Literaturnachweis - Detailanzeige
| Autor/inn/en | Scull, W. Reed; Perkins, Mark Andrew; Carrier, Jonathan W.; Barber, Michael |
|---|---|
| Titel | Community College Institutional Researchers' Knowledge, Experience, and Perceptions of Machine Learning |
| Quelle | In: Community College Journal of Research and Practice, 47 (2023) 5, S.354-368 (15 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Zusatzinformation | ORCID (Scull, W. Reed) ORCID (Perkins, Mark Andrew) ORCID (Carrier, Jonathan W.) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1066-8926 |
| DOI | 10.1080/10668926.2022.2043202 |
| Schlagwörter | Community Colleges; Researchers; Knowledge Level; Artificial Intelligence; Affordances; Barriers; Institutional Research; School Personnel; Attitudes; Experience |
| Abstract | Given pressing enrollment, retention and completion issues at community colleges, the use of data analytic tools has gained more relevance for practitioners and scholars. Among these tools is machine learning, but its use is relatively new to community colleges and institutional research practice. This exploratory qualitative study examined a small sample of community college institutional research officers and their work, with attention paid to their understandings of machine learning. Results suggest that these institutional research officers see both possibilities in the use of machine learning but also see barriers to its adoption in their institutions. A discussion highlighting the study's results is then followed by noting the implications for current and future administrative practice and suggesting pathways for future research. (As Provided). |
| Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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