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Eine Analyse von Interaktionsmustern für mobiles forschendes Lernen

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Handbuch Mobile Learning

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Zusammenfassung

In den letzten zehn Jahren wurde mobile Technologie mehr und mehr zu einer Standardkomponente im Methodenkatalog des forschenden Lernens. Nichtsdestotrotz wurden oft der pädagogische Mehrwert und der sinnvolle Einsatz hinterfragt. In diesem Beitrag haben die Autoren 62 Systeme zur Unterstützung von mobilem forschendem Lernen sowie die Nutzung von mobiler Technologie im Lerndesign und deren potenziellen Mehrwert analysiert. Als besondere Alleinstellungsmerkmale, die den Einsatz von mobiler Technologie rechtfertigen, können Funktionen der individuellen und kollaborativen Datensammlung, der Einsatz von Echtzeitkommunikation sowie die Verbindung von simulierten oder echten Lernsituationen mittels erweiterter Realität hervorgehoben werden. Hierzu präsentieren die Autoren ein Klassifikationsschema für die Entwicklung von dozenteninitiierten, lernerinitiierten und kontextinitiierten Lernszenarien für mobiles forschendes Lernen.

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  1. Heerlen, Niederlande

    Marcus Specht & Angel Suarez

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  1. Marcus Specht
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    Claudia de Witt

  2. Hagen, Germany

    Christina Gloerfeld

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Specht, M., Suarez, A. (2018). Eine Analyse von Interaktionsmustern für mobiles forschendes Lernen. In: de Witt, C., Gloerfeld, C. (eds) Handbuch Mobile Learning. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-19123-8_18

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