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Quality metrics and indicators for analytics of assessment design at scale

Ringtved, Ulla; Milligan, Sandra; Corrin, Linda; Littlejohn, Allison and Law, Nancy (2017). Quality metrics and indicators for analytics of assessment design at scale. In: LAK 17, 13-17 Mar 2017, Simon Fraser University, Vancouver, Canada.

URL: http://educ-lak17.educ.sfu.ca/index.php/pre-confer...
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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
Academic Unit/School: Learning and Teaching Innovation (LTI) > Institute of Educational Technology (IET)
Learning and Teaching Innovation (LTI)
Research Group: Health and Wellbeing PRA (Priority Research Area)
Item ID: 53529
Depositing User: Allison Littlejohn
Date Deposited: 23 Feb 2018 11:38
Last Modified: 07 Dec 2018 11:02
URI: http://oro.open.ac.uk/id/eprint/53529
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