Search

Virtual Reality (VR) has demonstrated significant advantages in various educational fields as it allows learners to actively learn in high interactivity and realism under their learning pace. However, for low-achieving students, VR learning environments may introduce some challenges, which are problems encountered during their learning process, which lead to difficulties in self-regulating their learning progress and becoming disoriented in the lack of guidance. This study aims to explore the improvement of self-regulated VR learning environment based on the Cognitive Theory of Multimedia Learning and enhance the performance of low-achieving students. We designed a VR course on electronic circuit hardware and programming, providing participants with a series of learning aids in the VR learning environment, including feedback, hints and guidance. Feedback aids provide correct or incorrect feedback after each task or test, guidance aids display progress following each task or test and hint aids offer guidance when inactivity is detected. A quasi-experiment was conducted by using questionnaires and practical tasks to assess the participants' cognitive levels, practical hands-on skills, self-regulated learning abilities and learning engagement after VR learning. The results demonstrated significant improvements in all learning indicators for low-achieving students.

The core purpose of integrating inquiry-based learning strategies into STEM activities is to create a challenging learning environment that stimulates students' active learning, thereby effectively enhancing their interest in learning, thinking skills, and practical application abilities. To achieve these goals, developing more technology-assisted tools and platforms to improve teaching efficiency and enrich the learning experience becomes crucial. Therefore, this research developed InquiryGPT, which guides students through the POEE inquiry process by imposing limitations, facilitating dialogue, and providing feedback, while avoiding over-reliance on ChatGPT. This promotes the cultivation of higher-order thinking skills through interactions with InquiryGPT, thereby enhancing students' knowledge construction and understanding. This study, based on the Technology Acceptance Model (TAM), examined the effectiveness of InquiryGPT. The results showed no significant difference between InquiryGPT and ChatGPT in terms of perceived usefulness and perceived ease of use. Additionally, through analysis of covariance (ANCOVA), the study further analyzed the impact of InquiryGPT on students' higher-order thinking skills and learning scores, proving that it significantly enhances students' creativity, problem-solving abilities, critical thinking, and knowledge construction.