Despite their prevalence in higher education, traditional lectures face well-documented limitations in sustaining attention and fostering conceptual depth. This session will demonstrate how an AI-enhanced audience interaction platform can motivate even the largest auditorium into participating in a dynamic learning environment through deliberate implementation of engagement principles.
During a 20-minute simulated lesson on hybrid human/AI cognition, participants will experience a progressive sequence of AI-facilitated micro-activities: diagnostic polls, peer-instruction cycles, collaborative canvases, rapid-fire brainstorming, and gamified challenges. Each element is generated or adapted in real-time by the platform’s generative AI engine, which produces questions, clusters responses, and branches subsequent prompts based on live analytics.
The activity sequence aligns with the ICAP engagement taxonomy (Chi and Wyilie, 2014) and is situated in the conversational framework model (Laurillard, 2002), illustrating how AI-augmented classroom response systems enables instructors to focus on orchestration, formative feedback, and disciplinary discourse rather than only lecturing performance.
A post-simulation debrief examines the underlying design logic, technical parameters, and institutional considerations: How can AI-augmented activities elicit higher-order thinking? What safeguards ensure data privacy and ethical transparency? Where should automation support faculty work, and where must human judgment remain central?
Attendees will leave with an editable Wooclap lesson template, a step-by-step engagement framework aligned with the ICAP model and the conversational framework, sample AI-generated question sets, and concrete design heuristics they can plug straight into any large-group Moodle course the next day.