Designing a SVVR Educational Game to Cultivate Environmental Behavior Decision-Making Skills: A Case Study on Tropical Rainforest and Indigenous Issues

Abstract

Cultivating learners' environmental behavior decision-making skills is important for environmentally sustainable development. General lecture or discussion teaching methods lack realistic scenarios and interactivity in the experience design of environmental behavior decision-making. It is difficult to stimulate learners' motivation and enhance problem-solving abilities, leading to poor transfer of learning. To solve the above problems, this study designed an educational game with a realistic story context. The game employs game-based learning to promote learning motivation, combines Spherical Video-based Virtual Reality (SVVR) to provide realistic environments, and uses Google Forms to enhance interactivity to understand learners’ environmental behavior decisions. In this game, learners can talk to non-learner characters (NPCs) in a complex tropical rainforest SVVR and engage in visual and auditory exploration to learn ecological knowledge and understand indigenous culture and challenges. Google Forms were used to solve puzzles and collect information about their personal environmental behavior decisions. An empirical evaluation involving 20 Taiwanese high school students revealed high levels of flow for the game. This indicated that the game could promote learning engagement. After playing the game, learners’ academic achievement significantly improved, demonstrating the enhancement of knowledge acquisition. The results of the environmental behavior decision-making and environmental awareness assessments showed that the game effectively combines cognition and action. The learners were highly interested in exploring the rainforest and had negative feelings about the indigenous people's loss of homes. These results indicate that the game's realistic and interactive design can promote deeper understanding and experience and facilitate effective environmental behavior decision-making.

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Author Information
Kang-Miao Cheng, National Taiwan University of Science and Technology, Taiwan
Huei-Tse Hou, National Taiwan University of Science and Technology, Taiwan