- Conference Session
- Minorities in Engineering Division(MIND) Technical Session 2
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- 2025 ASEE Annual Conference & Exposition
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Aldo R Pinon Villarreal, Angelo State University
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Diversity
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Minorities in Engineering Division(MIND)
personalexperience relating to one of the topics covered in the course materials. The second high contextquestion was a fill in the gap series of questions in which they needed to identify the name of theconcept or equation after providing a description of a real-case scenario. See Figure 1. To deterstudents from copying or collaborating with others, a total of three different exam versions werereleased and the included numeric problems were not previously published so they coul d not befound online. ChatGPT had not been released yet so it had no effect on this investigation, but itwould need to be addressed for future applications.Figure 1. Excerpt from a fill-in-the gap question series to identify the name of the concept orequation by providing them a
- Conference Session
- Minorities in Engineering Division(MIND) Technical Session 11
- Collection
- 2025 ASEE Annual Conference & Exposition
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Haya Alshayji, Pennsylvania State University; Deja Workman, Pennsylvania State University; Swapnika Dulam, Pennsylvania State University; Lauren A Griggs, The Pennsylvania State University; Dixon Zor, Pennsylvania State University; Christopher L Dancy, The Pennsylvania State University, University Park
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Diversity
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Minorities in Engineering Division(MIND)
://doi.org/10.1145/3375627.3375868[7] J. Borenstein and A. Howard, “Emerging challenges in AI and the need for AI ethicseducation,” AI and Ethics, 2021[8] J. Borenstein and A. Howard, “Emerging challenges in AI and the need for AI ethicseducation,” AI Ethics, vol. 1, pp. 61–65, 2021. doi: 10.1007/s43681-020-00002-7. [Online].Available: https://doi.org/10.1007/s43681-020-00002-7[9] S. Wang, T. Xu, H. Li, C. Zhang, J. Liang, J. Tang, P. S. Yu, and Q. Wen, “Large LanguageModels for Education: A Survey and Outlook,” arXiv preprint, vol. abs/2403.18105, 2024.[Online]. Available: https://arxiv.org/abs/2403.18105[10] E. Kasneci et al., “ChatGPT for Good? On Opportunities and Challenges of Large LanguageModels for Education.” Center for Open Science, 2023
- Conference Session
- Minorities in Engineering Division(MIND) Technical Session 1
- Collection
- 2025 ASEE Annual Conference & Exposition
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Nia A. Keith, Purdue University College of Engineering; Jacqueline E McDermott, Purdue University at West Lafayette (COE)
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Diversity
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Minorities in Engineering Division(MIND)
includedstudent experiences, feedback on program sessions, and suggestions for improvement. Next,feedback was separated by years (2017-2019, 2020-2023, and 2024) based on the different EarlyDiscovery program formats and input into Open AI software (ChatGPT), with the command ofidentifying the most frequently used words. These frequently used words were inserted into aword cloud generator website (https://www.freewordcloudgenerator.com/) to visually representthese terms. The final word cloud result provides a visual of the student feedback and keytakeaways from their experiences.Results and DiscussionThe three different Early Discovery program formats have their own goals, frameworks,benefits, and limitations (RQ1)To determine which Early Discovery