Affordances of Learning Analytics for Mediating Learning

Learning analytics acceptance and adoption is a socio-technological endeavour. Understanding how learning analytics impact practice is an important part of demonstrating their value. In the study presented in this thesis, "Mediated Learning" provides a framework through which to describe how learning analytics can impact psychological, social and material aspects of learning, from the perspective of educators and learners. It also offers a structure through which to make recommendations for improving the mediatory effects of learning analytics. A qualitative research design, based on "Grounded Theory" was implemented and 10 educators from 3 European universities were recruited through convenience and purposive sampling for exploratory interviews. A subsequent case study of the Open University provided critical perspectives from both educators (n=18) and learners (n=22) about the institutional, departmental, domain-related and epistemological factors that broadly influence perceptions of learning analytics. The study applied "Affordance Theory" to identify what participants were most easily able to recognise as beneficial to their own practice. Participant contributions were open-coded to uncover emerging themes and then organised into thematic categories and subcategories. Respondent validation, as well as triangulation of data between the exploratory interviews and focus groups support the validity of the study. Findings suggested that domain-related epistemological assumptions and previous experience influence how and why an individual could make use of learning analytics insights. Gaining stakeholder acceptance involves targeting the right training and opportunities at the appropriate disciplines. Findings also indicate that learning analytics has the strongest mediatory effect for learners when the technology is capable of exposing them to other learners' strategies, or when it assists them personally, and continually in goal orientation adoption. The implications of the study are important for higher education institutions looking to implement large-scale learning analytics initiatives, in particular, those with a diverse student body.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

The Open University

Year dc:date.issued

2018

Author dc:creator

• Farrell, Tracie

Language dc:language

en