| Owner: |
Virginia Byrne
|
| Owner Email: |
virginia.byrne@morgan.edu
|
| Paper Title: |
Exploring Trustworthiness of AI in Higher Education Teaching, Learning, and Assessment: A Systematic Review of the Literature
|
| Session Title: |
Learning and Assessment (Table 37)
|
| Paper Type: |
Roundtable Presentation
|
| Presentation Date: |
4/11/2024
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| Presentation Location: |
Philadelphia, Pennsylvania
|
| Descriptors: |
Instructional Technology, Literature, Technology
|
| Methodology: |
Conceptual/Theoretical
|
| Author(s): |
Virginia Byrne, Morgan State University; Keshiyena Pieters, Morgan State University
|
| Unit: |
Division J - Postsecondary Education
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| Abstract: |
While trust is an essential aspect of implementing AI in Higher Education courses, the field is still grappling with what makes an AI technology trustworthy to students, faculty, administrators, or policymakers. To understand how trust is being considered, we conducted a systematic review of 127 peer-reviewed articles focused on AI in Higher Education teaching, learning, and assessment. Finding that few articles discuss trust, and - when they do - it is to tout the trustworthiness of their novel AI design, we compare how trustworthiness is defined in other fields (e.g., health care, computer science) to highlight gaps for future research.
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| DOI: |
https://doi.org/10.3102/2110380
|