Presentation 1: 2:20pm – 2:50pm
Author: Sarah Alcock
Title:
Data driven reflection in professional learning: Using Learning Analytics Dashboards in learning design to engage final year student chartered accountants and their tutors in assessment Learning Analytics.
Abstract:
Maximising affordance of the trace data produced by learners and educators operating online continues to be a crucial objective in educational technology research. To achieve this goal, Learning Analytics research has begun to move from the data led, technological question of ‘how’ to represent past online learning behaviour, to the human led, pragmatic question of ‘why’ data is useful, and ‘what’ next step choices learners have. This doctoral thesis contributes to this paradigm shift by seeking to understand the implications of providing explanatory (telling a story, rather than simply giving data) and action-based (what next?) data visualisations and feedback on assessment, integrated into course design and presented via a Learning Analytics Dashboard (LAD) to chartered accountancy students and their tutors. It moves LAD research out of the conventional context of schools and higher education institutions (HEI) into a commercial, professional learning organisation, answering calls for research in new and authentic settings. In addition, this research addresses the need for LAD investigations to be grounded in learning science by framing data collection, analysis and discussion in Self Regulated Learning (SRL), a prevalent learning theory in Learning Analytics research. The study will use mixed methods, melding quantitative and qualitative methodologies throughout the data collection phase. Surveys, observations and interviews will be combined with repeated assessment scores to understand the extent to which the LAD is an effective tool for improving learning, as well as learner experience. A pilot study is underway, currently in early data collection phase, and this presentation will discuss methodology, initial data analysis and research aims.
Presentation 2: 2:50pm – 3:20pm
Author: Helen Darlaston
Title: How can mature female learners, who are health care professionals with additional responsibilities working with the National Health Service in England, increase self-efficacy to confidently engage with online continuing professional development via CLEAR education?
Abstract:
Heath care professionals (HCPs) who are mature female learners (MFLs), and other learners with additional caring responsibilities (such as those caring for elderly or ill parents), working within the National Health Service (NHS) in England may struggle to fit continuous professional development (CPD) learning into their already busy lives and as a result, have negative learning experiences. Online learning for CPD can benefit this group of learners as it is flexible and increases accessibility to learning.
Previous studies have shown that MFL and other learners with additional responsibilities value online learning for flexibility and accessibility, particularly within the Higher Education context. However, very view studies focus on how HCPs manage their CPD learning online or fit learning into their busy lives. Within the context of the NHS in England, this is a major issue, given that protected CPD study time is being eroded by clinical pressures due to the pandemic, but there is still need to undertake CPD in the most effective way.
Findings from a literature review focusing on online learning in NHS showed that HCPs struggle to dedicate time to learn, that increased accessibility may come at a cost for the learner and the learning provider, and that self-efficacy around online learning skills and systems is low. Further review identified areas that can contribute to improving the online learning experiences of learners with additional responsibilities in CPD. Exploring how HCPs fit learning into their lives can inform NHS-related CPD programmes as to what learning design would be most effective in a post-pandemic world and feeds into existing knowledge of online learning in other sectors.