The development of an expert system for developing instructional objectives
Abstract
Education, whether it is training in the private sector or teaching in the public and private schools, has been looking for ways to increase effectiveness and productivity. Extensive research and development have been done for the various branches of the armed forces and private sector organizations, such as Bell Telephone and Arther Andersen, to find ways to automate instructional development. This project focused on one phase of the development process: writing instructional objectives. The goal was to create an expert system, following models by Gagne and Mager, to assist instructional developers in the writing of objectives. The expert system was evaluated through both formative and summative evaluation processes. The purpose of the formative evaluation was to find logic errors and aesthetic problems. Eight graduate students and two professional trainers were asked to evaluate the expert system. After correcting all the errors and problems found during the formative evaluation, the expert system was submitted to a summative evaluation. The users for this evaluation were thirty-five graduate students enrolled in design and media courses at Purdue University. The users wrote one or two objectives, completed a questionnaire, and answered several questions in an interview. The findings of this evaluation showed that although the users would use the program, they would not use it for an extended period. The users indicated that the program was a better teaching tool than productivity tool. The researcher did find that the program forced users to actually visualize the students performing the intended outcomes of the objectives. The desired goal of this project was to improve productivity and to help automate the writing of instructional objectives. Suggestions for further research were made in order to achieve the desired goal. These areas include further development of this expert system using neural network software. In addition, research should be conducted on integrating task analyses data, student learning styles information, and the methods used for selecting or developing media and materials. It is this combined knowledge base that will allow artificial intelligent systems to truly serve the needs of instructional designers in an effective way.
Degree
Ph.D.
Advisors
Russell, Purdue University.
Subject Area
Curricula|Teaching|Artificial intelligence|Educational software
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