Formative assessment and learning analytics

D.T. Tempelaar, A.J.P. Heck, H. Cuypers, H. Kooij, van der, E.M. Vrie, van de

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

38 Citations (Scopus)

Abstract

Learning analytics seeks to enhance the learning process through systematic measurements of learning related data, and informing learners and teachers of the results of these measurements, so as to support the control of the learning process. Learning analytics has various sources of information, two main types being intentional and learner activity related metadata [1]. This contribution aims to provide a practical application of Shum and Crick's theoretical framework [1] of a learning analytics infrastructure that combines learning dispositions data with data extracted from computer-based, formative assessments. The latter data component is derived from one of the educational projects of ONBETWIST, part of the SURF program 'Testing and Test Driven Learning'.
Original languageEnglish
Title of host publicationProceedings of the Third International Conference on Learning Analytics and Knowledge (LAK'13, Leuven, Belgium, April 8-12, 2013)
Place of PublicationNew York NY
PublisherAssociation for Computing Machinery, Inc
Pages205-209
ISBN (Print)978-1-4503-1785-6
DOIs
Publication statusPublished - 2013
Eventconference; Third International Conference on Learning Analytics and Knowledge; 2013-04-08; 2013-04-12 -
Duration: 8 Apr 201312 Apr 2013

Conference

Conferenceconference; Third International Conference on Learning Analytics and Knowledge; 2013-04-08; 2013-04-12
Period8/04/1312/04/13
OtherThird International Conference on Learning Analytics and Knowledge

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    Tempelaar, D. T., Heck, A. J. P., Cuypers, H., Kooij, van der, H., & Vrie, van de, E. M. (2013). Formative assessment and learning analytics. In Proceedings of the Third International Conference on Learning Analytics and Knowledge (LAK'13, Leuven, Belgium, April 8-12, 2013) (pp. 205-209). Association for Computing Machinery, Inc. https://doi.org/10.1145/2460296.2460337