Learner enhanced technology Can activity analytics support understanding engagement a measurable process?

• Published in: Journal of applied research in higher education Vol. 8; no. 1; pp. 18 - 43
• Main Authors: Ballard, James, Butler, Philip Ian
• Format: Journal Article
• Language: English
• Published: 01.02.2016
• ISSN: 2050-7003
• DOI: 10.1108/JARHE-09-2014-0074

Purpose – The purpose of this paper is to propose a conceptual model of engagement, appropriated from social media marketing, as a sense-making framework to understand engagement as a measurable process through the development of engagement profiles. To explore its potential application to education the paper follows previous work with Personalised Learning strategies to place emphasis on the promotion of the learner voice – their ability to influence decisions affecting them and their community. Design/methodology/approach – This paper will position engagement as a sociocultural process and adopt an Activity Theory based methodology demonstrated through a desk analysis of VLE data from a further education college. Findings – The analysis suggests that the approach can yield insights that may be elusive in traditional measures reinforcing the overall conceptual proposal for a multi-method approach to profiling learner engagement. Research limitations/implications – The paper has focused on presentation and exploration of the conceptual approach, which has limited the scope to broaden the discussion of the desk analysis and wider findings that this approach reveals. Practical implications – It is intended that the approach offers a generalizable model that can be adopted by institutions planning to measure engagement or develop learner activity profiles. Several areas of immediate potential are identified throughout the paper. Originality/value – This paper contributes a multi-method approach to engagement as argued for in recent engagement literature. This should offer institutions a way to realise value from emerging ideas within related domains of Learning Design and Learning Analytics.