Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Taiwo Raphael Feyijimi, University of Georgia; VARUN KATHPALIA, University of Georgia; Sarah Jane Bork, University of Georgia

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

classification [4, 14]. • Knowledge: Represents a theoretical and practical understanding, including core principles, methodologies, and advancements in electrical engineering. It focuses on technical areas such as electrical systems, engineering principles, and scientific concepts fundamental to the discipline [15]. • Skills: Divided into: ▪ Hard Skills: Tangible, teachable technical abilities (e.g., programming, circuit design, and data analysis) [16]. ▪ Soft Skills: Interpersonal and professional competencies (e.g., communication, teamwork, and problem-solving) essential for workplace collaboration and leadership [17]. • Abilities refer to innate or developed capacities, including cognitive

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

preprint arXiv:1811.03578, 2018. [5] F. Mohammed and F. Ozdamli, “A systematic literature review of soft skills in information technology education,” Behavioral Sciences (Basel), vol. 14, p. 894, October 2024. [6] S. M. Fiore and T. J. Wiltshire, “Technology as teammate: Examining the role of external cognition in support of team cognitive processes,” Frontiers in Psychology, vol. 7, p. 1531, 2016. [7] P. Griffin and E. Care, eds., Assessment and Teaching of 21st Century Skills: Research and Applications. Dordrecht: Springer, 2014. [8] O. for Economic Co-operation and Development, PISA 2015 Results: Collaborative Problem Solving. Paris: OECD Publishing, 2017. [9] Q. He, “Collaborative problem-solving design in large-scale

Conference Session

DSAI Technical Session 10: Research Infrastructure and Institutional Insights

Collection

2025 ASEE Annual Conference & Exposition

Authors

Julie M. Smith; Jacob Koressel; Sofia De Jesus, Carnegie Mellon University; Joseph W Kmoch; Bryan Twarek

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

.” Entity Verdict CSTA Standard Human different none ChatGPT different none Llama different none Claude similar to Compare tradeoffs associated with computing technologies that affect people’s everyday activities and career options.Table 6: Classification for Arkansas standard CSRB.Y1.10.7: “Research and identify diverse ca-reers and career opportunities (e.g., accessibility, availability, demand) that are influenced by com-puter science and the technical and soft skills needed for each.”there does not appear to be a close match to this standard in any of the CSTA standards. However,Claude categorized it as based on CSTA 3B-AP-4: “Compare multiple