Learning analytics involves the measurement, collection, analysis and reporting of ‘big data’ related to learners and their contexts, with the intention of providing actionable intelligence that supports teaching and learning. At The Open University, there is increased recognition that “smart-and-pedagogically-informed” learning analytics are urgently needed to solve the student-retention problem. In the medium-longer term, we envision a need to provide evidence-based research for and practice-based solutions of personalised, bespoke learning, support and feedback to our students to remain competitive in the global market of education.
Before 2018, we aim to become a world leading centre of learning analytics research, whereby state-of-the-art evidence-based research leads to advancements of the learning analytics field, transformed into successful methods, approaches and commercial products. Furthermore, we need to ensure that research is effectively translated into cost-effective transformations of the core OU business programme. By developing micro-level experiments in the Jennie Lee Research Laboratories and meso-level interventions within the core business model (e.g., Student Experience Project PVC LT) together with the two other research programmes within IET (Innovative Pedagogy, Learning in an open world), we aim to become the leading centre of excellence in learning analytics as recognised by REF 2020.
- ABC Learning Gains - HEFCE funded
- OWL - EU funded
- CODUR - EU funded
- Student Experience Project Analytics
- TESLA - EU funded
- LAEP - The implications and opportunities of learning analytics for European educational policy
Currently, the team of researchers involved in research portfolio learning analytics are:
Dr Bart Rienties (Programme director learning analytics)
Analysing 157 Learning Designs using Learning Analytic approaches as a means to evaluate the impact of pedagogical decision-making. (2016).
Toetenel, L., Rienties, B.
British Journal of Educational Technology. DOI: 10.1111/bjet.12423. Impact factor: 1.394.
Modeling and managing learner satisfaction: use of learner feedback to enhance blended and online learning experience. (2016).
Li, N., Marsh, V., & Rienties, B.
Decision Sciences Journal of Innovative Education.
Analytics4Action Evaluation Framework: a review of evidence-based learning analytics interventions at the Open University UK (2016).
Rienties, B., Boroowa, A., Cross, S., Kubiak, C., Mayles, K., & Murphy, S.
Journal of Interactive Media in Education, 1 (2) 1-13.
The pivotal role of effort beliefs in mediating implicit theories of intelligence and achievement goals & academic motivations. (2015).
Tempelaar, D. T., Rienties, B., Giesbers, B., Gijselaers, W.
Social Psychology of Education. 18, 101-120. Impact factor: 0.682.
In search for the most informative data for feedback generation: Learning Analytics in a data-rich context. (2015).
Tempelaar, D. T., Rienties, B., & Giesbers, B.
Computers in Human Behavior, 47, 157-167. Impact factor: 2.273.
Using student experience as a model for designing an automatic feedback system for short essays (2014)
Alden, Bethany; Van Labeke, Nicolas; Field, Debora; Pulman, Stephen; Richardson, John T. E. and Whitelock, Denise
International Journal of e-Assessment, 4, Article 68(1)
Social learning analytics (2012)
Buckingham Shum, Simon and Ferguson, Rebecca
Journal of Educational Technology and Society, 15(3) (pp. 3-26)
An overview of learning analytics (2013-08-19)
Teaching in Higher Education, 18(6) (pp. 683-695)
The use, role and reception of open badges as a method for formative and summative reward in two Massive Open Online Courses (2014)
Cross, Simon; Whitelock, Denise and Galley, Rebecca
International Journal of e-Assessment, 4(1)
An exploration of the features of graded student essays using domain-independent natural language processing techniques (2014)
Field, Debora; Richardson, John T. E.; Pulman, Stephen; Van Labeke, Nicolas and Whitelock, Denise
International Journal of e-Assessment, 4, Article 69(1)
Learning analytics: drivers, developments and challenges (2012)
International Journal of Technology Enhanced Learning, 4(5/6) (pp. 304-317)
Why increased social presence through web videoconferencing does not automatically lead to improved learning (2014)
Giesbers, Bas; Rienties, Bart; Tempelaar, Dirk T. and Gijselaers, Wim
E-Learning and Digital Media, 11(1) (pp. 31-45)
Using technology for teaching and learning in higher education: a critical review of the role of evidence in informing practice (2014)
Price, Linda and Kirkwood, Adrian
Higher Education Research and Development, 33(3) (pp. 549-564)
Technology-enhanced learning and teaching in higher education: what is ‘enhanced’ and how do we know? A critical literature review (2014)
Kirkwood, Adrian and Price, Linda
Learning, Media and Technology, 39(1) (pp. 6-36)
Approaches to studying across the adult life span: Evidence from distance education (2013-08)
Richardson, John T. E.
Learning and Individual Differences, 26 (pp. 74-80)
Research issues in evaluating learning pattern development in higher education (2013-03)
Richardson, John T. E.
Studies in Educational Evaluation, 39(1) (pp. 66-70)
How achievement emotions impact students' decisions for online learning, and what precedes those emotions (2012)
Tempelaar, Dirk T.; Niculescu, Alexandra; Rienties, Bart; Gijselaers, Wim H. and Giesbers, Bas
Internet and Higher Education, 15(3) (pp. 161-169)