Towards a Revised LM-GM Framework for Classroom Analysis: A Systematic Literature Review

This systematic literature review examines whether the Learning Mechanics–Game Mechanics (LM-GM) framework, introduced by Arnab et al. (2015) for mapping pedagogical mechanisms onto game features in serious games, can be adapted for game-based learning in adolescent classrooms serving learners aged 12 to 16. The author argues that LM-GM is flexible enough to serve as a baseline across stakeholders, yet it lacks a mature treatment of adolescent differences, classroom constraints, and teacher orchestration. The review follows the PRISMA protocol, searching ERIC and JSTOR and using AI-assisted literature retrieval, which yielded roughly 353 database records plus nine supplementary sources. After deduplication and screening against inclusion criteria covering LM-GM centrality, adolescent learners, and bridges to self-determination theory (SDT) or player profiles, the review synthesizes a limited body of directly relevant studies.

The review identifies four significant extensions and applications. Callaghan et al. (2017) applied LM-GM to an engineering education game and reported that explicit mapping improved student engagement, though domain-specific adaptation was required. Jaccard et al. (2021) embedded LM-GM within the co.LAB collaborative design ecosystem, which supports multidisciplinary project management but does not address learner-level differences. Shearer's SMGX framework offers an ontological, machine-readable representation of game events that may support AI-based personalization, though it has seen little practical implementation. Iskandar et al. (2024), the study most directly relevant to adolescents (ages 13 to 15), found that a game redesigned using LM-GM principles produced better engagement, with genre, flow, and felt competence emerging as the most effective elements.

A central finding concerns the motivational extension of LM-GM through SDT. The review reports that adolescents are particularly sensitive to peer relatedness, performance comparison, and autonomy, and that LM-GM mappings lacking motivational analysis may yield pedagogically coherent but motivationally inert games. A reanalysis by Lobo (2023) found that visible leaderboards and competitive scoring corresponded to externally regulated engagement rather than intrinsic motivation. By contrast, the review finds the literature on learner profiling sparse and mixed: profile-based adaptation produced heterogeneous effects, and studies by Lavoué (2019) and Halif