Video demonstrations can predict the intention to use digital learning technologies
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
21.01.2023
Typ der Arbeit
Studiengang
Typ
01A - Beitrag in wissenschaftlicher Zeitschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
British Journal of Educational Technology
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
Patentnummer
Verlag / Herausgebende Institution
Wiley
Verlagsort / Veranstaltungsort
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
The technology acceptance model (TAM) uses perceived usefulness and perceived ease of use to predict the intention to use a technology which is important when deciding to invest in a technology. Its extension for e-learning (the general extended tech-nology acceptance model for e-learning; GETAMEL) adds subjective norm to predict the intention to use. Technology acceptance is typically measured after the technology has been used for at least three months. This study aims to identify whether a minimal amount of exposure to the technology using video demonstrations is sufficient to predict the intention to use it three months later. In two studies—one using TAM and one using GETAMEL—we showed students of different cohorts (94 and 111 participants, respectively) video demonstra-tions of four digital technologies (classroom response system, classroom chat, e-lectures, mobile virtual real-ity). We then measured technology acceptance imme-diately after the demonstration and after three months of technology use. Using partial least squares model-ling, we found that perceived usefulness significantly predicted the intention to use three months later. In GETAMEL, perceived usefulness significantly predicted the intention to use for three of the four learning technol-ogies, while subjective norm only predicted the inten-tion to use for mobile virtual reality. We conclude that video demonstrations can provide valuable insight for decision-makers and educators on whether students will use a technology before investing in it.
Schlagwörter
digital learning technologies, e-learning, perceived usefulnes, virtual reality
Fachgebiet (DDC)
003 - Systeme
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
0007-1013
1467-8535
1467-8535
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Hybrid
Lizenz
Zitation
SPRENGER, David und Adrian SCHWANINGER, 2023. Video demonstrations can predict the intention to use digital learning technologies. British Journal of Educational Technology. 21 Januar 2023. DOI 10.1111/bjet.13298. Verfügbar unter: https://doi.org/10.26041/fhnw-4650