Abstract Thus, student motivation in science, technology, engineering, and mathematics (STEM) is a chronic problem, encouraging educators to include game elements in the allocated instruction. But two separate methodologies, gamification (adding elements from games, like points and badges, to non-game contexts) and game-based learning (employing full-bore games as the primary learning vehicle), are often confused with one another in both practice and research. This study aims to differentiate the effects of these factors on student motivation in secondary STEM classrooms. We will use a quasi-experimental design within six middle school science classes (N = 144). Three classes will receive a gamified adaptation of the standard curriculum, while three other classes will interact with a purpose-built educational game covering the same learning objectives. A control group will be taught traditionally. Intrinsic Motivation Inventory (IMI) will be administered pre- and post-intervention; additional qualitative data will be collected via semi-structured interviews. While both interventions are expected to lead to better motivation than conventional instruction, it is hypothesised that game-based learning will have a greater positive impact on intrinsic motivation and situational interest owing to its immersive narrative and authentic problem-solving contexts. On the other hand, gamification is believed to hold a more prominent role when it comes to extrinsic motivation and achieving task completion in the short run. Results will provide empirical guidance/useful case evidence for educators and instructional designers determining when to implement which game-informed strategies in order to facilitate sustained engagement in STEM.IntroductionBackgroundThe continuous drop in student motivation has been identified as a major concern for educators and policymakers around the world within science, technology, engineering, and mathematics (STEM) classrooms [1]. Although STEM literacy is considered essential for economic competitiveness, innovative minds in workforce development [1], surveys of students consistently show that interest in subject areas related to STEM declines markedly during the middle and secondary school years [2]. Traditional teaching methods, which typically involve lecture-style transmission of information and pre-packaged problem sets divorced from real-world context, often do not satisfy the basic psychological needs for autonomy, competence, and relatedness, three elements described in self-determination theory as essential for intrinsic motivation [3]. To address this motivational crisis, educators have increasingly adopted game-informed pedagogies [4]. The premise is solid: Digital games are carefully crafted to ensure abiding interest through challenge, feedback, narrative, and agency elements that closely map onto principles of effective learning spaces [5]. As a result, two different but often conflated strategies emerged: gamification, incorporating game-design elements such as points, badges, and leaderboards into non-game education [5], and Game-Based Learning (GBL): using full-blown games as the main vehicle for delivering content and getting students to practice skills [6]. The proliferation of these approaches mirrors a wider trend towards learner-centred, interactive pedagogies; the lack of conceptual clarity about their specific mechanisms is an ongoing challenge for both research and practice.Problem StatementAlthough gamification and game-based learning can rely on a similar foundation of game-inspired design, they are in fact two distinct instructional strategies grounded in different psychological and pedagogical mechanisms [7]. Gamification works by applying motivational affordances to preexisting curricular content, usually making use of extrinsic motivators to help ensure completion of tasks and compliance with desirable behaviours [8]. In contrast, game-based learning embeds the outcome objectives within the core mechanics and thematic structure of a game, striving to create intrinsic motivation through immersion, problem-solving, and authentic contextualization [9]. Despite these theoretical differences, educational literature as well as classroom practice often use the two terms interchangeably, leading to what some scholars have called “conceptual slippage” [10]. This conflation has meaningful consequences for practice: educators may add gamified elements through implementation in the expectation that doing so will cause deep engagement like game-based learning, or conversely, they may deploy complex educational games when simpler gamification strategies can all that is needed to achieve their intended outcomes [11]. From a research perspective, the absence of comparative studies that also consider the differential effects these approaches have on specific motivational outcomes has led to fragmented evidence bases that provide only general guidance for instructional design [12]. Earlier studies have tended to focus on one approach in isolation, and many of them do not evaluate whether the motivational impact is due to the specific game elements or simply general pedagogical factors such as novelty (of games) or teacher enthusiasm [13]. Furthermore, most existing studies are limited to short-term engagement metrics that do not specify between intrinsic or extrinsic motivational pathways [14], creating an important gap in understanding how such approaches differentially shape students’ longer-term interest in STEM domains.Purpose and Research QuestionsThis research will help to fill this gap by systematically comparing the differential effects of gamification and game-based learning on student motivation in secondary STEM classrooms. Instead of viewing motivation as a unitary construct, this work separates intrinsic motivation (engagement due to inherent interest and pleasure) from extrinsic motivation (engagement driven by external incentives or performance pressures), reasoning that these different forms of motivation may respond differently to game-informed techniques [15]. Using a quasi-experimental design that delineates the aspects of the described intervention conditions, this study aims to provide empirical clarity on which approach produces better outcomes for some motivational targets. As such, this study is guided by the following research questions:RQ1: How does intrinsic motivation differ between the gamified group and the game-based learning group?RQ2: How do extrinsic motivation and task engagement in both conditions differ?RQ3: What do students feel about each approach in terms of enjoyment, relevance, and perceived learning? In particular, these questions aim to both quantify differences in motivational outcomes as well as qualitatively describe students’ subjective experiences, thereby providing a more holistic view of how each strategy plays out in real-life classroom scenarios.Significance of the StudyThis study contributes to the body of knowledge in educational technology, both theoretically and practically. What theoretically expands self-determination theory by exploring how different game-informed strategies satisfy or thwart learners’ basic psychological needs for autonomy, competence, and relatedness differentially [3]. Although self-determination theory has been applied widely to explain motivation in traditional and digital learning contexts, few studies have explicitly examined how the underlying structural differences between gamification and game-based learning can cater to these fundamental needs [16]. This study enhances our understanding of the mechanisms that may underlie these motivational processes by mapping intervention characteristics onto theoretical constructs. Practically, findings will yield actionable guidance for STEM educators, instructional designers, and curriculum developers who must choose appropriate approaches at the intersection of game design with informal learning [17]. For applications where instant task completion and behavioural engagement are important objectives, gamification serves as a low-resources solution; for situations where in-depth conceptualisation and an enduring interest in the subject are of greatest concern, game-based learning might reflect a higher payback [18]. Moreover, by deconstructing motivational results, this study provides practitioners with specific insights that could aid in aligning pedagogical practices with different learning aims and optimising both instructional efficiency and resource utilisation [19]. By doing so, this study furthers the larger mission of transforming STEM education from a source of student alienation to one defined by curiosity, persistence, and genuine intellectual delight [20].Literature ReviewTheoretical Framework: Self-Determination TheoryThe theoretical framework for this study is based on self-determination theory (SDT), a macro-theory of human motivation that has been widely adopted in educational contexts [21]. Self-Determination Theory (SDT) asserts that intrinsic motivation, doing an activity for its inherent satisfaction instead of some separable consequence, thrives when three basic psychological needs are fulfilled: autonomy, competence, and relatedness [3]. Autonomy is defined as the experience of volition and psychological freedom; competence relates to the sense of being effective in one’s interactions with the environment; and relatedness refers to experiencing a meaningful connection with others [22]. Just supporting these needs leads individuals to be more intrinsically motivated, engaged, and thrive; however, thwarting these needs shifts motivation towards controlled extrinsic forms or may even lead to a complete absence of motivation [23]. In educational contexts, SDT has also been especially useful for understanding how instructional practices succeed or fail in maintaining student interest [24]. Yet, traditional approaches to STEM teaching, rooted in one-size-fits-all curricula and extrinsic grading pressures, frequently undermine both autonomy and relatedness [25], thereby reinforcing the downward trajectory of student motivation that is observed across secondary education. In contrast, game-informed pedagogies may offer ways to fulfil these psychological needs through mechanisms like choice (autonomy), scaffolded challenge (competence), and collaborative or competitive structures (relatedness) [26]. Most critically, SDT makes a distinction between intrinsic motivation (engagement in an activity for its own sake) and extrinsic motivation (engagement through the prospect of separable consequences), which is vital to understanding the divergent effects of gamification and game-based learning [27]. This study utilises SDT as a theoretical framework to analyse how each approach exerts an effect on different motivational pathways.Gamification in Education: Definitions, Mechanisms, and Empirical FindingsGamification is essentially the application of game design elements within non-game contexts [6]. In education, it usually means adding motivational affordances like points, badges, leaderboards, progress bars, and challenges to existing curricular activities while keeping the instructional content intact [28]. Usual mechanisms by which gamification can affect motivation are mainly based on behavioural and extrinsic elements, such as receiving points for immediate feedback, awarding badges when achievements are accomplished, and competitive social benchmarking using leaderboards [8]. The relatively low cost of implementing gamification and the ease with which it can be included in traditional schooling frameworks fuelled early enthusiasm [4]. It has produced inconclusive empirical support for its effectiveness in motivating behaviour. Sailer and Homner also conducted a meta-analysis of gamification studies that yielded small to moderate positive effects on cognitive, motivational, and behavioural outcomes across the studies; however, they noted significant variance in effect size as a function of contextual factors and implementation quality [29]. The most consistent positive effects are seen in extrinsic motivation and task completion metrics, with points and badges having reliable effects on how long participants engage for and participation rates [30]. However, concerns have been raised regarding the sustainability of such effects: high rates of extrinsic reinforcement may actually disrupt intrinsic motivation, a phenomenon termed the overjustification effect [31]. Furthermore, leaderboards can have harmful effects on motivation for low achievers due to decreased competence [32]. Qualitative research indicates that students do not consider gamified components as meaningful and perceive them to be superficial or manipulative when there is no incorporation with learning objectives [33]. These findings indicate that although gamification may prove beneficial in terms of driving behavioural engagement, it is still unclear whether this intervention has the capacity to facilitate deeper intrinsic interest around STEM content.Game-Based Learning: Definitions, Characteristics, and Empirical FindingsGame-based learning (GBL) is the use of fully developed digital or analog games as the main means for delivering educational material and developing skills [5]. In contrast with gamification, which adds a layer of game elements on top of existing instruction, GBL incorporates learning objectives into the core game mechanics, narrative structure in games, and problem-solving challenges [34]. Some essential features of good educational games are meaningful storytelling to give context, authentic tasks that require using knowledge, progressively increasing difficulty to cause flow, and chances to explore or discover [35]. The theoretical underpinning of GBL is rooted in constructivism, from which the notion that learners create understanding via active participation in authentic, situated contexts [36] emerges. The empirical data have largely confirmed the effectiveness of GBL in improving motivation and learning outcomes. A comprehensive meta-analysis conducted by Clark and co-authors has shown that games consistently outperformed traditional instruction for both learning and retention across a variety of subjects, with particularly strong effect sizes for STEM subjects [37]. In relation to motivation, GBL has been linked with enhanced situational interest, perceived autonomy, and effort in difficult tasks [38]. In particular, the purported immersive quality of narrative-driven games likely satisfies a psychological need for relatedness through identification with characters and meaningful social interactions in-game [39]. Longitudinal research has shown that GBL results in long-lasting effects on motivation towards STEM careers when games include authentic practices of science, such as experimentation and modelling [40]. Implementation challenges have included increased development costs, extended time commitments, and the necessity for teacher training to implement game-based experiences effectively [41]. Furthermore, bad game designs (those that underemphasize pedagogy in favour of fun) can lead to engagement but no better learning gains [42]. The evidence indicates that GBL is more effective than gamification for cultivating intrinsic motivation and deep conceptual understanding despite these challenges.Comparative Studies: Review of Existing Research Contrasting the Two ApproachesAlthough there is now a significant amount of research on both gamification and GBL, little research directly compares their different effects on motivation within the same methodological frame [12]. The comparative literature is limited in both quantity and scope. In a study by de-Marcos and colleagues, the effectiveness of a gamified learning platform was tested against serious games in relation to information literacy instruction, finding that while the game produced better learning outcomes, a greater impression of perceived enjoyment was found with a gamified approach [43]. In contrast, a study by Su and Cheng found that elementary science learners exposed to game-based learning exhibited significantly greater learning motivation and self-efficacy than those who received gamified instruction [44]. These contradictory findings indicate that contextual factors such as age group, domain of study, and fidelity of implementation moderate the relative success of either approach. However, a recent systematic review by Li et al [12] identified only twelve empirical studies that directly compared gamification and game-based learning in any educational context, concluding that the evidence base is still too fragmentary to draw firm conclusions. The primary gaps in the research included: (a) a failure to differentiate between intrinsic and extrinsic motivational outcomes, (b) little use of studies including control groups with no-game treatment conditions to control for novelty effects, (c) few examining whether different subgroups of students (based on factors such as prior gaming experience or academic achievement) might benefit from approaches differently; and (d) qualitative data capturing students’ subjective experience with each approach was lacking [14]. Moreover, most comparative studies used pre-existing games or gamified platforms that vary on multiple other dimensions besides the central dichotomy of approach used, adding confounding variables that limit interpretability [45]. This research fills these gaps by creating interventions that hold content, length, and instructor attributes constant while systematically varying the game-informed strategy.Hypotheses DevelopmentFrom the theoretical framework and empirical literature discussed, we propose the following hypotheses. Firstly, regarding intrinsic motivation, GBL is theorised to fulfil the psychological needs for competence and relatedness due to its immersive and autonomy-supportive characteristics more effectively than gamification’s predominantly extrinsic mechanisms [5], [38]. Hence, the H1: Students in the game-based learning condition will show significantly higher levels of intrinsic motivation after interaction compared to students in the gamification condition, controlling for pre-test motivation scores. Second, in the context of extrinsic motivation and task engagement, it is anticipated that gamification’s reliance on tangible rewards, individual progress tracking, and social comparison mechanisms [8], [30] will create more robust short-term behavioural compliance. So, H2 would be that Gamification conditions students will show significantly greater extrinsic motivation and task completion than the GBL group. Third, qualitative judgements of enjoyment, relevance, and perceived learning are anticipated to be more favourable towards GBL based on its ability to situate STEM content within meaningful stories and real problem-solving situations [35], [40]. Therefore, H3: Students in the game-based learning condition will have more positive perceptions of enjoyment and relevance, and perceived learning in semi-structured interviews, compared to students in the gamification condition. Collectively, these hypotheses postulate a trade-off between the two: gamification may be optimal for short-term behavioral engagement while GBL is hypothesized to produce better outcomes for intrinsic motivation and meaningful learning experiences.Methodology This section describes the research design, participant characteristics, intervention conditions, instrumentation, procedures, and data analysis methods employed to address the research questions. The methodology is structured to ensure replicability and to support valid inferences regarding the differential effects of gamification and game-based learning on student motivation.Research DesignThis study uses a quasi-experimental, non-equivalent groups design with pre-test and post-test measures [46], [47]. Since random assignment of individual students is impossible in real school settings, intact eighth-grade science classes are randomly assigned to each of three conditions: gamification, game-based learning, and traditional instruction (control). This approach allows for the comparison of motivational outcomes while controlling for pre-existing differences using pre-test covariate adjustment [48]. A control group enables the separation of treatment effects from those due to confounding factors like maturation or history. The design is factorial (3 (condition) × 2 (time)), allowing for analysis of main effects, as well as interaction effects across conditions.ParticipantsDuring the fall of 2025, data were collected via semi-structured interviews with participants who were recruited from six eighth-grade science classes in a public middle school situated in an urban district in the Midwestern United States. The school is home to a diverse student body: 44 per cent White, 27 per cent Hispanic/Latino, 19 per cent African American, and 10 per cent Asian or multiracial. About 38 per cent of schoolchildren qualify for free or reduced-price lunch. All the students in six classes can join. Inclusion criteria include being enrolled in eighth-grade general science and demonstrating both student assent and parental consent. (Students with individualised education plans (IEPs) directing teachers to provide alternative science instruction are ineligible, but are excluded to prevent contamination of the intervention; similarly, students whose proficiency in English is so limited that it would affect responding on self-report instruments are ineligible.)The required sample size is determined via a priori power analysis using G*Power 3.1 [49]. Assuming f = 0.25, α= 0.05, and power = 0.80 for a three-group ANCOVA with one covariate, the total required sample size is N = 172. Target enrolment is 172 students, accounting for an expected 15 per cent attrition. These estimates meet the minimum per-class thresholds, comprising six classes with average sizes of 28–32 → 180–192 people. Demographic and background variables, such as prior science achievement (i.e., last semester grade) and prior gaming experience (self-report item), were collected at the pre-test stage.Intervention ConditionsAll three conditions address identical learning objectives aligned with state science standards for forces and motion (physical science). The instructional duration is four weeks, with equivalent instructional time per condition. Table I summarises the distinguishing features of each condition.Table 1. Comparison of intervention conditions.
