Predicting What People Learn From Examples.
Abstract
Students often memorize a set of steps from examples in domains such as probability and physics, without inducing what subgoals those steps achieve. Such students fail to solve novel problems with identical goal structures but which do not permit exactly the same set of steps as the examples. This final report contains three papers that examine whether examples can help people to learn relevant subgoals for solving problems in a particular domain, and if learning the subgoals helps them to solve novel problems that involve those subgoals but require new steps for achieving them. It was hypothesized that when learners are encouraged to group steps from example solutions then they will be more likely to learn subgoals, perhaps through a self-explanation process. The connection between grouping and subgoal formation was supported by transfer results as well as analyses of participants' descriptions of how to solve problems. More generally, the fact that subgoals can effectively conveyed by examples and that those subgoals can aid transfer, has important implications for the design of training materials and tutoring environments.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 11, 1995
- Accession Number
- ADA294290
Entities
People
- Richard Catrambone
Organizations
- Georgia Tech