Studies of Diagnosis and Remediation with High School Algebra Students
Abstract
This research note compares the effects of reteaching and different styles of error-based remediation. More research is needed to understand the factors which lead to successful remediation. Six studies discussed in this RN compare error-specific or model-based remediation (MBR) with reteaching in algebra. The results show that MBR and reteaching are both more effective than no tutoring, but MBR is not clearly more effective than reteaching. The results are discussed both in terms of stability of errors, and of their relevance to educational practice and the field of intelligent tutoring systems. Classical computer aided intelligence systems have been used to provide tutorial instruction and socratic or supportive problem solving. Tutorial systems aim to diagnose a student's errors and then to provide appropriate remediation. Supportive problem solving systems monitor the student's problem solving, and aim to provide help and advice whenever requested. The subfield of Intelligent CAI, or ITS (Intelligent Tutoring Systems), arose because workers felt that CAI was intrinsically limited, and in fact incapable of providing highly adaptive instruction.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1988
- Accession Number
- ADA199022
Entities
People
- Anthony E. Kelly
- D. Sleeman
- Joseph Moore
- R. Martinak
- R. Ward
Organizations
- Stanford University