Using Artificial Intelligence Techniques to Assist Faculty Advisors in Accurate Student Advising at The University Level
Date of Award
Doctor of Science
Center for Computer-Based Learning
Dennis D. Murphy
Gerorge K. Fornshell
This study addressed the design and development of a personal computer-based knowledge system to assist inexperienced faculty with the academic advising process for students in the Department of vocational Education at Old Dominion University.
The goals of this project included:
- Improving the timeliness and accuracy of student advising
- Examine the possibility of using a personal computer-based knowledge system to improve access to complex advising information, and
- Developing an advising knowledge system model that could be easily modified for other program areas in the Department of vocational and Technical Education.
The software product that was developed as a result of this dissertation was called EASE or Easy Advising Expert Software. EASE was developed through a knowledge acquisition process that involved a series of interviews with an advising expert in the Department of Vocational and Technical Education. Knowledge acquisition techniques included audio tape recorded interviews and video tape recorded advising sessions. The knowledge acquisition process proved to be a critical element in defining information-based problems associated with the advising process. Later, a fact list was prepared that addressed information and questions that were typically and atypically encountered during advising sessions with a student.
An expert system knowledge base was prepared using a Production Rule Language (PRL), unique to the Level5 Expert system software that was used in developing an implementation version of EASE. The operation of EASE is a user-friendly backward chaining knowledge base system that provides the user with a goal selection option of choosing an area of advising information where help is needed. Alternately, the knowledge system can be used for a complete advising session that addresses all requirements for a degree program in Technology Education. This includes recommendations for semester course selections, an advising session report, and a graduation review check. Thus, EASE provides the user with access to information about course offerings, prerequisites for courses, program requirements, and degree requirements that is characteristically associated with the experiences of an expert advisor. The knowledge acquisition processes and advising expert system that has resulted from this project can serve as a model for developing advising knowledge systems for other organizations that have experienced information-based problems in the academic advising process.
Walter F. Deal III. 1988. Using Artificial Intelligence Techniques to Assist Faculty Advisors in Accurate Student Advising at The University Level. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Center for Computer-Based Learning. (481)