Competency-Based Assessment in the Era of Generative Artificial Intelligence: Perspectives of Selected STEM Educators

Authors

  • Friday Joseph AGBO School of Computing and Information Sciences, Willamette University Author
  • Heather Kitada SMALLEY School of Computing and Information Sciences, Willamette University Author
  • Kathryn NYMAN College of Arts and Sciences, Willamette University Author

DOI:

https://doi.org/10.58459/icce.2024.4970

Abstract

Generative Artificial Intelligence (GenAI) has come to stay, and educators are exploring its usage in diverse contexts. One pertinent question begging for an answer is how educators integrating GenAI tools can equitably assess students' learning outcomes. This study explores the mixed-method approach, consisting of a rapid literature review and an analysis of experts' perspectives to address this question. We analyze data from the Scopus and Web of Science databases from the rapid review to understand how the use of GenAI is penetrating the STEM field. On the other hand, the thematic analysis of data generated from a ten-week-long group learning circle discussion among STEM professors regarding assessment in the era of the GenAI was used to gain understanding of educators' perspectives regarding how students' learning could be assessed in a classroom where GenAI tools are used. Our findings provide insights regarding how, where, and when to integrate GenAI in STEM classes and potential assessment strategies that could foster trust and transparency between educators and students. This study contributes to the growing body of literature on GenAI in STEM education. It offers implications from the perspective of contextual adoption of assessment strategy in the era of GenAI rather than the traditional approach of one-size-fits-all.

Downloads

Download data is not yet available.

Downloads

Published

2024-11-25

How to Cite

Competency-Based Assessment in the Era of Generative Artificial Intelligence: Perspectives of Selected STEM Educators. (2024). International Conference on Computers in Education. https://doi.org/10.58459/icce.2024.4970