Conference Session

DSAI Technical Session 4: Workshops, Professional Development, and Training

Collection

2025 ASEE Annual Conference & Exposition

Authors

yilin zhang, University of Florida; Bruce F. Carroll, University of Florida; Jinnie Shin, University of Florida; Kent J. Crippen, University of Florida

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

Paper ID #48016PEER HELPER (Peer Engagement for Effective Reflection, Holistic EngineeringLearning, Planning, and Encouraging Reflection) Automated Discourse AnalysisFrameworkyilin zhang, University of FloridaDr. Bruce F. Carroll, University of Florida Dr. Carroll is an Associate Professor of Mechanical and Aerospace Engineering at the University of Florida. He holds an affiliate appointment in Engineering Education. His research interests include engineering identity, self-efficacy, and matriculation of Latine/x/a/o students to graduate school. He works with survey methods and overlaps with machine learning using

Conference Session

DSAI Technical Session 9: Student Reflections, Metacognition, and Competency Mapping

Collection

2025 ASEE Annual Conference & Exposition

Authors

Juan Alvarez, University of Illinois at Urbana - Champaign; Max Fowler, University of Illinois at Urbana - Champaign; Jennifer R Amos, University of Illinois at Urbana - Champaign; Yael Gertner, University of Illinois at Urbana - Champaign

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

. 27–41. [6] Dastyni Loksa, Amy J. Ko, Will Jernigan, Alannah Oleson, Christopher J. Mendez, and Margaret M. Burnett. 2016. Programming, Problem Solving, and Self-Awareness: Effects of Explicit Guidance. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 1449–1461. https://doi.org/10.1145/ 2858036.2858252 [7] Wan Nor Afiqah Wan Othman and Aziman Abdullah. 2018. Assessing self-efficacy and college readiness level among new undergraduate students in computer science using metacognitive awareness inventory (MAI). IOP Conference Series: Materials Science and Engineering 342, 1 (apr 2018

Conference Session

DSAI Technical Session 4: Workshops, Professional Development, and Training

Collection

2025 ASEE Annual Conference & Exposition

Authors

Neel Manmohan Parekh, University of Florida; Kevin Scroggins, University of Florida; Yolanda Gil, University of Southern California; Emmanuel J Dorley, University of Florida

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

assessments: Shedding light on sequential conversation-based measurement,” International Journal of Assessment Tools in Education, vol. 10, no. Special Issue, pp. 194–207, 2023.[10] Y. Gil, E. Deelman, M. H. Ellisman, T. Fahringer, G. Fox, D. Gannon, C. Goble, M. Livny, L. Moreau, and J. Myers, “Intelligent workflow systems and provenance-aware software,” AI Magazine, vol. 38, no. 3, pp. 47–62, 2017.[11] S. Malallah, E. U. Osiobe, Z. Marafie, P. Henriquez-Coronel, L. Shamir, E. L. Carlson, and J. L. Weese, “Developing an instrument for assessing self-efficacy confidence in data science,” in 2024 ASEE Annual Conference & Exposition Proceedings, (Portland, Oregon), American Society for Engineering Education (ASEE), 2024

Conference Session

DSAI Technical Session 10: Research Infrastructure and Institutional Insights

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jordan Esiason, SageFox Consulting Group; Talia Goldwasser, SageFox Consulting Group; Rebecca Zarch, SageFox Consulting Group; Alan Peterfreund, SAGE

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

10 This web-based interactive document was designed to create 2-year to 4-year bridge programs 8 Positive identity development (for students) 8 a “Landscape Report” that provides the data sources and Positive self-efficacy development (for students) 7 means to describe the participation of people engaged in BIPOC mentoring programs 5 engineering pathways (from K–12 through employment), the Transfer coaching 3 Graduate–PhD bridge programs 1 capacity of the ecosystem to support engineering education

Conference Session

DSAI Technical Session 1: K–12 and Early Exposure to Data Science and AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Carrie Grace Aponte, Kansas State University; Safia Malallah, Kansas State University; Lior Shamir, Kansas State University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

significantly influence students’ careerinterest and perceived self-efficacy, which disproportionately discourages underrepresentedgroups such as females and minorities [5]. By focusing on providing equitable and engagingSTEM experiences, educators can foster broader confidence and interest in these fields. Earlyexposure to engaging and accessible STEM education not only prepares children for highereducation but also helps dismantle barriers that prevent many students from pursuing hardsciences [6].The deficiency in K-12 data science education, combined with the importance of early exposureto data science, inspired the development of this literature review. Young people should beequipped with the skills necessary to become educated and productive