YAZDANI%UK.AC.EXETER.PC@AC.UK (09/28/86)
[Forwarded from the AI-Ed digest by Laws@SRI-STRIPE.]
Here I present a survey of Intelligent Tutoring systems which,
although not exhaustive, is intended to be a source of reference for further
development. I would like to know of other systems which I should add,
prefably getting enteries in my proposed format. However, if you can't
spend the time to do this if you just send me any references you may
have I shall try and extract the information myself. Also if you would
like to suggest changes to the format to make it more useful please
do so. I would like to send the final version to somewhere( like AI mag.
for publication) and shall acknowledge any help I get.
You can't use REPLY to get to me so you need to SEND me Email to
YAZDANI%UK.AC.EXETER.PC@UCL-CS.arpa
or post to
Dept. of Computer Sceince
University of Exeter
Prince of Wales Road
EXETER EX4 4PT
ENGLAND
Thanks
______
ACE
Subject: Nuclear Magnetic Spectroscopy
Aim: Monitor Deductive Reasonsing
Features: Problem solving monitor, accepts natural language input
System: MODULAR ONE
Reference:
Sleeman, D.H., and Hendley, R. J. (1982)
ACE: a system which analyses complex explanations
in Sleeman and Brown (eds.)
BUGGY & DEBUGGY
Subject: Arithmetic
Aim: Diagnose bugs from behaviour
Features: Procedural representation of misconceptions (bugs),
hypothesis generation, problem generation system: LISP
System: LISP
Reference:
Brown, R.R. (1982)
Diagnosing bugs in simple procedural skills
in Sleeman & Brown (eds.)
BLOCKS
Subject: Blocks game
Aim: Diagnosis
System: LISP
Reference:
Brown, J.S. and Brown, R. R. (1978)
"A paradigmatic example of an artificially intelligent
instructional system"
Int. J. of Man-Machine Studies Vol., 10, pp.232-339.
FGA
Subject: French Grammar
Aim: Analyse free form French sentences
Features: Separation of dictionary, grammar, parser and error
reporting, general shell idea, human controlled
teaching strategy
System: PROLOG
Reference:
Barchan, J. Woodmansee, B.J. and Yazdani, M. (1985)
"A Prolog-based tool for French Grammar Analysis"
Instructional Science, Vol. 14
GUIDON
Subject: Medical diagnosis
Aim: Using MYCIN for tutoring
Features: Overlay student model, case method, separate of domain
knowledge from teaching expertise
System: LISP
Reference:
Clancey, W.J. (1979)
Tutoring rules for guiding a case method dialogue
in Int. J. of Man-Machine Studies, Vol. 11 pp 25-49.
GEOMETRY Tutor
Subject: Geometry
Aim: Monitoring geometry proof problems
Features: Use of production rules to represent 'ideal student
model' and 'bug catalogue'
System: Franz LISP
Reference:
Anderson, J.R., Boyle, C.F. and Yost, G.
The Geometry Tutor
Proceedings of IJCAI-85
INTEGRATION
Subject: Calculus
Aim: To deal with student initiated examples of symbolic
integration
Features: Self-improvement
System: LISP
Reference:
Kimbal, R. (1982)
A self-improving tutor for symbolic integration
in Sleeman and Brown (eds.)
LISP Tutor
Subject: LISP programming
Aim: Teaching of introductory LISP programming
Features: Using deviation from ideal student model
System: Franz LISP on VAX
Reference:
Anderson, J.R. and Reiser, B. (1985)
The LISP Tutor
in Byte Vol. 10 No. 4
LMS (Pixie)
Subject: Algebra equetion solving
Aim: Building student models
Features: Given problems and students answers it hypothesizes
models for them; uses rules and mal-rules.
System: LISP
Reference:
Sleeman, D.A. (1983)
Inferring student models for intelligent computer-aided
instruction
in Michalsky, R. Carbonnel, J. and Mitchell, T. (eds.)
Machine Learning
Springer-Verlag/Toga Press
MENO
Subject: Pascal programming
Aim: Tutoring novice programmers in the use of planning
Features: Hierarchical representation of correct and incorrect plans
System: LISP
Reference:
Woolf, B. and McDonald, D.D.(1984)
Building a computer tutor: design issues
IEEE Computers Sept. issue, pp. 6l-73
MACSYMA ADVISOR
Subject: Use of MACSYMA
Aim: Articulate users misconceptions about MACSYMA
Features: Representation of plans
System: LISP
Reference:
Genesreth, M.R. (1977)
An automated consultant for MACSYMA
Proceedings of IJCAI-77
NEOMYCIN
Subject: Medical diagnosis
Aim: Using expert systems for tutoring
Features: Separate of domain knowledge from teaching expertise,
automatic explanation of experts' reasoning
System: LISP
Reference:
Hasling, D.W., Clancey, W.J. and Rennels, G. (1984)
Strategic explanations for a dioagnostic consultation system
PROUST
Subject: Pascal programming
Aim: Automatic debugger and tutor
Features: Use of problem descriptions
System: GCL LISP on IBM PC (micro-PROUST), LISP on VAXs
Reference:
Johnson, W. L. and Soloway, E. (1985)
PROUST
in Byte Vol. 10, No. 4.
QUADRATIC tutor
Subject: Calculus
Aim: Teaching quadrantic equations
Features: Teaching strategy represented as a set of production rules
System: LISP
Reference:
O'Shea, T. (1982)
A self-improving quadratic tutor
in Sleeman and Brown (eds.)
Scholar
Subject: Geography
Aim: Provide mixed-initiative dialogue
Features: Semantic network representation of knowledge
System: LISP
Reference:
Carbonnel, J.R. and Collins, A. (1973)
"Natural Semantics in Artificial Intelligence"
Proceedings of IJCAI-73
Proceedings of IJCAI-85
SOPHIE
Subject: Electronic trouble shooting
Aim: Teaching how an expert trouble shooter copes with rare
faults
Features: Semantic grammar for natural language diaglogue,
qualitative knowledge plus simulation, multiple
knowledge sources
System: LISP
Reference:
Brown, J.S., Burton, R. R. and de Kleer, J. (1982)
"Pedagogical, natural language and knowledge engineering
techniques in SOPHIE I, II and III
in Sleeman, D. and Brown, J.S. (eds.)B
SPADE
Subject: LOGO programming
Aim: To facilitate the acquisition of programming skills
Features: Intelligent editor which prompts the student with
menu of design alternatives
Reference:
Miller, M.L. (1982))
A Structured Planning and Debugging Environment
Inferring student models for intelligent computer-aided
in Sleeman and Brown (eds.)
STEAMER
Subject: Steam plant operation
Aim: Convey qualitative model of a steam plant operation
Features: Good graphics and mathematical model of the plant
System: LISP
Reference:
Holland, J.D., Hutchins, E. L. and Weitzmann, L. (1984)
"STEAMER: An interative inspectable simutation based
training system"
in The AI Magazine, Vol. 5. No. 2
TUTOR
Subject: Highway Code
Aim: Prototype framework for a wide variety of subjects
Features: Semantic grammar implemented in definite clause grammar,
representing value clusters, "what if" facility
System: Prolog on VAX and IBM PC AT
Reference:
Davies, N., Dickens, S. and Ford, L. (1985)
"TUTOR": A prototype ICAI system"
in M. Bramer (ed.) 'Research and Development in Expert
Systems'
Cambridge University Press
WEST
Subject: How the West was Won
Aim: Drill and Practice in arithmetic
Features: Hierarchical representation of correct and incorrect plans
System: PLATO
Reference:
Comparison of students' moves with experts' moves,
student model and diagnostic strategies, tutoring expert
WHY
Subject: Meteorology
Aim: Tutoring students about processes involved in rainfall
Features: Multiple representations in direct tuition
System: LISP
Reference:
Stevens, A. and Goldin, S. F. (1982)
Misdconceptions in student understanding
in Sleeman and Brown (eds.)
WUSOR
Subject: Maze exploration game (Wumpus)
Aim: Teaching logic and probability
Features: Graph structure whose nodes represent rules
System: LISP
Reference:
Goldstein, I. (1982)
"The genetic graph: A representation for evlution of
procedural knowledge"
in Sleeman and Brown (eds.)