How Can Predictive Learning Analytics and Motivational Interventions Increase Student Retention and Enhance Administrative Support in Distance Education?

Autor/inn/en	Herodotou, Christothea; Naydenova, Galina; Boroowa, Avi; Gilmour, Alison; Rienties, Bart
Titel	How Can Predictive Learning Analytics and Motivational Interventions Increase Student Retention and Enhance Administrative Support in Distance Education?
Quelle	In: Journal of Learning Analytics, 7 (2020) 2, S.72-83 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Herodotou, Christothea)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	Learning Analytics; Predictive Measurement; Student Motivation; Intervention; Program Effectiveness; Cost Effectiveness; School Holding Power; Academic Persistence; At Risk Students; Undergraduate Students; Open Universities; Learner Engagement; Distance Education; Identification; Telecommunications; Electronic Mail; Foreign Countries; Academic Support Services; United Kingdom + Suchen Sie Ihr Suchwort? Schulische Motivation; Kosten-Nutzen-Analyse; Kosten-Nutzen-Denken; Offene Universität; Distance study; Distance learning; Fernunterricht; Identifikation; Identifizierung; Telekommunikationstechnik; Elektronischer Briefkasten; Ausland; Großbritannien
Abstract	Despite the potential of Predictive Learning Analytics (PLAs) to identify students at risk of failing their studies, research demonstrating effective application of PLAs to higher education is relatively limited. The aims of this study are: (1) to identify whether and how PLAs can inform the design of motivational interventions; and (2) to capture the impact of those interventions on student retention at the Open University UK. A predictive model -- the Student Probabilities Model (SPM) -- was used to predict the likelihood of a student remaining in a course at the next milestone and eventually completing it. Undergraduate students (N=630) with a low probability of completing their studies were randomly allocated into the control (n=312) and intervention groups (n=318), and contacted by the university Student Support Teams (SSTs) using a set of motivational interventions such as text, phone, and email. The results of the randomized control trial showed statistically significant better student retention outcomes for the intervention group, with the proposed intervention deemed effective in facilitating course completion. The intervention also improved the administration of student support at scale and low cost. (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: http://learning-analytics.info/journals/index.php/JLA/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01