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dc.contributor.authorKohnle, Antje
dc.contributor.authorPassante, Gina
dc.date.accessioned2017-11-27T12:30:12Z
dc.date.available2017-11-27T12:30:12Z
dc.date.issued2017-11-28
dc.identifier.citationKohnle , A & Passante , G 2017 , ' Characterizing representational learning : a combined simulation and tutorial on perturbation theory ' , Physical Review Physics Education Research , vol. 13 , no. 2 , 020131 . https://doi.org/10.1103/PhysRevPhysEducRes.13.020131en
dc.identifier.issn2469-9896
dc.identifier.otherPURE: 251624878
dc.identifier.otherPURE UUID: 820fa44e-2cc8-4e8b-b257-6af20f8c1823
dc.identifier.otherScopus: 85038563427
dc.identifier.otherORCID: /0000-0003-2638-4826/work/39487823
dc.identifier.otherWOS: 000416318700001
dc.identifier.urihttps://hdl.handle.net/10023/12177
dc.descriptionWe thank the University of St. Andrews for funding the development of simulations.en
dc.description.abstractAnalyzing, constructing and translating between graphical, pictorial and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence'') is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid- and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic and semantic use of representations.
dc.format.extent13
dc.language.isoeng
dc.relation.ispartofPhysical Review Physics Education Researchen
dc.rights© 2017 The Author(s). Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.en
dc.subjectLB Theory and practice of educationen
dc.subjectQC Physicsen
dc.subjectNDASen
dc.subject.lccLBen
dc.subject.lccQCen
dc.titleCharacterizing representational learning : a combined simulation and tutorial on perturbation theoryen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Physics and Astronomyen
dc.contributor.institutionUniversity of St Andrews. Centre for Higher Education Researchen
dc.identifier.doihttps://doi.org/10.1103/PhysRevPhysEducRes.13.020131
dc.description.statusPeer revieweden


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