The evolution of the case method in education

Higher education increasingly faces pressure to provide engaging and flexible learning experiences that go beyond theoretical knowledge, developing critical thinking, problem-solving, and interpersonal skills. The case method, a long-standing approach especially prominent in management education and famously used at Harvard Business School, has played a vital role in this. Traditionally, students analyze static case documents, participate in classroom discussions, and engage in structured debates to build decision-making skills. While effective at fostering critical thinking and interaction, this approach lacks adaptability to the evolving case context.

The GenAI-enhanced case method introduces a transformative dimension by boosting engagement, personalization, and realism in experiential learning.

How the GenAI-enhanced case method differs from traditional case teaching

Unlike the traditional static case method, the GenAI-enhanced approach leverages generative AI to create dynamic, interactive, and iterative learning environments. Key differences include how students engage with case characters, receive feedback, and experience the unfolding case narrative.

Traditional cases present students with fixed documents to analyze, offering limited external input. In contrast, the GenAI-enhanced case method enables interaction with AI-driven characters representing real stakeholders. Students can ask questions, negotiate, and navigate evolving scenarios in real time. Feedback is immediate and personalized, supporting deeper reflection and learning, whereas traditional methods depend on instructor feedback after assignments and discussions.

Furthermore, traditional cases remain unchanged regardless of student actions. GenAI-enhanced cases evolve based on student decisions, reflecting the complexity and unpredictability of real-world situations. This fosters iterative and adaptive learning, allowing students to revisit and refine their analyses in light of AI-generated responses—better simulating authentic decision-making.

From traditional to GenAI-enhanced case: Case Nordica and LessonLab’s Taito platform

Case Nordica illustrates how traditional case materials can be transformed into GenAI-enhanced learning experiences. Originally, it was a written case focusing on stakeholder management in a cross-border pulp mill project, requiring students to analyze stakeholder interests and discuss management strategies.

Through LessonLab’s TAITO platform, Case Nordica has been converted into an interactive GenAI-enhanced case simulation. Students engage directly with AI-generated stakeholders, interviewing and negotiating to explore perspectives and perform realistic stakeholder analyses. Their decisions regarding managing the case stakeholders dynamically influence the case scenario and stakeholder reactions. Students’ actions are followed by tailored real-time feedback, enabling deeper reflection and learning. This method enhances realism and learning outcomes while helping students build strategic and interpersonal skills.

LessonLab’s TAITO platform enabled rapid and easy conversion of traditional Case Nordica into GenAI-enhanced case simulation. Case Nordica has already been piloted at London South Bank University and University of Oulu. Feedback indicates that students appreciate the realism and interactivity, while instructors value the increased engagement and improved learning results.

The future of AI-enhanced case teaching

As GenAI-enhanced case teaching continues to evolve, it opens up several promising opportunities for higher education.

One of the most significant advantages is scalability. The GenAI-enhanced case method can support case-based learning for large student cohorts while still providing personalized feedback and assessment, something that would be difficult or at least very resource-intensive to achieve with the traditional case method.

The approach also delivers greater realism, simulating authentic business and policy dilemmas that mirror real-world complexities. In addition, AI has the capacity to facilitate collaborative learning by enabling multi-stakeholder role-playing exercises. These exercises help students prepare for the demands of complex negotiations and interdisciplinary collaboration.

Additionally, the GenAI-enhanced case method also allows for continuous improvement of the case itself. As students interact with the system, data can be collected and used to refine the case scenarios, enhancing pedagogical effectiveness over time.

In sum, GenAI-enhanced case teaching represents a significant advancement in experiential and active learning. It complements rather than replaces traditional methods, adding a powerful, interactive, and adaptive dimension to education. The main challenge for educators is to thoughtfully and responsibly integrate GenAI into curricula.

Author

Dr. Kirsi Aaltonen, LessonLab Oy