Literaturnachweis - Detailanzeige
Autor/inn/en | Hershkovitz, Arnon; Ambrose, Alex |
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Titel | Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students |
Quelle | In: Journal of Learning Analytics, 9 (2022) 2, S.202-217 (16 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Hershkovitz, Arnon) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
Schlagwörter | College Freshmen; College Faculty; Academic Advising; Low Achievement; Identification; Student Motivation; Learner Engagement; Study Habits; Student Characteristics; At Risk Students; Attendance Patterns; Indiana |
Abstract | In this qualitative study (N=6), we explored insights of first-year students' instructors and advisors into an early identification system aimed at detecting non-thriving students in the context of an all-campus first-year orientation course for undergraduates. Following the development of that prediction model in a bottom-up manner, using a plethora of available data, we focus on how its end-users could help us understand the underlying mechanisms that drive the identification of non-thriving students. As findings suggest, participants were appreciative overall of the prediction and its timing and came up with various behaviours that could explain non-thriving, mostly motivation and engagement. They suggested additional data that could predict non-thriving, including background information, academic engagement, and learning habits. (As Provided). |
Anmerkungen | Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: https://learning-analytics.info/index.php/JLA/index |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |