., Jansen, J.H., and Verloop, A., Teaching
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[Recovery Boiler Tutor]
Woolf, B.P. (1988) Representing Complex Knowledge in an
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Learning, edited by Self, J.,
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Held in Conjunction with ITS 2000. See
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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
___________________________________________
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
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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
___________________________________________
