Description
Prof. Dr. John Bessant, innovation scholar and FAU Ambassador since 2018, experiments with AI as a personal teaching assistant and as a learning coach for students. He uses AI to creatively redesign learning materials, translate concepts into alternative formats, and provide personalized support for large and heterogeneous student groups. AI serves as his “co-pilot,” processing the knowledge from his textbooks, guiding students through complex content, and offering individualized feedback. His goal is to make teaching more dialogical, personalized, and competence-oriented again — much like tutorial systems, but now supported by scalable AI tools.
„It’s a wonderful opportunity … with AI, I can give students a coach, a personal coach, and that AI can act as their guide through the material.“– Prof. Dr. John Bessant
Initial Situation
Many academic subjects, especially in innovation, management, and the social and economic sciences, are highly knowledge-intensive and heavily text-based. Instructors face large cohorts, diverse backgrounds, and very different levels of prior knowledge. At the same time, time and resources are limited, making it difficult to address each individual learning need. Added to this are new challenges posed by AI-generated text: students already use AI extensively, sometimes uncritically or to circumvent assessment requirements.
„I stand in front of 100 students… and I hope they hear the message in the way they need to hear it. That’s a pretty ambitious expectation.“– – Prof. Dr. John Bessant
Objectives
Prof. Dr. Bessant’s teaching approach pursues several strategic objectives:
- Enable personalization: Students should receive individualized learning pathways and continuous feedback.
- Creatively transform learning materials: AI should translate content into diverse formats (simulations, games, examples).
- Reform assessment: AI should provide constructive, individualized feedback at scale.
- Strengthen self-regulation and critical thinking: Students should use AI not as a shortcut, but as a tool for deeper understanding.
- Expand teachers’ competencies: AI is used as a learning partner and an innovator within one’s own didactic practice.
„What I want is to personalize the learning, but there isn’t enough time in the day. With AI, I can give them a coach.“ – Prof. Dr. John Bessant
Concepts, Implementation, Methods
Prof. Bessant uses AI as a creative co-pilot: he feeds his textbooks, examples, and instructional designs into the system and lets the AI generate new formats—games, simulations, role-plays, or alternative visualizations. AI functions as a design engine that structures ideas and produces creative variations. In parallel, he develops AI-based personal tutors that guide students individually through his content. The tutor “learns” his materials (“learn this yourself”) and then takes on classic tutorial functions: explaining, probing, diagnosing misunderstandings, and giving feedback.
Another major focus is AI-supported assessment: AI is used to analyze essays, apply rubrics, and deliver personalized feedback. Bessant examines how AI can reduce the workload of feedback processes while improving their quality. Didactically, he actively experiments—using a flipped-classroom approach, shared learning experiments with students, and dialogic interaction in AI-supported learning environments.
Experiences
- AI strongly supports the structuring and creative redesign of learning materials.
- Students use AI productively when they reflect together with instructors on how and why they are using it.
- AI is well suited for differentiated feedback and can detect common reasoning errors in student work.
- Weaker students in particular benefit from the “super tutor” function of AI.
- Learning environments become more dialogical: students ask more questions—and sometimes more complex ones than the instructor—which leads to inspiring learning moments.
„It’s a conversational device… like having your own private tutor who pushes you in the right direction.“ – Prof. Dr. John Bessant
Success Criteria
- Improved learning materials: AI generates a wide range of formats that address different learning styles.
- Greater personalization: Students receive granular, dialogical support without additional workload for instructors.
- Efficient assessment: AI helps generate feedback without replacing human quality assurance.
- Increased student activity: Learners contribute more questions and engage more actively in class.
- Low-threshold innovation: Instructors can safely experiment with AI in small, low-risk trials.
Overview„Don’t be afraid to play. Try small experiments — that’s how we learn what this thing can do.“ – Prof. Dr. John Bessant