This paper presents two strategies for metadata-matrix-based cross-case analysis of 19 national cases within the Horizon Europe project AECED (Transforming Education for Democracy through Aesthetic and Embodied Learning). The project unites six universities—UK, Finland, Germany, Portugal, Croatia, and Latvia—each with diverse linguistic, educational, and cultural contexts, yet all following a shared Participatory Action Research (PAR) framework across six phases: introduction, familiarization, collaborative reflection, planning, action, and reflection (Kemmis et al., 2014). To systematize experiences and track transformational changes, the project developed a Metadata Matrix (Oganisjana & Kozlovskis, 2024), structured into six metacolumns, each aligned with a PAR phase and integrating four memoing dimensions—descriptive, reflexive, conceptual, and theoretical. Memoing fosters reflexivity (Birks et al., 2008), supports code and category development (Charmaz, 2006), and enhances collaborative interpretation and analysis (Saldaña, 2016). Both cross-case analysis strategies begin with the formulation of a common research question to ensure comparability across cases (Miles & Huberman, 1994). From this shared starting point, the strategies diverge in their approach, each offering distinct advantages and challenges. Strategy 1: Open Coding & Cross-Case Thematic Analysis This approach involves conducting qualitative content analysis with open coding to inductively develop categories (Yin, 2018). A cross-case thematic analysis follows, identifying similarities and divergences (Braun & Clarke, 2006). Memoing across the four dimensions supports contextual and procedural analysis, revealing structural and procedural patterns that influence the democracy-related effects of aesthetic and embodied learning (Saldaña, 2016). The findings are synthesized into conceptual models or typologies, using visual tools to illustrate relationships (Maxwell, 2012). To enhance reliability, triangulation of data sources, member checking, and detailed contextual descriptions are employed to support interpretation. Strategy 2: Preconstructed Coding with Contextual Adaptation In this approach, one research partner conducts an inductive qualitative content analysis, developing an initial coding scheme. The remaining partners use these preconstructed codes as a starting point while retaining the flexibility to make case-specific modifications, ensuring a balance between standardization and contextual sensitivity (Fereday & Muir-Cochrane, 2006). Cross-case comparison identifies not only the frequency of preconstructed codes but also emerging insights (Saldaña, 2016). The findings are synthesized into a conceptual framework, highlighting shared patterns and context-dependent variations, demonstrating how the democracy-related effects of aesthetic and embodied learning differ based on institutional, pedagogical, and cultural contexts.

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