Causal Models in the Acquisition and Instruction of Programming Skills
Abstract
This research explores the relation between mental models and rule- based models of problem solving skill. The objective is a theory of the background knowledge that underlies problem solving rules and is needed for explanations. The instructional objective is to investigate how to construct an explanation that incorporates a description of the rule to be learned and its underlying justification. We are now pursuing a research program that draws on four areas: (1) GIL - The Graphical Instruction in LISP system is an intelligent tutoring system for programming that constructs explanations directly from its problem solving knowledge. (2) GLEE - The Graphical LISP Exploratory Environment is a graphical programming environment based on the graphical representations use in GIL, but providing the students more freedom to explore and test their hypotheses. (3) Human Tutors - We are conducting experiments to investigate the tutoring strategies and learning consequences of instruction by human tutors and consultants. (4) BAT Book - The Behavioral Analogy Tracing Environment is an online book and problem solving environment that facilitates students' use of example in a text book and use of their own solutions to previous problems. (kr)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1990
- Accession Number
- ADA226206
Entities
People
- Brian J. Reiser
Organizations
- Princeton University