Cross-case synthesis
This cross-case synthesis brings together the insights from the two scenario planning sessions of the PWO SAIL project: one involving the Creative Media Management (CMM) programme and one involving Applied Computer Science (TI). The analysis builds on the individual session analyses for both programmes and follows the methodological approach described in the WP2 approach and analysis document (Competence analysis and desired level of autonomy). Together, the methodological framework, the two session analyses and this cross-case synthesis form the analytical foundation of WP2.
The aim of this synthesis is not to reduce both domains to a single, uniform vision of GenAI. The analysis aims to highlight where professional logics intersect, where they diverge, and which conceptual axes and typologies are useful for understanding different forms of professional autonomy within AI-integrated contexts. The choice of these axes and typologies is an interpretative choice made by the researchers, guided by the objective of WP2: to provide educational programmes with tools to shape the integration of AI into curricula in a way that continues to support professional autonomy, in-depth understanding and sustainable competence development.
Although this analysis is primarily based on competences and professional autonomy, the findings suggest that underlying professional dispositions also play an important role. After all, the areas of tension identified do not relate exclusively to what professionals need to know or be able to do, but also to their sensitivity in interpreting situations correctly and their willingness to exercise professional judgement and take responsibility within AI-integrated work processes. In both the CMM and TI sessions, critical assessment, taking responsibility, exercising control and interpreting context meaningfully appear to be not only about what professionals are capable of, but also about their willingness to actually act upon this when the situation demands it. The concept of disposition therefore appears to be a useful additional lens through which to interpret the findings of this synthesis and to ensure that curriculum development is not focused exclusively on what students need to know and be able to do, but also on the professional dispositions that help determine whether and how these competences are actually applied in AI-integrated professional contexts.
Against this background, both sessions confirm the central hypothesis of WP2: the question is not whether professionals will use GenAI, but what forms of professional autonomy will remain necessary once AI becomes structurally integrated into professional contexts. At the same time, both sessions make it clear that professional autonomy within CMM and TI is interpreted differently, depending on the professional context in which AI is used. Although both programmes experience similar areas of tension, the emphases and concrete interpretations of autonomy differ, with direct implications for curriculum development.
Given the exploratory nature of this phase, the findings are indicative and analytically exploratory, but not exhaustive. They are based on two sessions within a single institution and will be further validated in a subsequent phase.