Foundations of dynamic learning analytics: Using university student data to increase retention


de Freitas, Sara , Gibson, David , Du Plessis, Coert , Halloran, Pat , Ambrose, Matt , Dunwell, I. and Arnab, S. (2014) Foundations of dynamic learning analytics: Using university student data to increase retention. British Journal of Educational Technology, volume 46 (6): 1175-1188


Full Text

Official URLTEST PDF Post-Print.pdf (702.4KB)


Abstract

With digitisation and the rise of e-learning have come a range of computational tools and approaches that have allowed educators to better support the learners' experience in schools, colleges and universities. The move away from traditional paper-based course materials, registration, admissions and support services to the mobile, always-on and always accessible data has driven demand for information and generated new forms of data observable through consumption behaviours. These changes have led to a plethora of data sets that store learning content and track user behaviours. Most recently, new data analytics approaches are creating new ways of understanding trends and behaviours in students that can be used to improve learning design, strengthen student retention, provide early warning signals concerning individual students and help to personalise the learner's experience. This paper proposes a foundational learning analytics model (LAM) for higher education that focuses on the dynamic interaction of stakeholders with their data supported by visual analytics, such as self-organising maps, to generate conversations, shared inquiry and solution-seeking. The model can be applied for other educational institutions interested in using learning analytics processes to support personalised learning and support services. Further work is testing its efficacy in increasing student retention rates.



Details

Item TypeArticle
TitleFoundations of dynamic learning analytics: Using university student data to increase retention
Authorsde Freitas, Sara
Gibson, David
Du Plessis, Coert
Halloran, Pat
Ambrose, Matt
Dunwell, I. (profile-link for )
Arnab, S. (profile-link for ) http://orcid.org/0000-0002-4939-7382
Departments Engineering and Computing/SGI - Serious Games Institute
Identifiers
ISSN0007-1013, ESSN: 1467-8535
DOI10.1111/bjet.12212
Publisher statementThis is the peer reviewed version of the following article: de Freitas, S., Gibson, D., Du Plessis, C., Halloran, P., Ambrose, M., Dunwell, I. and Arnab, S. (2015) Foundations of dynamic learning analytics: Using university student data to increase retention. British Journal of Educational Technology, volume 46 (6): 1175-1188, which has been published in final form at http://dx.doi.org/10.1111/bjet.12212. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for self-archiving.
Sharelink
Deposited on 03-Feb-2015 in Research - Coventry.
Last modified on 07-Dec-2016

Details


Actions