Using virtual reality for dynamic learning: an extended technology acceptance model.

Area of Science:

• Educational Technology
• Human-Computer Interaction
• Learning Sciences

Background:

• Virtual Reality (VR) is increasingly integrated into educational curricula and training programs.
• Research on VR's learning affordances is growing, yet student perceptions and intentions to use VR for training remain underexplored.
• Understanding these factors is crucial for effective VR adoption in education.

Purpose of the Study:

• To identify factors influencing students' intention to use Virtual Reality (VR) in dynamic learning environments.
• To extend the Technology Acceptance Model (TAM) with VR-specific and educational factors.
• To provide guidance for educators implementing VR in training.

Main Methods:

• Development of an extended Technology Acceptance Model (TAM) incorporating educational and VR-specific factors.
• Application of Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM).
• Testing 14 hypotheses to determine the impact on behavioral intention (BI).

Main Results:

• Nine out of 14 hypotheses were supported.
• Eight predictor factors significantly influenced behavioral intention (BI), directly or indirectly.
• Original TAM factors demonstrated the strongest relationships, with VR-specific and learning factors also showing significant support.

Conclusions:

• The extended TAM effectively explains students' intention to use VR in educational settings.
• Educators can leverage these findings to facilitate the successful integration of VR technology.
• Further research can build upon this model to optimize VR learning experiences.