Time: 02:00 PM
Thesis Title: Professional Learning Analytics for Researchers: theory, practice and human-centred design
PhD candidate: Yuveena Gopalan
Building a successful and sustained career in academia, like most professions, requires a complex mix of formal and informal professional learning. However, institutional support for academic development tends to focus on teaching and learning, and on the training of PhD students, with very little understanding of the needs of Early- and Mid-Career Researchers (ECRs/MCRs). Moreover, institutional strategies tend to inform key developmental focus areas and therefore the types of training activities available for career and skills development. These identified formal training programs however do not convey how learning should occur or translate into day-to-day work activities and situations. This creates a discord with institutions in providing relevant support to academic researcher according to their work demands and developmental needs. Consequently, studies in understanding academics’ perspectives on career growth and development have started to emerge recently. Furthermore, the research data landscape is shifting, with analytics offering new proxies for researcher impact, while personal analytics tools present opportunities to use data and visualisations for career development. These data, tools and systems could empower individual researchers in using data to understand and evidence their own progress, and plan for the future. The objective is therefore to understand how high performing researchers have, in their own terms, navigated their careers, and use these insights to investigate potential data visualisations to provoke productive reflection on the part of PhDs/ECRs/MCRs.
Yuveena Gopalan is a PhD student at the Connected Intelligence Centre, UTS and is a Research Data Insights Analyst with UTS’s Research Office. In her current role within the Research Office, she has been exploring institutional research data in developing tools towards demonstrating institutional research capabilities and sector based funding opportunities for UTS. She has worked on education based data science projects with NSW government Data Analytics Centre and with CSIRO on predicting water pipeline asset failure. Her research is focussed on tackling the challenge of designing Researcher Professional Learning Analytics, that is, the use of data-informed tools and visualisation to support academics develop their careers.
Supervisors: Simon Buckingham Shum and David Boud