Mini Workshop Higher Education Research and Development Society of Australasia 2015

Scholars in the mist: Navigating the complex fog of data for the enhancement of learning and teaching practice (#180)

Jason M Lodge 1 , Melinda J Lewis 2 , Linda Corrin 3
  1. Melbourne Centre for the Study of Higher Education & Science of Learning Research Centre, University of Melbourne, Melbourne, Victoria, Australia
  2. Centre for Research on Computer Supported Learning and Cognition (CoCo), Faculty of Education and Social Work, The University of Sydney, Sydney, NSW, Australia
  3. Melbourne Centre for the Study of Higher Education, University of Melbourne, Melbourne, Victoria, Australia

Abstract

Recently there has been an explosion in the number of sources of data available about students and other aspects of higher education. The learning analytics community has been at the forefront in researching and discussing the use of these sources of data (e.g. Lockyer et al., 2013). Despite this, there is still much complexity to be navigated before these data can be meaningfully used in context. This workshop has several aims; firstly to explore the origins of data driven approaches to enhancement of teaching. The second aim of this workshop will be to reflect on the use of data within a broader context of learning and teaching practice with a particular emphasis on evaluation methods and scholarly reflective practice (as per Lodge & Lewis, 2012). Finally, the facilitators of this workshop will involve participants in a targeted discussion to consider the strategic and contextualised use of data for enhancing learning and teaching. Participants will be provided with concrete strategies for navigating the complex and growing fog of data available to them (see also Long & Siemens, 2011).   

This workshop will be of interest to higher education researchers, scholarly teaching academics and academic developers. Some of the workshop will be devoted to summarising the current status of data gathering, analysis, interpretation and dissemination in higher education. No previous experience with educational technology, statistics, information management or learning analytics is therefore assumed. The remainder of the workshop is designed to be interactive, with participants invited to consider and share examples from their own institutions and practice for seeding discussion.   

Relation to conference sub-theme: Navigating complexity and uncertainty    

Complexity in higher education in the 21st century is exemplified in no more obvious place than in the increasing production, integration and analysis of data about and from students. This supposed deluge of new forms of data creates novel and complex problems for institutions, academics and teaching support staff as well as significant opportunities. There has been much focus on leveraging these data sources for the purpose of enhancing retention of students (e.g. Macfadyen & Dawson, 2010) and some attention has been given to using data and analytics to enhance learning design (e.g. Lockyer et al., 2013). To date, there has been little focus on the more complex problem of enhancing teaching and learning practices beyond the level of individual learning tasks and activities or bounded by a stylised disciplinary focus. The proposed workshop builds on the experiences of the three facilitators as researchers, teachers and academic developers towards seeding a broader conversation and critique about the use of data for enhancing scholarly practice and academic labour. Our proposed mini-workshop therefore directly relates to the conference theme: Navigating complexity and uncertainty.    

  1. Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing Pedagogical Action: Aligning Learning Analytics With Learning Design. American Behavioral Scientist, 57(10), 1439–1459. doi:10.1177/0002764213479367
  2. Lodge, J. M. & Lewis, M. J. (2012). Pigeon pecks and mouse clicks: Putting the learning back into learning analytics. In M. Brown, M. Hartnett & T. Stewart (Eds.), Future challenges, sustainable futures. Proceedings ascilite Wellington 2012.
  3. Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 48(5), 31–40.
  4. Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599. doi:10.1016/j.compedu.2009.09.008