Using Learning Analytics to Scale the Provision of Personalised Feedback

Autor/inn/en	Pardo, Abelardo; Jovanovic, Jelena; Dawson, Shane; Gaševic, Dragan; Mirriahi, Negin
Titel	Using Learning Analytics to Scale the Provision of Personalised Feedback
Quelle	In: British Journal of Educational Technology, 50 (2019) 1, S.128-138 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Pardo, Abelardo)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.12592
Schlagwörter	Learning; Data Analysis; Feedback (Response); Technology Uses in Education; College Freshmen; Undergraduate Students; Engineering Education; Blended Learning; Individualized Instruction; Student Attitudes; Academic Achievement + Suchen Sie Ihr Suchwort? Lernen; Auswertung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Studienanfänger; Ingenieurausbildung; Individualisierender Unterricht; Schülerverhalten; Schulleistung
Abstract	There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this impediment. As students interact with the various learning technologies in their course of study, they create digital traces that can be captured and analysed. These digital traces form the new kind of data that are frequently used in learning analytics to develop actionable recommendations that can support student learning. This paper explores the use of such analytics to address the challenges impeding the capacity of instructors to provide personalised feedback at scale. The case study reported in the paper showed how the approach was associated with a positive impact on student perception of feedback quality and on academic achievement. The study was conducted with first year undergraduate engineering students enrolled in a computer systems course with a blended learning design across three consecutive years (N[subscript 2013] = 290, N[subscript 2014] = 316 and N[subscript 2015] = 415). (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01