An investigation into experts' opinions of the role of artificial intelligence in college engineering and science curricula during the next five years
Abstract
The purpose of this study was to determine experts' opinions of what role artificial intelligence will play within the next five years in engineering and science education at the college level. There were two major purposes for this study: to determine what types of artificial intelligence are currently being taught in the college engineering and science curricula and to gain information that would enable colleges and universities, with input from business and industry, to determine whether their graduates are appropriately prepared for entering the work force. When considering the future and the proposed future, this study asked its respondents to project out five years. This period of time was chosen as it was sufficient to allow curricular changes to be made and implemented, to encompass the next couple of generations of hardware and software, and to allow for faculty turnover and publication cycles. A survey questionnaire consisting of twenty-three questions concerning artificial intelligence in engineering and science curricula was presented to a sample of seventy-five experts in college and university environments, to seventy-five experts in business and industry and to three futures experts. Each of the experts had shown an interest in artificial intelligence as evidenced by current work in this area. The survey method followed the practices in the Total Design Method (Dillman, 1978) for surveys. The overall response rate was 47.33%. The results indicated that artificial intelligence will play an increased role within the next five years in these areas. Both university and industry respondents saw this increase occurring in most of the AI areas rather than in one or two primary areas. However, there were some notable differences of opinion, for example, in the areas of expert systems, handwriting recognition and neural networks. These differences should be examined further to determine whether they might be indicative of a discrepancy between university preparation of students and industry expectations.
Degree
Ph.D.
Advisors
Lehman, Purdue University.
Subject Area
Curricula|Teaching|Computer science|Artificial intelligence|Educational software
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