Abstract:

The 21st century has transformed expectations in higher education, emphasizing graduates’ ability to demonstrate critical thinking, collaboration, adaptability, and metacognitive skills rather than mere content mastery. Traditional lecture-based models, which prioritize passive knowledge transmission, often fail to cultivate these competencies. Flipped learning has emerged as a promising alternative, reconfiguring instructional time to prioritize active, student-centered engagement. In this model, students engage with pre-class materials—such as readings and videos—before attending sessions devoted to collaborative problem-solving and applied activities. Grounded in cognitive load theory and constructivism, flipped learning reduces cognitive overload by allowing students to process foundational knowledge at their own pace and promotes social co-construction of knowledge during class.

Despite its benefits, implementing flipped learning in higher education presents significant challenges. Designing high-quality pre-class resources and recording instructional videos demand substantial time and technical expertise, often exceeding instructors’ capacity. Balancing content coverage with student engagement further complicates course design, particularly for freshman cohorts who may lack self-regulation skills and perceive flipped learning as burdensome. These barriers underscore the need for innovative strategies that minimize instructor workload while maximizing pedagogical effectiveness.

This study explores a targeted flipped learning approach in a freshman-level communication skills unit focusing on active listening, conflict management, and mediation—topics that benefit from applied practice. To address design and preparation challenges from the instructor, generative AI (GenAI) was integrated into pre-class learning activities, enabling students to interact with AI-driven content summaries and scenario-based prompts before class. Students were also required to complete reflective exercises to consolidate understanding. Data were collected from learning platform for students’ engagement levels and through surveys assessing student perceptions of lesson design.

Findings suggest that students demonstrated strong engagement with pre-class activities. Survey responses indicate that learners agreed the AI-supported activity was an enjoyable and fruitful way to prepare for lessons. Both pre-class and in-class components contributed to a flexible and encouraging learning environment. Students perceived the design as well-structured, with materials that were sufficiently challenging to stimulate learning. Additionally, the presence of deadlines created a sense of urgency, motivating students to complete tasks on time and arrive well-prepared for in-class discussions and role-play activities.

This study contributes to the growing discourse on scalable flipped learning strategies in higher education by demonstrating that flipping, supported by GenAI, can mitigate implementation barriers while preserving pedagogical integrity. By minimizing content overload and leveraging AI for pre-class preparation, instructors can create active learning environments without incurring prohibitive resource demands.

Keywords:

Flipped learning, GenAI, Active Learning, Active Listening, Conflict Management, Mediation.