Beyond Word Processing: Using an Interactive Learning Environment to Teach Writing.

Abstract

This study examines whether computer-aided instruction that explicitly models the process of composing for basic writers is more effective than traditional classroom instruction. Three objectives guided the research: to determine the basic quality of essays from the treatment and the control group using standard, holistic rating methods; to infer cognitive development by measuring improvement along four separate measures using an analytic scale; to determine whether initial aptitude was a factor in performance differences. Eight-hundred and fifty-two eighth-grade English students (423 in the control group and 429 in the treatment group) completed a 40-minute transactional writing sample at the beginning and at the end of a 16-week semester. The results show that the group using a computerized cognition facilitator outperformed the group taught only in the traditional classroom both on the holistic and on the analytical measures. Additionally, when the population was partitioned to reflect initial ability the treatment group in the lower segment showed marked improvement, whereas the high-end segment of the treatment group produced no significant gain. When partitioned in the same manner, the high-end for the control group degraded in performance, while the lower-end control improved both on the holistic and the analytic measures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1996
Accession Number
ADA319034

Entities

People

  • Patricia A. Carlson
  • Todd M. Miller

Tags

DTIC Thesaurus Topics

  • Cognition
  • Computer-Aided Instruction
  • Computers
  • Environment
  • Instructions
  • Learning
  • Mental Processes
  • Psychological Phenomena And Processes
  • Standards
  • Students

Fields of Study

  • Education

Readers

  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.
  • STEM Education
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference