Schwaninger, Adrian

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Adrian
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Schwaninger, Adrian

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  • Vorschaubild
    Publikation
    Video demonstrations can predict the intention to use digital learning technologies
    (Wiley, 21.01.2023) Sprenger, David; Schwaninger, Adrian [in: British Journal of Educational Technology]
    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.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    How realistic is threat image projection for X-ray baggage screening?
    (MDPI, 13.03.2022) Riz à Porta, Robin; Sterchi, Yanik; Schwaninger, Adrian [in: Sensors]
    At airports, security officers (screeners) inspect X-ray images of passenger baggage in order to prevent threat items (bombs, guns, knives, etc.) from being brought onto an aircraft. Because threat items rarely occur, many airports use a threat-image-projection (TIP) system, which projects pre-recorded X-ray images of threat items onto some of the X-ray baggage images in order to improve the threat detection of screeners. TIP is regulatorily mandated in many countries and is also used to identify officers with insufficient threat-detection performance. However, TIP images sometimes look unrealistic because of artifacts and unrealistic scenarios, which could reduce the efficacy of TIP. Screeners rated a representative sample of TIP images regarding artifacts identified in a pre-study. We also evaluated whether specific image characteristics affect the occurrence rate of artifacts. 24% of the TIP images were rated to display artifacts and 26% to depict unrealistic scenarios, with 34% showing at least one of the two. With two-thirds of the TIP images having been perceived as realistic, we argue that TIP still serves its purpose, but artifacts and unrealistic scenarios should be reduced. Recommendations on how to improve the efficacy of TIP by considering image characteristics are provided.
    01A - Beitrag in wissenschaftlicher Zeitschrift