Literaturnachweis - Detailanzeige
| Autor/inn/en | Bosman, Lisa; Kotla, Bhavana; Madamanchi, Aasakiran; Bartholomew, Scott; Byrd, Vetria |
|---|---|
| Titel | Preparing the Future Entrepreneurial Engineering Workforce Using Web-Based AI-Enabled Tools |
| Quelle | In: European Journal of Engineering Education, 48 (2023) 5, S.972-989 (18 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Zusatzinformation | ORCID (Byrd, Vetria) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0304-3797 |
| DOI | 10.1080/03043797.2022.2119122 |
| Schlagwörter | Entrepreneurship; Engineering Education; Labor Force Development; Artificial Intelligence; Computer Simulation; Educational Games; Internet; Student Attitudes; Supply and Demand; Information Management; Instructional Effectiveness; Undergraduate Students |
| Abstract | Artificial intelligence (AI) is a rapidly developing field with growing importance in engineering, mainly as it serves to better understand and manipulate big data. However, the literature is sparse on how to educate engineers on the use of AI applications. For many years, a role-playing simulation known as the 'Beer Distribution Game' has been a staple of industrial engineering education and an established vehicle for teaching the fundamentals of supply chain management (SCM) technology. The purpose of the study is to suggest an alternative and effective way to introduce AI and web-based games to students. This paper introduces and applies two types of web-based AI-enabled tools in a second-year industrial engineering classroom including OpexAnalytics (a web-based AI-enabled Beer Distribution Game learning module) and CompareAssess (a web-based AI-enabled tool to promote 'learning by evaluation'). Findings provide evidence of this 5-week web-based AI-enabled learning module's effectiveness in improving student perceptions and learning outcomes related to the intersection between supply chain management and artificial intelligence. The intention for this module was not to sufficiently prepare students for data science and artificial intelligence work assignments; however, this module offers a starting point for further skill development in higher-level coursework. (As Provided). |
| Anmerkungen | Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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