Gamification has become the default solution to online education's engagement problem. Nearly every major MOOC platform—Coursera, edX, Udemy, FutureLearn—incorporates game mechanics: progress bars, achievement badges, streaks, points, leaderboards, and completion certificates. The logic is intuitive: if games can hold attention for hours, game-like elements should be able to hold attention in educational contexts. And attention, the argument continues, is a prerequisite for learning.
The research literature, however, reveals a more complicated picture. Gamification consistently increases engagement metrics—time on platform, click rates, session frequency, course activity. Whether it increases learning—the acquisition of knowledge, skills, and understanding that persist beyond the gamified environment—is a different question with a different, less encouraging answer.
The Engagement-Learning Gap
Suartama, Sudarma, and Gde (2024) examine the effect of gamification on student engagement and academic achievement in case- and project-based online learning. Their study is valuable because it measures both engagement (activity levels, participation frequency) and achievement (assessment performance, skill demonstration) separately, rather than conflating them.
The challenge of maintaining student engagement and promoting academic achievement in online learning environments was intensified during the COVID-19 pandemic, when digital platforms became the primary mode of instruction. The study examines whether gamification—applied specifically to case-based and project-based learning—produces durable learning effects or merely cosmetic engagement increases.
The distinction between engagement types matters. Behavioral engagement (logging in, completing activities) is relatively easy to gamify—points and progress bars directly incentivize observable actions. Cognitive engagement (deep processing, transfer, critical thinking) and emotional engagement (interest, value, identification with the subject) are harder to influence through game mechanics. A leaderboard can motivate a student to complete a quiz, but it cannot motivate them to think deeply about the quiz content.
Teacher Perspectives from Nigeria
Ikpat (2025) investigates teachers' perceptions of gamification's influence on student engagement and learning outcomes in Nigerian primary schools. Using a mixed-methods approach involving quantitative surveys and qualitative interviews, the study captures how educators—who must implement gamification in practice—understand its effects and limitations.
The Nigerian context is significant because it represents conditions that differ from the well-resourced environments where gamification is typically studied: limited technology infrastructure, large class sizes, and teachers who may have minimal training in educational technology. Gamification that "works" in a Stanford MOOC may not transfer to a Lagos primary school.
The findings indicate that teachers perceive significant positive impacts on academic achievement, student participation, and knowledge retention. Badges and points were the most frequently used gamification elements, most commonly applied in mathematics. However, teachers also highlighted challenges including lack of technological resources, curriculum alignment difficulties, skepticism from stakeholders, and insufficient training. A broader concern in the gamification literature—the well-documented "overjustification effect" in which external rewards may reduce intrinsic motivation—remains relevant: when the badges stop, does the learning stop too?
Learning Analytics and Gamification in MOOCs
Yunus, Sulaiman, and Wong (2025) examine learning analytics specifically applied to gamified MOOC environments. The evolution of the education system brings learning institutions that offer online knowledge delivery as an alternative, giving more flexibility to learners. The study investigates how learning analytics can capture and analyze the engagement patterns that gamification produces.
The learning analytics approach offers a methodological advance: rather than measuring gamification effects through pre/post tests (which capture aggregate outcomes but miss process), analytics can track how gamification changes the pattern of learning behavior—whether students distribute their study time more evenly, engage with a wider range of content, or spend more time on difficult material.
The study examines engagement trends across different parameters—including how learners interact with course content, participate in comments, and spend time on courses—to identify which types of gamification engage students more. The broader gamification literature suggests differential effects: progress indicators (progress bars, completion percentages) tend to increase consistent engagement over time, competitive elements (leaderboards, rankings) may increase short-term intensity but discourage students who fall behind, and social elements (peer badges, collaborative challenges) may increase breadth of engagement but reduce depth.
AI + Gamification: The Next Integration
Shtayyat and Gawanmeh (2025) examine the emerging integration of gamification and AI in Moodle-based higher education e-learning. Rather than treating gamification as a static set of design elements, they explore how AI can make gamification adaptive—adjusting game mechanics to individual learner profiles, performance trajectories, and motivational states.
The combination is conceptually promising. Static gamification applies the same mechanics to all learners: everyone sees the same leaderboard, earns the same badges, follows the same progress bar. Adaptive gamification could provide competitive elements to students who are motivated by competition, collaborative elements to students who are motivated by social connection, and mastery indicators to students who are motivated by competence.
However, adaptive gamification also raises the concerns identified in the broader AI-education literature: algorithmic profiling of motivation, the risk of manipulation (using psychological insights to maximize engagement rather than learning), and the privacy implications of continuous motivational monitoring.
The Theoretical Framework
Sylvester (2025) provides a comprehensive overview of gamification in educational contexts by examining theoretical frameworks, design principles, and case studies. The paper explores self-determination theory (SDT)—the framework of autonomy, competence, and relatedness—as the theoretical basis for understanding why some gamification elements work while others do not.
SDT predicts that game elements supporting autonomy (choice, self-pacing), competence (clear goals, meaningful feedback, calibrated challenge), and relatedness (social connection, collaborative goals) should enhance intrinsic motivation and learning. Game elements that undermine these needs—mandatory competition, punitive failure mechanics, extrinsic-only rewards—should be counterproductive.
This theoretical lens explains the inconsistent findings in the empirical literature. Gamification is not a monolithic intervention; it is a collection of design choices, each with different psychological mechanisms and different effects depending on context, population, and implementation quality.
Claims and Evidence
<| Claim | Evidence | Verdict |
|---|---|---|
| Gamification increases student engagement in online learning | Suartama et al. (2024), Yunus et al. (2025): consistent behavioral engagement increases | ✅ Supported |
| Gamification improves learning outcomes | Mixed: some studies show gains, others show engagement without learning transfer | ⚠️ Uncertain |
| Competitive gamification elements (leaderboards) benefit all students | Yunus et al. (2025): short-term intensity increase but potential discouragement for low-performers | ⚠️ Uncertain (population-dependent) |
| Teachers view gamification positively | Ikpat (2025): positive impacts on achievement and participation, but challenges include resource limitations, curriculum alignment, and stakeholder skepticism | ⚠️ Uncertain (conditional) |
| AI-adaptive gamification outperforms static gamification | Shtayyat & Gawanmeh (2025): conceptually promising but empirical validation limited | ⚠️ Uncertain |
Open Questions
Implications
The evidence base suggests that gamification is a useful but insufficient tool for online education. It addresses the behavioral dimension of engagement effectively—getting students to show up, participate, and complete activities. Whether it addresses the cognitive and emotional dimensions—thinking deeply, caring about the subject, transferring learning to new contexts—depends entirely on how it is designed.
The implication for course designers is that gamification should be treated as a pedagogical decision, not a technical feature. Choosing between competitive and collaborative elements, between extrinsic and intrinsic rewards, between progress indicators and mastery challenges is a choice about what kind of learning environment you are creating. The most effective gamification is pedagogically informed, culturally appropriate, and evaluated against learning outcomes—not engagement metrics.