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Adaptive Feedback from Artificial Neural Networks Facilitates Pre-Service Teachers’ Diagnostic Reasoning in Simulation-based Learning

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cam.depositDate2022-04-11
cam.issuedOnline2022-04-12
cam.orpheus.success2022-04-11 - Embargo set during processing via Fast-track
dc.contributor.authorSailer, Michael
dc.contributor.authorBauer, Elisabeth
dc.contributor.authorHofmann, Riikka
dc.contributor.authorKiesewetter, Jan
dc.contributor.authorGlas, Julia
dc.contributor.authorGurevych, Irina
dc.contributor.authorFischer, Frank
dc.date.accessioned2022-04-11T23:30:47Z
dc.date.available2022-04-11T23:30:47Z
dc.date.updated2022-04-11T07:48:24Z
dc.description.abstractIn simulations, pre-service teachers need sophisticated feedback to develop complex skills such as diagnostic reasoning. In an experimental study with N = 178 pre-service teachers about simulated pupils with learning difficulties, we investigated the effects of automatic adaptive feedback, which is based on artificial neural networks, on pre-service teachers’ diagnostic reasoning. Diagnostic reasoning was operationalised as diagnostic accuracy and the quality of justifications. We compared automatic adaptive feedback with static feedback, which we provided in form of an expert solution. Further, we experimentally manipulated whether the learners worked individually or in dyads on the computer lab-based simulations. Results show that adaptive feedback facilitates pre-service teachers’ quality of justifications in written assignments, but not their diagnostic accuracy. Further, static feedback even had detrimental effects on the learning process in dyads. Automatic adaptive feedback in simulations offers scalable, elaborate, process-oriented feedback in real-time to high numbers of students in higher education.
dc.description.sponsorshipThis research was supported by a grant of the German Federal Ministry of Research and Education (Grant No.: 16DHL1040) and by the Elite Network of Bavaria (K-GS-2012-209).
dc.identifier.doi10.17863/CAM.83431
dc.identifier.issn0959-4752
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/335999
dc.language.isoeng
dc.publisherElsevier
dc.publisher.departmentFaculty of Education
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleAdaptive Feedback from Artificial Neural Networks Facilitates Pre-Service Teachers’ Diagnostic Reasoning in Simulation-based Learning
dc.typeArticle
dcterms.dateAccepted2022-04-01
prism.publicationNameLearning and Instruction
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
pubs.licence-identifierapollo-deposit-licence-2-1
rioxxterms.typeJournal Article/Review
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1016/j.learninstruc.2022.101620

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