Computer Generated Voice-Over in a Medical E-Learning Application: The Impact on Factual Learning Outcome

Stefan Minder (University of Bern, Switzerland)

Michele Notari (University of Bern, Switzerland)

Felix Schmitz (University of Bern, Switzerland)

Rainer Hofer (University of Bern, Switzerland)

Ulrich Woermann (University of Bern, Switzerland)

Abstract: The Medical Faculty of the University of Bern uses voice-over in picture driven e-learning modules to avoid split attention induced by the modality effect. To lower production costs, professional narrators have been replaced by computer-generated voices. The e-learning modules are produced with a content management system (CMS) offering text-to-speech functionality. 107 Swiss high school students passed a 20-minute e-learning sequence on cystic fibrosis. In a nested between-group design with four learning content presentation modalities (written text vs. human voice-over vs. artificial voice-over plus 15"-laptop-screens vs. 2,8"smart-phone screens), the learning outcome was assessed at three points in time: before, just after, and six weeks after the learning phase. All modalities led to significant short-term and long-term increase in factual knowledge about cystic fibrosis. Our two hypotheses are supported: (1) presenting pictures with both human and artificial voice-over leads to the same factual learning outcome, and (2) the e-learning module leads to the same learning outcome and acceptance independent of devices and their screen sizes. Furthermore, the image-voice-over modality on mobile devices (small screens) turned out to be a setting with no significant difference in effectiveness.

Keywords: TTS, e-learning, modality effect, split attention, text-to-speech

Categories: H.5.1, H.5.2, H.5.4, K.3.1