2025 ASEE Annual Conference & Exposition

Quest: Human Learning - A Framework for Incorporating Generative-AI Teaching and Learning Instruction in STEM Pre-Service Teacher Preparation (Evaluation)

Presented at Pre-College Engineering Education Division (PCEE) Technical Session 19

Generative Artificial Intelligence (GenAI) offers tools to transform K-12 science, engineering, technology, and mathematics (STEM) education. Pre-service teachers are in a prime position to learn about and engage with this emergent technology, preparing them to enter the workforce with knowledge on how GenAI can impact the learning outcomes of their K-12 students.

This paper examines the implementation of GenAI ethics instruction in a pre-service teacher preparation program at a small engineering-focused R1 institution. The pre-service teacher preparation program, [PROGRAM], aims to prepare STEM students for teaching at any level. [PROGRAM] offers pathways for undergraduate and graduate students to obtain licensure for teaching in K-12 science, math, and computer science. Given the recent advances in GenAI, [PROGRAM] asks STEM students to develop innovative future-oriented STEM curriculum and instruction focused on the future of human and GenAI interaction.

This paper uses a case study approach to review curriculum and student artifacts related to GenAI ethics education in [PROGRAM]. We evaluate how robust the integration of GenAI ethics assignments is in the overall [PROGRAM] curricula. This is coupled with an examination of students’ work to explore how they are thinking and developing innovative curricula and instruction regarding GenAI ethics.

The review of [PROGRAM] curriculum shows that GenAI ethics instruction is most prevalent in courses focused on computer science education. Students focusing on math and science education pathways also engage in GenAI ethics instruction, though this is an area that is relatively ad-hoc and can be formalized to foster deeper understanding of human-GenAI interaction throughout the course. Examination of student artifacts is ongoing.

[PROGRAM]’s implementation of GenAI ethics education in a pre-service teacher education program empowers future K-12 educators to thoughtfully and responsibly integrate GenAI into the classroom to enhance learning experiences, support diverse learners, and prepare K-12 students for the future. As GenAI advances, teaching technological ethics with a focus on teaching future generations provides a novel pathway for STEM majors to reconnect with and define human talents and abilities to solve human problems and develop technological solutions.

Authors

Dr. Christine Liebe http://orcid.org/0000-0003-1313-0114 Colorado School of Mines [biography]

Christine Liebe is a computer science education researcher at the Colorado School of Mines. Her research interests include K-12 computer science curriculum, instruction, assessment, and teacher preparation. Additionally, she participates in statewide CS K
Dr. Sabina Anne Schill Colorado School of Mines [biography]

Sabina is the Interim Assistant Director or Teach@Mines at Colorado School of Mines. She got her PhD in Environmental Engineering from the University of Colorado Boulder and her BS in Physics from Westminster College in Salt Lake City. Sabina is interested in teaching, engineering education research, and K-12 STEM education.
C. Estelle Smith http://orcid.org/0000-0002-4981-7105 Colorado School of Mines [biography]

Dr. C. Estelle Smith is a Tenure-Track Assistant Professor in the Department of Computer Science at the Colorado School of Mines. Her research focuses on human-computer interaction, human-AI interaction, and social and collaborative computing. Since 2023, Dr. Smith has been continuously involved in efforts to assess and understand student adoption of Generative AI (GenAI) across campus. She participated in writing institution-wide policies for Mines, and she has given numerous guest lectures and organized numerous workshops on the ethics and use of GenAI in engineering education.
Jesan Ahammed Ovi Colorado School of Mines [biography]

Jesan Ahammed Ovi is a Ph.D. student in the Computer Science Department at the Colorado School of Mines, where he works as a Research Assistant under the supervision of Dr. Estelle Smith. His primary research area is Human-Computer Interaction (HCI), complemented by prior experience in Natural Language Processing (NLP) and data mining. Jesan was previously a faculty member at East West University. He also contributed to the “GenAI Adoption at Mines” research project, where he led data analysis efforts using advanced statistical and machine learning techniques.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

« View session