dayuso@BBN.COM ("Damaris M. Ayuso") (06/20/89)
BBN STC Science Development Program
AI Seminar Series Lecture
KNOWLEDGE REPRESENTATION AND EXPLANATION
IN AN INTELLIGENT TUTORING SYSTEM FOR PROGRAMMING
Brian J. Reiser
Princeton University
bjr@confidence.Princeton.edu
BBN STC, 2nd floor large conference room
10 Moulton St, Cambridge MA, 02138
Friday June 23rd, 10:30 AM
I will describe an intelligent tutoring system for programming called
GIL (Graphical Instruction in LISP) that constructs explanations
directly from the content of its problem solving knowledge. GIL
provides feedback by comparing a student's solution to its problem
solving model. GIL's problem solving rules not only encode what step
to take in each problem situation, but also can reason about why each
step is effective. Explanations are constructed dynamically rather
than being prepared in advance for each situation in which feedback is
required. The tutor is embedded in a graphical programming
environment so that students work in a medium that more closely
corresponds to their planning operations. GIL produces reasonable
explanations for a wide variety of errors concerning approximately 200
rules and high-level plans used in an introductory programming lesson.
I will describe studies of students learning to program using GIL and
working with human tutors, and consider: (1) how GIL's graphical
representation facilitates students' reasoning, (2) how GIL's
explanations enables students to learn more effectively from their errors,
and (3) the ways in which the pedagogical strategies and
effectiveness of human tutors are modeled in GIL.