Facilitating adaptive learning: A QCA study on conditions for learning in simulation games

Background Research on how facilitation design and facilitator interventions influence adaptive learning outcomes in simulation games remains limited. While previous studies have examined individual learning conditions in simulation games, less is known about how these conditions operate in combination to support adaptive learning. Aims This study investigates which combinations of facilitation design conditions and facilitator interventions enhance adaptive learning outcomes in simulation games. Samples The study analyses 31 simulation game cases from educational and organizational contexts. Methods A Qualitative Comparative Analysis (QCA) was conducted to examine configurations of five learning conditions: buy-in (buyin), expectancy guidance (expect), intervention approach (interv), learning loops (loops), and debriefing setup (debrf). Data were retrieved from multiple sources, including session transcripts, interviews with facilitators and participants, session reports, questionnaires, in-game assessments, and reflection materials. Results Two intermediate configurations leading to adaptive learning outcomes were identified. Configuration 1 consisted of buyin∗expect∗loops ∼ debrf, while Configuration 2 consisted of buyin∗interv∗loops∗debrf. The parsimonious solution (buyin∗loops) indicates that buy-in and learning loops constitute core conditions across configurations linked to the outcome. Necessity analysis further shows that expect and interv also function as necessary conditions, although they appear in different configurations. Debriefing does not emerge as a necessary condition and contributes to the outcome only within specific configurations. Conclusions These findings provide insight into how facilitation design conditions interact in simulation games and offer guidance for preparing facilitation strategies that support adaptive learning.