Quality Metrics and Indicators for Analytics of Assessment Design at Scale

Ringtved, U., Milligan, S., Corrin, L., Littlejohn, A. and Law, N. (2017) Quality Metrics and Indicators for Analytics of Assessment Design at Scale. 7th International Conference on Learning Analytics and Knowledge (LAK 17), Vancouver, BC, Canada, 13-17 Mar 2017.

Abstract

Notions of what constitutes quality in learning and assessment design in traditional on-campus or online teaching-learning settings may not translate well in scaled digital environments. This workshop, DesignLAK17, provides the opportunity to explore the issues and opportunities arising from the use of analytics in scaled assessment design. There are opportunities for new paradigms of learning design to exploit the distinctive characteristics and potentials of analytics, trace data and newer kinds of sensory data available on digital platforms, and to transform assessment in the process. However, notions of what is and is not good quality assessment design need to be reconsidered, and new metrics for capturing quality are required to unleash these anticipated potentials of data analytics. This symposium and workshop will focus on what might be appropriate quality metrics and indicators for analytics-based assessment design in scaled learning. It aims to build a community of interest around the topic, to share perspectives, and to generate design and research ideas.

• Item Type: Conference or Workshop Item
• Keywords: Massive open online course, MOOC, quality, higher education, online learning, technology-enhanced learning.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Littlejohn, Professor Allison
• Authors: Ringtved, U., Milligan, S., Corrin, L., Littlejohn, A., and Law, N.
• College/School: College of Social Sciences > School of Education