Identifying Engagement Patterns with Video Annotation Activities: A Case Study in Professional Development

Autor/inn/en	Mirriahi, Negin; Jovanovic, Jelena; Dawson, Shane; Gaševic, Dragan; Pardo, Abelardo
Titel	Identifying Engagement Patterns with Video Annotation Activities: A Case Study in Professional Development
Quelle	In: Australasian Journal of Educational Technology, 34 (2018) 1, S.57-72 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1449-5554
Schlagwörter	Video Technology; Case Studies; Online Courses; Higher Education; Faculty Development; College Faculty; Teaching Methods; Blended Learning; Learning Processes; Markov Processes; Research Universities; Foreign Countries; Learning Experience; Learner Engagement; Metacognition; Learning Strategies; Statistical Analysis; Australia + Suchen Sie Ihr Suchwort? Case study; Fallstudie; Case Study; Online course; Online-Kurs; Hochschulbildung; Hochschulsystem; Hochschulwesen; Fakultät; Teaching method; Lehrmethode; Unterrichtsmethode; Learning process; Lernprozess; Markowscher Prozess; Forschungseinrichtung; Ausland; Lernerfahrung; Meta cognitive ability; Meta-cognition; Metakognitive Fähigkeit; Metakognition; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Statistische Analyse; Australien
Abstract	The rapid growth of blended and online learning models in higher education has resulted in a parallel increase in the use of audio-visual resources among students and teachers. Despite the heavy adoption of video resources, there have been few studies investigating their effect on learning processes and even less so in the context of academic development. This paper uses learning analytic techniques to examine how academic teaching staff engage with a set of prescribed videos and video annotations in a professional development course. The data was collected from two offerings of the course at a large research-intensive university in Australia. The data was used to identify patterns of activity and transition states as users engaged with the course videos and video annotations. Latent class analysis and hidden Markov models were used to characterise the evolution of engagement throughout the course. The results provide a detailed description of the evolution of learner engagement that can be readily translated into action aimed at increasing the quality of the learning experience. (As Provided).
Anmerkungen	Australasian Society for Computers in Learning in Tertiary Education. Ascilite Secretariat, P.O. Box 44, Figtree, NSW, Australia. Tel: +61-8-9367-1133; e-mail: info@ascilite.org.au; Web site: https://ajet.org.au/index.php/AJET
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01