ABSTRACT
This workshop aims to promote strategic planning for learning analytics in higher education through developing institutional policies. While adoption of learning analytics is predominantly seen in small-scale and bottom-up patterns, it is believed that a systemic implementation can bring the widest impact to the education system and lasting benefits to learners. However, the success of it highly depends on the adopted strategy that meets the needs of various stakeholders and systematically pushes the institution towards achieving its targets. It is imperative to develop a learning analytics policy that ensures a practice that is valid, effective and ethical.
The workshop involves two components. The first component includes a set of presentations about the state of learning analytics in higher education, drawing on results from an Australian and a European project examining institutional learning analytics policy and adoption processes. The second component is an interactive session where participants are encouraged to share their motivations for adopting learning analytics and the diversity of challenges they perceive impede analytics adoption in their institution. Using the RAPID Outcome Mapping Approach (ROMA), participants will create a draft policy that articulates how the various challenges can be addressed. This workshop aims to further develop our understanding of how learning analytics operates in an organizational system and promote a cultural change in how such analytics are adopted in higher education.
- Colvin, C., Rogers, T., Wade, A., Dawson, S., Gasevic, D., Shum, S.B., Nelson, K., Alexander, S., Lockyer, L., Kennedy, G., Corrin, L. and Fisher, J. 2015. Student retention and learning analytics: a snapshot of Australian practices and a framework for advancement. The Australian Government Office for Learning and Teaching.Google Scholar
- Ferguson, R., Macfadyen, L.P., Clow, D., Tynan, B., Alexander, S. and Dawson, S. 2014. Setting Learning Analytics in Context: Overcoming the Barriers to Large- Scale Adoption. Journal of Learning Analytics. 1, 3 (Sep. 2014), 120--144.Google ScholarCross Ref
- Gašević, D., Dawson, S., Rogers, T. and Gasevic, D. 2016. Learning analytics should not promote one size fits all: the effects of instructional conditions in predicting academic success. The Internet and Higher Education. 28, (2016), 68--84.Google ScholarCross Ref
- Macfadyen, L.P., Dawson, S., Pardo, A. and Gaševic, D. 2014. Embracing Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge. Research & Practice in Assessment. 9, (2014), 17--28.Google Scholar
- Newland, B., Martin, L. and Ringan, N. 2015. Learning analytics in UK HE 2015: a HeLF survey report.Google Scholar
- Siemens, G., Dawson, S. and Lynch, G. 2013. Improving the quality and productivity of the higher education sector: policy and strategy for systems-level deployment of learning analytics. Society for Learning Analytics Research for the Australian Office for Learning and Teaching.Google Scholar
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Index Terms
- LA policy: developing an institutional policy for learning analytics using the RAPID outcome mapping approach
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