Schwaninger, Adrian
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3D imaging for hold baggage screening: The relevance of rotation and slicing functions
Belastungen und Ressourcen und ihre Auswirkungen auf Beanspruchung, Wohlbefinden und Kündigungsabsicht - Eine Studie mit Flughafensicherheitsbeauftragten
Video demonstrations can predict the intention to use digital learning technologies
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.