Titel:	Analyzing Self-Explanations in Mathematics: Gestures and Written Notes Do Matter
Autor(en):	Salle, Alexander
ORCID des Autors:	https://orcid.org/0000-0002-2845-6945
Zusammenfassung:	When learners self-explain, they try to make sense of new information. Although research has shown that bodily actions and written notes are an important part of learning, previous analyses of self-explanations rarely take into account written and non-verbal data produced spontaneously. In this paper, the extent to which interpretations of self-explanations are influenced by the systematic consideration of such data is investigated. The video recordings of 33 undergraduate students, who learned with worked-out examples dealing with complex numbers, were categorized successively including three different data bases: (a) verbal data, (b) verbal and written data, and (c) verbal, written and non-verbal data. Results reveal that including written data (notes) and non-verbal data (gestures and actions) leads to a more accurate analysis of self-explanations than an analysis solely based on verbal data. This influence is even stronger for the categorization of self-explanations as adequate or inadequate.
Bibliografische Angaben:	Salle A (2020) Analyzing Self-Explanations in Mathematics: Gestures and Written Notes Do Matter. Front. Psychol. 11:513758.
URL:	https://osnadocs.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-202105114505
Schlagworte:	self-explanation; gesture; multimodality; trigonometry; complex numbers
Erscheinungsdatum:	23-Nov-2020
Lizenzbezeichnung:	Attribution 4.0 International
URL der Lizenz:	http://creativecommons.org/licenses/by/4.0/
Publikationstyp:	Einzelbeitrag in einer wissenschaftlichen Zeitschrift [article]
Enthalten in den Sammlungen:	FB06 - Hochschulschriften Open-Access-Publikationsfonds

Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons