Integrating an SVVR-based advance organizer and AI companions in ethics education: fostering critical thinking, active learning, and task–technology fit
Abstract
In university-level ethics education, moral dilemmas place significant emphasis on developing critical thinking skills. Traditionally, instructors provide a contextual advance organizer to help students connect theoretical concepts with real-world applications before engaging in peer-based critical thinking activities. Recently, researchers have begun experimenting with generative AI learning companions to simulate meaningful human–AI collaboration for ethical critical thinking, yet relatively few studies have explored incorporating a contextual advance organizer into these AI-based approaches. This pilot study proposes an AI–human collaborative learning system architecture that integrates a spherical video-based virtual reality (SVVR) contextual advance organizer. A quasi-experimental study was conducted with 104 undergraduates in an asynchronous course to investigate how two types of contextual advance organizers, each paired with AI collaborative learning, affect learners’ critical thinking, active learning inclination, and perceived task–technology fit. The experimental group employed an SVVR-based contextual organizer, while the control group used a traditional case-based text. Results indicate that the SVVR organizer not only significantly boosts students’ critical thinking and active learning inclination but also enhances their perceptions of task–technology fit. It is recommended that future instructional designers adopt this system architecture in other courses to further promote learners’ critical thinking and active learning.
Fields of Study & Subjects
Education and Critical Thinking Development
Innovative Teaching Methodologies in Social Sciences
Intelligent Tutoring Systems and Adaptive Learning
Publication details
- Journal / source
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Volume
- 34
- Issue
- 7
- Pages
- 4683–4701
- Publication date
- 5 January 2026
- Language
- EN