Generalized Teaching Machine Decision Structure with Application to Speed Reading

Abstract

A relatively new type of automated instruction called the "computer-directed" teaching machine is discussed in this thesis. Typical present-day teaching machines either give every student the same instruction material or choose what material the student receives on the basis of his answer to the last question. The computer-directed machine chooses instruction material by making a statistical evaluation of the student's total behavior in comparison with other students' total behaviors. This machine's statistics are actually changed as new students take the course. Such a teaching machine can perform very much like a human tutor who adjusts his presentation to fit the individual student's capabilities and who improves his teaching technique with each student. In this paper a technique is suggested for comparing teaching machines. The machine's tutorial functions would be fitted to a very general model of the tutorial teaching cycle. This allows the various automated instruction devices to be discussed in terms of a common model. An application of the computer-directed machine was made to a speed reading course. Preliminary experiments with this course indicate that the computer-directed machine can perform like a human tutor.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1964
Accession Number
AD0602660

Entities

People

  • Theodore R. Strollo

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Computer Programming
  • Computer Programs
  • Computers
  • Contracts
  • Floating Point Operations
  • Information Processing
  • Input Output Devices
  • Instructions
  • Instructors
  • Materials
  • Maximum Likelihood Estimation
  • Probability Density Functions
  • Standards
  • Students
  • Teaching Machines
  • Teaching Methods

Readers

  • Computer Engineering
  • Instructional Design and Training Evaluation.
  • STEM Education

Technology Areas

  • AI & ML