Immersive Learning Predicted: Presence, Prior Knowledge, and School Performance Influence Learning Outcomes in Immersive Educational Virtual Environments

Abstract

Media Learning is an internal process nested within a complex combination of learner-specific and external factors. The Educational Framework for Immersive Learning hypothesizes learners’ presence, motivational traits, emotional states, cognitive capabilities, and previous knowledge as predictors of learning outcomes in immersive educational virtual environments. This article proposes a research model for investigating relations between these variables that seem to be crucial for explaining Immersive Learning processes. Three Virtual Realities for learning three topics of Computer Science Education (components of a computer, asymmetric cryptography, and finite state machines), each provided on three distinct levels of technological immersion, were used to carry out a study with 78 participants. Path analysis was used to test the hypotheses deriving from the research model, showing that presence, prior knowledge about the content, and school performance influence learning outcomes. Presence was predicted by the users’ academic emotional states prior to the study and the provided level of immersion. The emotional states were influenced by the students’ school performance. Prior knowledge and school performance of the students were affected by the motivational variables. This study contributes to existing research as it adds factors that are crucial for learning processes to the discussion on Immersive Learning.