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

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 To lower production costs, professional narrators have been replaced by computer-generated voices.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.2,8smart-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.