Techniques for using artificial intelligence to foster active learning

6. Interactive simulations and decision-making scenarios based on artificial intelligence

Interactive simulations and decision-making scenarios are a powerful form of active learning because they enable learners to gain knowledge through their own actions. Rather than passively following a presentation, learners make decisions in a digital environment, observe the consequences, and continuously adjust their problem-solving strategies. Artificial intelligence-based systems adapt the simulation’s progression based on learners’ decisions, ensuring a personalised learning experience.

This form of learning is especially valuable in higher education, as it fosters the development of professional competencies that are difficult to acquire through purely theoretical approaches, such as critical thinking, solving complex problems, making decisions in uncertain situations, and taking responsibility for the outcomes.

Interactive simulations directly link key elements of active learning with real professional environments.

Example of an AI tool in a higher education setting:

Body Interact is a simulation system that uses artificial intelligence to model clinical situations in health sciences. Students actively participate in diagnostics and therapeutic decision-making, while the virtual patient’s condition changes in real time based on their actions. The tool requires an institutional subscription for full access and advanced features, while the basic version offers a limited number of scenarios free of charge. The effectiveness of teaching activities supported by this tool depends on the teacher’s pedagogical preparation and moderation.

Pedagogical value:

• Students learn from the consequences of their own decisions, encouraging a deeper understanding of cause-and-effect relationships.
• The simulation environment allows for safe learning from mistakes.
• Reflection, argumentation, and team decision-making are encouraged.
• Knowledge is applied in authentic professional environments.

This tool enables active experiential learning that goes beyond theoretical content acquisition and directly develops the professional competencies needed in higher education in health fields. Artificial intelligence dynamically adapts the simulation to students’ actions, thereby strengthening responsibility in learning.

In an emergency medicine course, students in groups care for a virtual patient with acute respiratory distress. 

The simulation is followed by a structured discussion in which students explain their decisions and analyse different approaches. This fosters critical reflection on actions and encourages students to reflect on their own assessments.