MERIG: Design of a Multidimensional Evaluation Rubric for Informatics Games

This work-in-progress paper introduces MERIG, a multidimensional evaluation rubric for informatics games aimed at primary education. Its central argument is that many existing learning games fail to combine pedagogical rigor with inclusive design, which can deepen gender disparities in STEM participation. The rubric is meant to guide researchers, educators, and designers toward games that are both effective and equitable, and the authors position it as a conceptual prototype rather than a validated instrument.

The theoretical foundation draws on Constructionism, which emphasizes learning through active creation, the Universal Design for Learning framework, which promotes multiple means of engagement, representation, and action, and gender-sensitive design approaches such as the PECC Framework and the Gender-Inclusivity Framework. MERIG is organized into three dimensions: gender-sensitive inclusive design, which examines representation, stereotypes, and accessibility; pedagogical efficacy, which assesses learning objectives, observable evidence of competence, and empirical support; and ludo didactics, which considers feedback, intrinsic motivation, scaffolding, and learner agency. Each criterion is rated on a five-point Likert scale intended to capture gradations in quality.

The methodology is design-oriented and rests on a structured synthesis of literature and existing frameworks rather than on empirical data. The authors explicitly state that the rubric has not yet been tested or validated, and no participant data were collected. The scope is conceptual and focused on European primary informatics education.

The authors outline next steps: expert feedback from research, educational, and game-design stakeholders to refine criteria and resolve overlaps, development of concrete examples for each criterion and scale level, and application of the rubric to existing primary-school informatics games to test its analytical utility. Longer-term goals include empirical validation and broader adoption within the game-based learning community.