Session: 09-01-05: Curriculum Innovations, Pedagogy and Learning Methodologies, Globalization of Engineering and Engineering Accreditation

Paper Number: 146093

146093 - Chat Gpt Inclusive Student Active Teaching for Engineering Education 

ChatGPT assistive tool can dramatically enhance or limit the intellectual growth of engineering students Based on the ways of utilizing it. The utilization of ChatGPT in the after-class assignments given generally after the instructor-focused lectures-based courses is considered a challenge when separating students' original work from the copy-pasted portion from the AI resources. Here, we present a case study of how ChatGPT was utilized to enhance student mastery of the course content when applied in Student Presentation-based Effective Teaching (SPET). Under this approach, students are allowed to use ChatGPT or any AI resource along with the suggested textbook to prepare answers to the questions regarding the upcoming discussion topics. Students generally get 7-15 days to do self-study and independently answer the questions posted before the discussion date. In addition, students are expected to work in 3-5 student groups to prepare a group presentation to answer the same questions they answered individually to develop a threshold level of content mastery and familiarity with the concepts to be discussed. Students are required to submit individual and group presentations by the discussion date in the scheduled class. Students are provided instructions about the rubric that will be used for evaluating the student's mastery and efforts. Generally, 30% marks are assigned to the level of completion of the assigned questions, 20% grade for the quality of presentation, and 30% grade is assigned for the quality of presentation and demonstrating mastery by giving examples and analogies. 20% marks are assigned for answering the questions or "what if" scenario. This approach allowed us to gauge the level of concept mastery of individual students. Advantageously, the instructor also provided additional insights and explanations to add to the students' self-developed understanding during the class discussion. During the class, each group comes to the stage to present the answers to the questions given to them by going over the specific section that the group decided on as a team. As per the rubric, each student is responsible for understanding the whole presentation. During the class discussion, students reflect on the nature of content obtained from ChatGPT. This approach was applied to the MECH 500 Resaerch Method and Technical Communication Course. This course provides an in-depth understanding of journal writing skills, positive intelligence for enhancing student learning potential and mental resilience, efficient methods of optimizing resaerch parameters using industrially tested Taguchi Design of Experiment, NSF-Graduate Resaerch Fellowship proposal development. Students also discussed the efficacy of ChatGPT regarding different topics. As a major highlight, all the students earned at least a C grade. Even though the level of mastery of content varied among the students, all the students were able to show the critical level of mastery to demonstrate their proficiency. ChatGPT was least helpful in covering the topic of positive intelligence because there was only one key website to serve as the content source. All the students typically came up with a similar-looking response to questions in the assignment on the topic of Positive Intelligence. However, ChaTGPT was extremely useful when many wide-ranging resources were available. As a major success of this approach, all 16 graduate students actively participated in the course activities. In the end, students participated in the resaerch project to gain insights about the AI tool limitations regarding creativity and critical thinking. This paper will discuss the details of several class modules and analysis of learning outcomes.

Presenting Author: Pawan Tyagi University of the District of Columbia

Presenting Author Biography: Prof. Pawan Tyagi is currently leading the NSF-CREST Center for Nanoscale Research and Education (CNRE). He is also the director of the DOE-NNSA Sponsored Consortium of Additive Manufacturing Post Processing Partnerships (AMP3)-his consortium is a group of four HBCUs and three DOE industries. Prof. Pawan Tyagi's expertise is in the area of integrating nanomaterials into devices and sensors to advance futuristic computer technology, biomedical devices, energy technology, and advanced manufacturing. He has made a seminal contribution in the area of tunnel junction-based molecular spintronics devices. At the University of the District of Columbia, he is serving as the founder and director of the Nanotechnology Application Laboratory and leading several federally funded projects. Prof. Tyagi has published more than 50 publications, including more than 15 students as coauthors. He has two awarded patents and five pending patents. Two pending patents are with his undergraduate and graduate students. Prof. Tyagi has 24 years of experience in materials science, arising from his BS and MS in metallurgical and materials engineering at the Indian Institute of Technology (IIT), industrial career, doctoral study at the University of Kentucky, and postdoctoral research at Johns Hopkins University. Prof. Tyagi is a passionate teacher and has attained training in effective teaching from renowned teaching experts. He has invented a new teaching approach, namely Student Presentation Based Effective Teaching (SPET). SPET is especially suitable for busy professors teaching advanced engineering courses. Prof. Tyagi is advancing SPET to teach science and engineering courses to students from high school to Ph.D. level.

Authors:

Pawan Tyagi University of the District of Columbia
Ali Alshweiki University of the District of Columbia