Learning Mechanics and Game Mechanics Under the Perspective of Self-Determination Theory to Foster Motivation in Digital Game Based Learning

• Only four of 16 reviewed studies found motivational increases from serious games, amid inconsistent DGBL findings.The reviewed instructional-game studies mostly used mathematics games, with participants ranging from elementary to higher education.Source: Educational technologies and motivation · p. 2
• Technology itself does not necessarily foster motivation; the activities it supports and their integration into the curriculum matter.The passage argues that technology-enhanced learning activities need adequate motivational stimuli.Source: Educational technologies and motivation · p. 2
• Motivational effects are difficult to isolate because classroom factors can mediate them and games contain varied mechanics that may help or hinder motivation.The passage gives teacher support and evaluation context as possible mediators, and notes that some games fail to engage certain learners.Source: Educational technologies and motivation · pp. 2–3
• The paper proposes analyzing DGBL at the micro level—through learning and game mechanics—and asks which SDT components relate to motivation and how LM-GM can operationalize them.The research plan reviews DGBL motivation, introduces SDT and its rationale, then examines links between SDT components and LM-GM.Source: Educational technologies and motivation · p. 3
• The literature review and SDT analysis are intended to establish the basis for mapping SDT components to LM-GM.The paper presents SDT as a motivation theory for analyzing DGBL and examines its links with LM-GM.Source: Educational technologies and motivation · p. 3

• A review of more than 70 classroom-game studies found affectivity and motivation in 33 studies and learning in 32.The broader literature generally reports a positive link between educational digital games and learner motivation.Source: Digital game based learning and… · p. 3
• Motivation may emerge from the fit among students’ goals and histories, game affordances, and institutional context, rather than from game use alone.The passage concludes that not every game experience is perceived as fun and that motivational potential may not materialize when relevant requirements are unmet.Source: Digital game based learning and… · p. 4
• The paper uses SDT to examine game design elements that could increase motivational potential and adopts LM-GM for its mechanics-level analysis.The stated research questions identify SDT components related to DGBL motivation and assess how LM-GM can operationalize them.Source: Digital game based learning and… · p. 4

Motivation theories in DGBL

• Flow theory and CET are among the motivational theories used in DGBL research.Flow has been extended to include playability and used to evaluate educational-game quality.Source: Motivation theories in DGBL · pp. 4–5
• Flow experience is described as cognitive absorption or task engagement in which unrelated thoughts and emotions do not affect the individual.The passage attributes the concept to Csikszentmihalyi and notes its later application to educational-game playability.Source: Motivation theories in DGBL · p. 5
• CET distinguishes intrinsic motivation, driven by interest and enjoyment, from extrinsic motivation, directed toward contingent outcomes.The paper says SDT, which includes CET, can provide a broader framework for evaluating motivation in games.Source: Motivation theories in DGBL · p. 5

• Studies cited in the paper link higher self-determined motivation with greater flow and deep task engagement.One cited study reports that participants with self-determined motivation reached the highest flow states; another finds they were more likely to experience flow.Source: Self-determination theory (SDT) · p. 5
• SDT combines CET with other motivational theories and identifies autonomy, competence, and relatedness as needs for growth.Autonomy concerns self-organizing and regulating behavior; relatedness concerns belonging and connection; competence concerns mastery and effectiveness.Source: Self-determination theory (SDT) · pp. 5–6
• The paper describes autonomy, competence, and relatedness as components that can positively influence intrinsic and autonomous motivation.Source: Self-determination theory (SDT) · p. 6

The continuum of autonomy and motivation within SDT

• SDT distinguishes amotivation, intrinsic motivation, and extrinsic motivation according to the reasons or goals behind an action.Source: The continuum of autonomy and… · p. 6
• Self-determination in learning is framed as requiring competence, social connection, autonomy, and coherence with students’ goals.Source: The continuum of autonomy and… · p. 6

SDT in education

• Learners benefit from teacher-supported autonomy, which is associated with growth orientation, competence, confidence, openness, and creativity.Source: SDT in education · pp. 6–7
• Teacher autonomy support is related to students’ autonomous motivation and engagement.Source: SDT in education · p. 7
• Intrinsic motivation and identified regulation have moderately strong positive relations with secondary-school achievement; introjected and external regulation relate negatively, while amotivation has a strong negative relation.Source: SDT in education · p. 7

• Games may be more likely to seem fun when they connect to students’ lives or offer meaningful choices reflecting their needs, interests, goals, abilities, and cultural backgrounds.Source: SDT within digital games · pp. 7–8
• The proposed game-mechanics components are autonomy, competence, relatedness, and coherence between game goals and students’ goals.Source: SDT within digital games · p. 8
• LM-GM’s micro-level analysis is presented as useful for using game mechanics to foster SDT components in game design.Source: SDT within digital games · p. 8

• The section describes Lim et al.’s LM-GM model for game design and reviews its impact in games where it has been used.Source: The learning mechanics game mechanics… · p. 8

• Existing frameworks are described as lacking robust methods to relate learning mechanics to game mechanics, a connection identified as key to learning-game design.Source: Introduction to LM-GM model · p. 8
• LM-GM treats pedagogical elements as an abstract interface and game elements as a concrete interface, with game mechanics expressed through rules or algorithms.Source: Introduction to LM-GM model · p. 8
• LM-GM is descriptive rather than prescriptive, allowing users to map learning and gaming mechanics to describe serious-game situations.Source: Introduction to LM-GM model · p. 8
• The model can support serious-game design or analysis by mapping ludic elements to pedagogical intent through player actions and gameplay.Source: What we know so far of the impact of… · p. 8
• PR:EPARe used LM-GM’s abstract and concrete mechanics to identify a pedagogic delivery style; a UK cluster-randomized trial with 505 participants reported positive outcomes for the game-based approach.Outcomes drew on self-reported psychosocial preparedness to avoid coercion and observations of students’ and teachers’ experiences.Source: What we know so far of the impact of… · pp. 9–10
• LM-GM has been combined with MDA to connect pedagogical and entertainment design, and used to inform stealth assessment and serious-game reuse principles; reusability remains a challenge for bespoke games.Source: What we know so far of the impact of… · p. 10

The game and learning mechanics under the perspective of the Self-determination theory (SDT)

• The framework combines the LM-GM classification with the SDT continuum to analyze mechanics’ potential to support motivation.Game mechanics are intended to support the game experience, while learning mechanics support the learning activity.Source: The game and learning mechanics under… · p. 10
• The framework organizes mechanics by Bloom’s taxonomy and their potential for extrinsic or intrinsic motivation.The horizontal axis runs from amotivation through extrinsic motivation to intrinsic motivation; the vertical axis runs from retention to creating.Source: The game and learning mechanics under… · p. 11
• Because games involve interaction, the authors place no game or learning mechanics in the amotivation zone.The mechanics’ learning outcomes and motivational potential also depend on how they are implemented in the learning situation.Source: The game and learning mechanics under… · p. 11
• Some mechanics, including meta-game and realism, cannot be classified, while a mechanic such as progression can occupy different motivational positions depending on its implementation.A fixed sequence may feel controlling, whereas a suggested pathway that leaves the route to learners may support autonomy.Source: The game and learning mechanics under… · p. 11

Discussion

• Autonomous motivation is expected when a game-based learning activity aligns with students’ goals, autonomy, competence, and relatedness.The authors state that meeting these four requirements should foster autonomous motivation.Source: Discussion · p. 11
• Table 2 presents game mechanics alongside learning mechanics according to their extrinsic and intrinsic motivation potential.Source: Table 2 · p. 12
• The LM-GM model can operationalize SDT components, but both the mechanics selected and how they are implemented shape players’ perceptions.The discussion uses progression as an example of a mechanic whose perception can vary with its implementation.Source: Discussion · p. 12
• Mechanics must be evaluated in context: teacher support can reduce perceived autonomy, while meaningful choices and team engagement can add autonomy to externally controlled mechanics.The authors call for balancing external and intrinsic motivation with learners’ competence and regulation or co-regulation capabilities.Source: Discussion · pp. 12–13
• The proposed framework combines SDT and LM-GM, but its compatibility and pedagogical relevance still require testing in a concrete classroom setting.The paper nevertheless argues that game design meeting the four player-activity requirements should contribute to enjoyment, motivation, and engagement.Source: Discussion · p. 13

Author Biographies

• Jean-Nicolas Proulx is an educational technologies PhD student and auxiliary teacher whose research interests include serious games, academic motivation, and game-based learning.His thesis focuses on game-based learning for academic success and motivation in high school history.Source: Author Biographies · p. 17
• Margarida Romero is an educational technology professor whose research includes creative and inclusive uses of technology to develop 21st-century skills.Source: Author Biographies · p. 17
• Sylvester Arnab is a Games Science reader whose research interests include gameful, playful, and pervasive designs.Source: Author Biographies · p. 17