Learning Dispositions and Transferable Competencies: Pedagogy, Modelling, and Learning Analytics

RE Deakin Crick, Simon Buckingham-Shum

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

67 Citations (Scopus)

Abstract

Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a combination of learners’ dispositions, values,attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically,are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, criticalthinking and collaboration skills. To date, the learning analytics research and development communities have not addressed howthese complex concepts can be modelled and analysed. We report progress in the design and implementation of learning analyticsbased on an empirically validated multidimensional construct termed “learning power”. We describe a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research anddevelopment programme.
Translated title of the contributionLearning Dispositions and Transferable Competencies: Pedagogy, Modelling, and Learning Analytics
Original languageEnglish
Title of host publicationProc. 2nd International Conference on Learning Analytics & Knowledge
Place of PublicationVancouver BC
PublisherAssociation for Computing Machinery (ACM)
Publication statusPublished - 2 May 2012

Bibliographical note

Name and Venue of Event: Vancouver, BC, Canada
Conference Organiser: Learning Analytics and Knowledge

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