Study Notes: Gamification for Student Engagement - A Theoretical Mapping and Framework Analysis

Overview of Gamification and the Higher Education Landscape in the United Kingdom

In the modern Higher Education (HE) environment within the United Kingdom (UK), ensuring student satisfaction and positive outcomes has transitioned into a political and economic priority. This shift is reflected in the Department for Business (2016) white paper entitled ‘Higher Education: Success as a Knowledge Economy.’ The term ‘student engagement’ is currently applied loosely across the sector and is measured through several surrogates that have substantial consequences for institutional success, such as the National Student Survey (NSS). The NSS measures student satisfaction, which in turn feeds into league tables and the Teaching Excellence Framework (TEF), influencing funding and student recruitment. Consequently, supporting student engagement is of paramount importance to education providers, while also offering implicit benefits to students through a student-centred approach to education, as noted by Tangney (2014).

Gamification, defined as the application of game elements to non-game situations, has gained traction in education as a mechanism for reinforcing motivation and learning outcomes. While it is widely accepted that gamification can enhance engagement in business and education, the supporting evidence remains equivocal. Research has historically emphasized behavioural responses, yet there is emerging evidence that gamification can support deeper cognitive and affective aspects of learning. Despite this potential, it remains unclear how gamification specifically influences student engagement to lead to learning. This paper by Errol Scott Rivera and Claire Louise Palmer Garden, published in the Journal of Further and Higher Education (2021, Vol. $45$, No. $7$, pp. $999–1012$), seeks to bridge the gap between practice and theory by synthesizing student engagement and gamification literature into a new Gamification for Student Engagement Framework.

Defining Gamification and Analyzing Current Research Evidence

Gamification is distinct from game-based learning and serious games because it employs specific elements of games without transforming the entire learning process into a fully-fledged game. The term entered the mainstream around the year $2010$. This study adopts a simplified version of Landers’ ($2014$) definition of gamification: ‘the use of game attributes outside the context of a game with the purpose of affecting learning.’ This definition does not stipulate which specific game attributes must be present, allowing for a nuanced application beyond the simple dichotomy of traditional instruction versus badges and points as described by Alsawaier ($2018$).

Research regarding the impact of gamification is currently limited by a focus on motivation, which represents only a small facet of student engagement according to Kahu ($2013$). Dichev and Dicheva ($2017$) conducted a systematic review to identify empirical evidence for the impact of gamification on motivational processes and learning effectiveness and found equivocal results. Their findings indicated that $26\%$ of empirical papers reported a positive effect, while nearly two-thirds of the studies ($64\%$ approximately) were inconclusive, and $10\%$ reported negative outcomes. Many studies focus on behavioural outcomes—such as ‘time on task’ or assessment attainment—because they are easier to measure and do not require complex pedagogical theory. However, these surface measures are poor predictors of the multifaceted and context-dependent nature of the student experience.

Landers’ Theory of Gamified Learning and its Limitations

Landers’ Theory of Gamified Learning ($2014$) provides a framework describing scenarios where gamification supports learning, a concept known as gamified learning. This theory proposes that game attributes directly affect a student’s behaviour or attitude, which then affects how a student interacts with instructional content to achieve learning outcomes. In this mediation model, the aim of gamification is not to provide the instructional content itself (as serious games do) but to modify the learner’s state to improve the effectiveness of pre-existing instruction. This perspective is supported by Skinner ($1984$) and others who relate gamification to behaviour change.

However, Landers’ theory is limited as it does not define ‘behaviour and attitudes’ according to specific pedagogic theories and fails to account for social, cognitive, and affective facets of engagement relevant to Higher Education. It also ignores wider consequences such as student satisfaction or wellbeing. Consequently, no comprehensive model currently exists that links game attributes to the broader experience of student engagement. The authors of the current framework aim to overcome this hurdle by systematically linking Landers’ work with Kahu’s Student Engagement Framework through the lens of social cognitive psychology.

Kahu’s Student Engagement Framework

Kahu ($2013$) identifies that the state of engagement is often conflated with its causes or effects, such as motivation or learning. Kahu’s framework resolves these conflations by separating the antecedents of engagement from the state itself. The behavioral perspective of engagement focuses on student behavior elicited by teaching practice but is limited because it ignores affect and dynamic complexity. In contrast, the psychological view incorporates behavioral, cognitive, and affective dimensions, which are shared with popular models of attitude in social psychology, as noted by Jain ($2014$).

Kahu’s overarching framework synthesizes elements into three main areas: antecedents (influences), the state of engagement, and consequences (outcomes). For example, motivation is categorized as an antecedent rather than engagement itself; it is a facet of the cognitive dimension that also includes self-regulation and self-efficacy. Engagement is conceptualized as a complex variable psychological state comprising affect, cognition, and behavior. The structural and psychosocial influences of the university and the student serve as antecedents, while proximal consequences include learning, achievement, wellbeing, and satisfaction. Mapping the antecedents of engagement onto categories of game attributes (such as assessment and curriculum) allows gamification to be viewed as a tool that modifies these influences.

Bedwell’s Taxonomy and Bloom’s Taxonomy of Educational Objectives

To bridge gamification and learning outcomes, the framework utilizes Bedwell’s taxonomy, which defines $19$ game attributes organized into $9$ distinct categories. These categories are mapped against training outcomes and cover all three domains of learning: cognitive, affective, and psychomotor. The categories include Assessment, Conflict/Challenge, Control, Game Fiction, Human Interaction, Immersion, Action Language, Rules/Goals, and Environment. The use of Bloom’s Taxonomy (Bloom $1956$; Krathwohl $2002$), which includes levels such as Remembering, Understanding, Application, Analysis, Organisation, and Synthesis/Evaluation, facilitates the application of Bedwell’s taxonomy in the HE setting.

Table $1$ in the study maps these taxonomies, indicating varying levels of evidence for links between game attributes and specific learning levels. For instance, the 'Assessment' attribute shows strong evidence ($++$) for 'Remembering/Understanding' and 'Application' levels. 'Conflict/Challenge' demonstrates evidence for every cognitive level as well as motivation. 'Game Fiction' is linked to 'Analysis/Organisation' and 'Synthesis/Evaluation.' This mapping provides a point of connection between Kahu’s engagement framework and specific educational objectives through shared cognitive and affective domains.

The Gamification for Student Engagement Framework Results and Propositions

The synthesis of Landers’ and Kahu’s work results in the Gamification for Student Engagement Framework, which is built upon four testable propositions. Proposition ($1$) states that gamification is a process through which student engagement states—not solely behaviours and attitudes—can be modified to support learning outcomes. Proposition ($2$) asserts that the achievement of learning outcomes is a measurable consequence of the state of student engagement across affective, cognitive, and behavioural domains. Proposition ($3$) claims it is possible to select game attributes appropriate to support specific learning objectives across the cognitive, affective, and psychomotor domains. Finally, Proposition ($4$) suggests it is possible to select a game attribute for a gamification strategy by identifying the psychological domain shared between the learning outcome and the desired student experience of engagement.

A practitioner wishing to follow this framework would follow a series of steps: ($1$) Review the mapping table to identify an appropriate game attribute, such as using 'Human Interaction' for analysis and organisation; ($2$) Identify an enabling engagement state from the same domain, such as 'deep learning' (cognitive) for a knowledge organisation outcome; ($3$) Consider how the relationship between that state and an antecedent (like self-efficacy) can be supported by the attribute; and ($4$) Implement the attribute into the course through a task designed to affect that antecedent. This enables the purposeful selection of attributes based on desired student experiences.

Discussion on Implementation, Evaluation, and Benefits

The framework allows for the scientific testing of specific game attributes. Researchers can ask questions such as: ‘What is the effect of game attribute $A$ (e.g., Human Interaction) on engagement state $B$?’ or ‘Does game attribute $X$ support learning outcome $Y$ (e.g., Knowledge Organisation)?’ This systematic approach moves beyond the common reliance on ‘assessment’ attributes like points, badges, and leaderboards, which Dichev and Dicheva ($2017$) found to be the most used elements due to their ease of implementation. By utilizing the framework, practitioners can explore underinvestigated attributes like ‘Action Language,’ ‘Environment,’ and ‘Human Interaction.’

Broadening the scope beyond academic learning, the framework can evaluate other consequences of engagement, such as student wellbeing and satisfaction, using instruments like the PERMA framework (Kern et al., $2015$). While the framework is grounded in social cognitive psychology, the authors acknowledge this is not the only valid approach. They extend Landers’ mediation model to encompass cognitive and affective domains and expand the outcomes to include social consequences. Although Bloom’s taxonomy historically neglected behavioural components, psychomotor skills can be reframed as sets of behaviours to facilitate research into that area.

Practitioners’ Reflective Cycle and Adoption Barriers

Barriers to adopting the framework may include its perceived complexity or novelty. However, the authors argue that practitioners gamify naturally over time as part of a diffuse, reflective process. This journey often begins with cognitive dissonance, where a time-tested lesson design fails to produce the expected quality of learning. Experimental practitioners then iteratively modify their designs. Reframing gamification as a natural outcome of this reflective cycle may aid widespread adoption. The framework provides the structure to articulate and systematize these observations and evaluations.

The types of game attributes and their embedding in the experience significantly influence outcomes. For instance, the ‘lusory attitude’—the playfulness and immersion achieved by game-like experiences—may impact engagement. Motivation is context-dependent and varies among individual learners, which aligns with Kahu’s multifaceted view of engagement. Ultimately, the framework aims to provide a toolkit of purposefully applicable game attributes for any educational scenario targeting improved engagement and learning.

Ethical Considerations in Gamification

Gamification has distinct ethical limits. There is a risk that changing the context of an experience can obscure the true nature of a task, potentially invalidating participant consent (Kim and Werbach $2016$). When game attributes are used in mandatory, invasive, or exploitative contexts, gamification becomes a tool for decreasing resistance rather than supporting learning. The authors recommend preliminary application of the framework to non-mandatory parts of a course.

Gamification becomes unethical the moment game attributes are added to deceive, coerce, or mollify participants. Therefore, any attempt to gamify a task must include ethical checks. These checks should ensure the purpose and methods of gamification are transparent and available to participants. The authors anticipate that existing institutional quality frameworks may be modified to incorporate these ethical safeguards, with the Gamification for Student Engagement Framework providing a method to articulate the process clearly.