Conference Session

Technical Sessions 1

Collection

2024 Fall ASEE Mid-Atlantic Section Conference

Authors

Gonca Altuger-Genc, State University of New York, College of Technology at Farmingdale; Akin Tatoglu, University of Hartford

Tagged Topics

Professional Papers

request or can be more specific such as review for grammar, structure, punctuation, or flow. The decision of how they want ChatGPT to review their essays are carried out by students. The original version and the revised by ChatGPT version of the student essays are shown in Figure 5. Figure 5. Students' Essay and ChatGPT Review of the Students' Essay➢ Phase V – Outcomes Review and Post-Experience Survey: In the last phase, a discussion on the overall experience, and level of incorporation and the outcome quality of the essays are carried out followed by a post-experience survey developed by authors [1] and is a 5-point Likert scale survey as shown in Figure Q. Figure 6. Post-Experience Survey

Conference Session

Technical Sessions 4

Collection

2024 Fall ASEE Mid-Atlantic Section Conference

Authors

Tracey Carbonetto, Pennsylvania State University, Allentown

Tagged Topics

Diversity, Professional Papers

,modifications and improvements to a syllabus based on comments from the students maydemonstrate a method for syllabus improvement and show a correlation to student success. References:Carbonetto, T. (2024). Early Career Engineers’ Perspectives on Leadership Competency Development in Undergraduate Education (Publication No. 30994836) [Doctoral dissertation, Marshall University]. ProQuest Dissertations & Theses Global.Dann, R. (2014). Assessment as learning: Blurring the boundaries of assessment and learning for theory, policy, and practice. Assessment in Education: Principles, Policy & Practice, 21(2), 149-166.Farmer, W., & Hu, Q. (2018). FCL: A formal language for writing

Conference Session

Technical Sessions 5

Collection

2024 Fall ASEE Mid-Atlantic Section Conference

Authors

Matthew Fried, SUNY Farmingdale; Mohammad Alshibli

Tagged Topics

Diversity, Professional Papers

Technology, 58(1), 504-509. https://doi.org/10.1002/pra2.487[2] Dai, Y., Chai, C. S., Lin, P., Jong, M. S., Guo, Y., & Jian-jun, Q. (2020). Promoting students’well-being by developing their readiness for the artificial intelligence age. Sustainability, 12(16),6597. https://doi.org/10.3390/su12166597[3] Chiu, T. K. F. and Chai, C. S. (2020). Sustainable curriculum planning for artificialintelligence education: a self-determination theory perspective. Sustainability, 12(14), 5568.https://doi.org/10.3390/su12145568[4] Cavanagh, T. B., Chen, B., Lahcen, R. A. M., & Paradiso, J. (2020). Constructing a designframework and pedagogical approach for adaptive learning in higher education: a practitioner'sperspective. The International Review of

Conference Session

Technical Sessions 1

Collection

2024 Fall ASEE Mid-Atlantic Section Conference

Authors

Wenhai Li, Farmingdale State College; Yue Hung, Farmingdale State College; Reiss Guttman, Farmingdale State College; Sen Zhang, State University of New York, Oneonta; Ning Yu, State University of New York, Brockport

Tagged Topics

Professional Papers

dependencies in speech recognition and language translation, making them a key tool in voice-controlled robotics. • Week 5: Reinforcement Learning (RL) – The final lecture covers RL, focusing on how agents learn to maximize rewards through interaction with their environment. The lecture explains key RL concepts such as agents, states, actions, rewards, and policies. Students learn how reinforcement learning can be applied to robotics, where robots learn to optimize performance through trial and error. Concepts such as Q-learning and exploration vs. exploitation are briefly introduced, with practical examples tied to robotic systems.Since MET students generally have less experience with programming and

Conference Session

Technical Sessions 1

Collection

2024 Fall ASEE Mid-Atlantic Section Conference

Authors

Zhou Zhang, SUNY Farmingdale State College; Yizhe Chang, California State Polytechnic University, Pomona

Tagged Topics

Professional Papers

, July 26-29, 2022.[37] Kusam, V.A., 2024, “Generative-AI Assisted Feedback Provisioning for Project-based Learning in CS Education” (Doctoral dissertation).[38] Salinas-Navarro, D.E., Vilalta-Perdomo, E., Michel-Villarreal, R. & Montesinos, L., 2024, “Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment”, Education Sciences, Vol. 14, No, 1, p.83.[39] Li, H., Xu, T., Zhang, C., Chen, E., Liang, J., Fan, X., Li, H., Tang, J. & Wen, Q., 2024, “Bringing Generative AI to Adaptive Learning in Education”, arXiv preprint arXiv:2402.14601.[40] Weng, J.C., 2023, “Putting Intellectual Robots to Work: Implementing Generative AI Tools in Project Management”, NYU SPS