E-Publication Assignment2

ACKNOWLEDGEMENTS I wish to express my heartfelt gratitude to my advisor, Ms. Aslina Baharum for her extensive revisions suggestions throughout the entire process including that of developing the outline and drafting the final manuscript which was assisted by her expertise and high level of professionalism in higher education. Thanks to everyone who participated in this project by completing the questionnaire since it would not have been possible without their responses. To my family and friends who supported me during the difficult times, I truly appreciate your help. ABSTRACT While there has been a tremendous growth in the use of digital education, there are ongoing difficulties related to maintaining learner motivation over time. Existing research on gamification focuses predominantly on approaches based on external rewards including points, badges, and leaderboards. In comparison, the use of deep aesthetic and narrative aspects of entertainment design has been explored very little. The main goals of the study presented here are to investigate the ways in which three categories of entertainment design (aesthetic design, character design, and gamified interaction) influence learner motivation and how these elements may be combined without interfering with educational goals. A quantitative descriptive design was employed, with data collected from 65 adult learners aged 18 to 35 via a structured online questionnaire combining 5-point Likert-scale items with optional open-ended responses; participants were categorised by self-reported personality tendency into extroverted, introverted, and ambivert groups to examine whether psychological disposition modulates responses to specific design elements. Results showed that aesthetic personalisation produced the strongest overall motivational effect, with matched-preference respondents scoring above 4.5; character design was especially valued by introverted learners (M = 3.95) compared to extroverted learners (M = 3.65); extroverted participants responded most strongly to immediate interactive feedback (M = 4.30); and ambivert respondents showed the greatest preference for multiplayer cooperative features (M = 4.08). Qualitative responses indicated that entertainment elements were most valuable when functionally purposeful rather than decorative. Based on these findings, three design integration principles are proposed: functional embedding, personality-responsiveness, and narrative continuity. This study extends the gamification literature beyond extrinsic mechanics, offering an empirically grounded framework for designing digital learning environments that are both pedagogically effective and genuinely engaging. Keywords: gamification, entertainment design, learner motivation, digital education, personality traits 1

TABLE OF CONTENTS 1 1 4 4 4 5 5 5 6 6 6 7 7 7 8 8 9 9 10 10 11 11 12 13 13 13 15 15 15 16 17 18 19 Acknowledgements Abstract 1.0 Introduction 1.1 Background 1.2 Problem Statement 1.3 Research Objectives 1.4 Research Questions 1.5 Scope 1.5.1 Target Audience 1.5.2 Research Scope 1.6 Summary 2.0 Literature Review 2.1 Overview 2.2 Motivational Frameworks in Digital Learning 2.3 Gamification in Digital Education: Benefits and Limitations 2.4 Entertainment Design Elements: Visual Aesthetics, Character Design, and Narrative 2.5 Research Gap 2.6 Summary 3.0 Methodology 3.1 Overview 3.2 Data Collection 3.2.1 Participants and Sampling 3.2.2 Instrument 3.2.3 Procedure 3.3 Data Analysis 3.4 Summary 4.0 Implementation 4.1 Overview 4.2 Findings from Objective 1 — Impact of Entertainment Design on Motivation 4.3 Findings from Objective 2 — Entertainment Design Elements That Sustain Long-Term Engagement 4.4 Findings from Objective 3 — Balancing Educational and Entertainment Elements 4.5 Summary 5.0 Conclusion E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 2

19 19 20 22 24 24 24 5.1 Research Summary 5.2 Research Contribution 5.3 Limitations and Future Works References Appendices Appendix A: Survey Questionnaire Appendix B: Survey Response Data E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 3

1.1 Background In the last 10 years, knowledge acquisition has drastically been changed over the internet. The older model was that taking a course meant sitting in a classroom at a certain time and buying your way onto the course. All you have to do is open a laptop and start learning now. This change was accelerated by the COVID-19 Pandemic which made campuses turn to entirely online teaching. Used to be, it was just temporary. Even some online courses or 100 percent online programs have opened in universes around the globe, an illustration of a half and half course (Zeng et al, 2024). Even with widely available educational content, student learning is sometimes less effective. In reality, who would blame them; online learners are not being focused Non-academic reasons such as social media and family activities are also potential distraction for the students to develop their motivation, (Pan, 2023). Moreover, the existence of professor and classmates in-person triggers performance. There is no such social pressure online. In part this can be attributed to the very design of many platforms. Most are not particularly interactive—they just show videos and texts. This results in students becoming isolated and disengaged with a detrimental effect on their academic achievement (Pan 2023). So the issue is not that you don’t have all the information, but a lack of involvement from students to fully internalize it. This is where many teachers are looking to utilize gamification or the use of game elements in learning. The theory being is that if it is more interactive and story based learning, the kids will be more engaged. Some research supports this hypothesis. Zeng et al. Well designed gamification has proven to increase student motivation and well-being by satisfying students need) (2024). But not all gamification works. Simply introducing a leaderboard without relating it to learning objectives causes anxiety and demotivation among learners. So, it is not sufficient just to add game elements — it must be executed prudently. 1.2 Problem Statement When I observe how gamification is generally implemented in digital education, a trend emerges. Most tools are still designed like traditional courses, with game features simply added on top. This is what Cheng and Wang (2021) point out: many game-based systems are really just rebranded teaching methods. They often neglect the elements that make games truly fun, such as engaging stories, interesting characters, and appealing graphics. As a1 C H A P T E R 1 . 0 Introduction1.1 Background1.2 Problem Statement1.3 Research Objectives1.4 Research Questions1.5 Scope1.6 Summary 4

result, students may focus more on collecting points or badges than on the actual learning. This problem was also noted by Christopoulos and Mystakidis (2023) and by Jiang and Shangguan (2022). Another problem is that, even if gamification works initially, the enthusiasm doesn't last. Ratinho and Martins (2023) explain how students may be captivated by game mechanics at first, but after a while, they become accustomed to them and lose interest. Most studies have focused on external rewards such as points and badges, but little research has been conducted on the role of narrative and aesthetics in maintaining student engagement. Only very recently have some researchers (Rodrigues et al., 2022) begun to suggest that a more creative and collaborative design might prove more effective in the long run. These two problems demonstrate that the gamification of education needs further exploration. If we do not use the emotional and narrative tools that have always proven successful in entertainment to captivate learners, we will only get a slightly different version of the same old online courses. 1.3 Research Objectives To explore how elements such as visual storytelling, character design, and interactive features influence student motivation in online learning environments. To determine which game design features are most effective at maintaining learner interest over the long term. To propose practical solutions for effectively integrating educational content and game elements into gamified learning systems. 1.4 Research Questions How do visual storytelling, character design, and interactive features influence student motivation in online learning? What design features are most effective at maintaining student engagement and preventing disengagement over time? How can the right balance be struck between learning objectives and game elements when designing gamified platforms? 1.5 Scope This study focuses on adult learners aged 18 to 35 who have used digital platforms such as Coursera or MOOCs. This age group is important because it represents the main user base of these platforms, but also a significant proportion of learners who drop out. The figures are E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 5

quite surprising. Borrella (2023) indicates that MOOC completion rates are often below 10%, and sometimes even below 5%. Researchers in education and information technology (2025) have also found that motivation varies according to the learner's age and experience; this group is therefore a relevant target for our research. Furthermore, having grown up with video games, people in this age group are likely more receptive to learning experiences inspired by video game culture. 1.5.1 Target Audience We will examine three specific design elements: visual aesthetics, character design, and interaction mechanisms. We are interested in their impact on learner motivation, engagement, and burnout. Loyola (2025) argues that successful game aesthetics not only capture attention but also encourage players to return, and that the visual and emotional aspects of design can foster deeper understanding. Jafarkhani (2024) shares this view, stating that stimulating learning environments give meaning to choices and provide students with a sense of progress. 1.5.2 Research Scope This study will not address institutional support, material requirements, or students outside the 18-35 age range. We wish to limit its scope to ensure accurate results. 1.6 Summary Online learning has experienced rapid growth, but maintaining student motivation throughout their training remains a major challenge. Most gamification tools rely on simple rewards like points and badges, neglecting the stories, characters, and visual appeal that make entertainment so engaging. Students often get bored, and making learning fun is difficult. This study aims to address this gap by exploring how game design can be used in digital learning to maintain motivation, reduce mental fatigue, and create a satisfying learning experience that is both educational and enjoyable. I am convinced that we shouldn't have to choose between the two. E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 6

2.1 Overview This chapter discusses scientific studies related to the three research questions of this research: how game design techniques affect learner motivation; what elements are most effective in sustaining learner engagement; and how to reconcile educational and game-like goals in the design of gamified digital learning experiences. The review is based on empirical evidence, systematic reviews and meta-analyses published between the years of 2019-2025. The literature review is organized according to themes of motivation theory, gamification practice, elements of game design and challenges associated with sustaining learner engagement. 2.2 Motivational Frameworks in Digital Learning Since game design is still an under-theorised part of gamification practice, it makes sense to critically interrogate what existing motivational frameworks can tell us and their shortcomings. Most gamification research appears to be based on self-determination theory (SDT), which argues that intrinsic motivation stems from the satisfaction of three basic psychological needs: autonomy, competence, and relatedness (Deci & Ryan, 2000). Meta- analysis from Zeng et al., published in the British Journal of Educational Technology (2024), found that gamification has generally beneficial effects on skill development and social connectivity—two of three core needs—but left open the hotly contested question of whether or how good gamification can sustainably nurture intrinsic motivation, at least in its deep sense. A framework with some similarities can be found in Csikszentmihalyi's flow theory (1990), which relates staying engrossed on the long-term to a balance between challenge and competence. The positive affect which grants access to the flow state is enabled by aesthetic aspects—colour, animation, character expressiveness (Plass et al., 2022). Yet self-determination theory (SDT) and flow theory fail to provide a satisfactory account of how the aesthetic or narrative dimensions of design influence motivation independently from its interactive characteristics over longer periods of time, an area that we elaborate further in the following section.2 C H A P T E R 2 . 0 Literature Review2.1 Overview2.2 Motivational Frameworks in Digital Learning2.3 Gamification in Digital Education: Benefits and Limitations2.4 Entertainment Design Elements: Visual Aesthetics, Character Design, and Narrative2.5 Research Gap2.6 Summary 7

2.3 Gamification in Digital Education: Benefits and Limitations Gamification—the integration of game design elements into non-game contexts (Deterding et al., 2011)—is widespread in digital education, most often in the form of points, badges, and leaderboards, frequently abbreviated as PBL. A PRISMA-guided systematic review by Ratinho and Martins (2023) of 40 studies selected from 548 articles published in Heliyon found a generally positive short-term effect on student motivation. A meta-analysis by Zeng et al. (2024), published in the British Journal of Educational Technology, reached broadly similar conclusions after examining 15 years of empirical data. However, this overall positive finding contrasts with a body of equally compelling evidence to the contrary. Hanus and Fox (2015), in a frequently cited longitudinal study, found that introducing badges, leaderboards, and coins into a university course actually reduced student motivation and satisfaction compared to a control group that received no gamification. A 2024 meta-analysis published in Educational Technology Research and Development reached a similar conclusion, acknowledging that the question of whether gamification truly enhances intrinsic motivation remains unanswered. Methodological issues compound this uncertainty: many studies rely on short-term self-reported data and lack the consistency necessary for meaningful comparisons (Ratinho & Martins, 2023). More fundamentally, the problem-based learning model that dominates current practice focuses only on the extrinsic surface of game design, neglecting the aesthetic, emotional, and narrative dimensions—the elements that give entertainment its true enduring appeal. 2.4 Entertainment Design Elements: Visual Aesthetics, Character Design, and Narrative A smaller but rapidly expanding field of research is increasingly focusing on the playful dimension of learning. Studies on emotional design in multimedia learning demonstrate that visual characteristics—warm colour palettes, anthropomorphic shapes, expressive forms— can generate positive emotional states that enhance cognitive engagement and improve learning outcomes, particularly when task difficulty remains moderate (Plass et al., 2014; PMC, 2025). A study published via ScienceDirect (2024) also identified graphic qualities such as 2D/3D visual balance and compositional harmony as key factors in knowledge-related emotional responses, including curiosity and interest. More specifically, about Character design, an article writes by Fink et al.(2024) that published in Frontiers in Education, demonstrates that AI-based avatars can foster experience of immersive and personalized, and still proven motivational effects. However, the field still continues to view characters much as functional pedagogical agents tools for conveying contents, rather than as thoughtfully designed aesthetic presences. The gap between how the entertainment industry conceives of characters and how educational research is large . Of the three arguments put forward, the one concerning the role of narrative is perhaps the most compelling. A study by PMC (2022) demonstrated that integrating fantasy and narrative E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 8

elements into a gamified online course reversed a decline in engagement observed over eight weeks, while also significantly boosting peer interaction and learning performance. Rodrigues et al. (2022), drawing on a 14-week longitudinal study, also found that fictional and collaborative gamification elements helped learners resist the novelty effect over time, thus positioning narrative not as a mere ornament, but as a structurally more durable motivational mechanism than extrinsic rewards alone. 2.5 Research Gap What the literature as a whole establishes is that conventional gamification produces measurable but limited motivational effects, often fleeting and sometimes even counterproductive. Recent data suggest that visual aesthetics, character design, and storytelling offer more affectively sustainable alternatives. Yet, these elements remain largely unexplored empirically: studied briefly and in isolation, rather than as components of integrated entertainment design systems. The question of a productive balance between pedagogical rigor and playful immersion is addressed theoretically in the literature but rarely tested empirically. This study fills this gap by examining how entertainment design techniques interact to maintain motivation in adult digital learning environments, thus bringing design-driven evidence to a field still largely preoccupied with extrinsic mechanisms and short-term measures. 2.6 Summary The traditional gamification will only boosts motivation for a short time which always fade (sometimes even reduce engagement). Recent research based on self-determination theory and immersion theory highlights visual aesthetics, character design and storytelling as an alternative that evokes emotion longer and creates positive emotional states without drops of engagement. These game design elements haven't been studied as a whole system yet. Our study fills that gap by examining how these techniques work together to maintain adult learners' motivation in digital learning environments. E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 9

3.1 Overview In this chapter we present our research protocol, data collection process, and analytical approach in this study. We used a quantitative descriptive methodology that allowed us to achieve our three research objectives by means of an online questionnaire with items scored using a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree); afterwards, we performed a descriptive statistical analysis over the obtained data. Our choice of quantitative method is based on the fact that it enables measuring systematically within a given population; furthermore, it allows reproducible statistical comparisons. Adding a segmentation of personality traits – distinguishing between extroverted, introverted, and ambiverted tendencies – adds a new differentiating aspect which is mostly missing in existing research about gamification (Creswell, 2014). In the rest of this chapter we detail how we selected the participants, constructed the instrument according to our three research objectives, described the data collection process, as well as analyzed them. Figure 1. Research design and analysis flow across the three research objectives.3 C H A P T E R 3 . 0 Methodology3.1 Overview3.2 Data Collection3.3 Data Analysis3.4 Summary 10

3.2 Data Collection 3.2.1 Participants and Sampling Figure 2. Participant sampling and data collection procedure. The target population consisted of adult learners aged 18 to 35 who had previously used platforms such as Coursera or MOOCs – this demographic group was chosen because it represents the main category of self-directed online learners and is also the most familiar with the aesthetics of video games. A convenience sampling approach based on voluntary participation was used; the questionnaire was distributed via social media and email, with initial screening questions confirming that all respondents had prior experience with digital learning. Of the expected 100 to 300 respondents, 65 valid responses were obtained – an insufficient number acknowledged as a limitation in Chapter 5. The most represented age group was 18– 24 (n = 35), followed by those under 18 (n = 16) and 25–29 (n = 14). For the purposes of objective 2, these 65 respondents were segmented into three groups according to their self- reported personality tendency: extroverts (n = 24), introverts (n = 21), and ambiverts (n = 20). This segmentation was incorporated into the first part of the questionnaire precisely to determine whether different psychological dispositions produce differentiated responses to specific design elements—a dimension that the gamification literature has largely overlooked. 65 VALID RESPONDENTS 24 / 21 / 20 EXTROVERT / INTROVERT / AMBIVERT 18–24 LARGEST AGE BAND (N=35) E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 11

3.2.2 Instrument Data collection was conducted using a structured online questionnaire organized into three parts. The first part (General Information) collected demographic data regarding age, frequency of digital learning, platform experience, and a self-assessment of personality tendencies. This last variable was deliberately included to test whether different psychological orientations lead to significantly different responses to the design elements of entertainment content. The second part (Perception Scale of Design Elements) formed the core of the measurement instrument and covered three dimensions divided into three subscales (A, B, and C), detailed below. The third part (Open Comments) offered respondents the opportunity to elaborate on their design preferences. These responses were not formally analyzed but helped to contextualize and enrich the trends observed in the quantitative data. Participation was entirely voluntary and anonymous. A. Objective 1 — Entertainment Design and Motivation Subscale A comprised three questions with Likert-type response options measuring perceptions of the visual aesthetics and character design: Does the appropriateness of the interface style to personal aesthetic preferences increase motivation to use it? Does making a virtual character feel less sad and frustrated create a sense of camaraderie? (Q2): Does the character with defined personality/story return a positive adherence to lesson pace? For example, a fifth (Q3) multiple choice question asked participants which virtual tutor style they preferred from four different options: cute, professional, humorous or serious (Q4). Subscale B centered on playful interaction: the perceived values of rankings, points, and badges (Q5); immediate feedback mechanisms like animations and sound effects (Q6); perceived autonomy in the task as compared to one-way instruction (Q7); and motivation to engage with competitive or cooperative multiplayer elements of play (Q8). And underestimation of the repetition and diligence required to master tasks (Q9). B. Objective 2 — Design Components for Ongoing Engagement For Objective 2, focused items from subscales A and B were chosen based on their connection to long-term engagement: the companionship function of virtual characters (Q2), the compelling role of characters featuring personalities or backstories (Q3), perceptions associated with durability for gamification elements such as leaderboards and badges (Q5), interactive feedback in real time (Q6), self-reported willingness to interact with other learners via competition or cooperation (Q8) and persistence against mastery through repeated attempts at a task (Q9). Instead of introducing new items, we explored existing practised designs from a new angle by analysing their relationships with personality and so not only initial appeal but also the extent to which a given design feature supports sustained motivation in repeated learning interactions for different learner types; as described in 3.2.1. C. Objective 3 — Balancing Educational and Entertainment Elements To address the issue of balance, subscale C focused on background music and sound effects in relation to concentration (Q10), user interface quality in relation to learning fatigue (Q11), and interface speed and fluidity in relation to overall system appreciation (Q12). Together with subscales A and B, these items allowed us to map the relative perception of different E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 12

entertainment design categories and identify the points of tension most likely to arise between playful immersion and the educational objective. The open-ended responses in Part 3 served to contextualize and enrich the quantitative trends emerging from this comparison, particularly regarding the perceived balance between playful value and learning effectiveness. 3.2.3 Procedure The questionnaire was distributed online via social media and email. At the start of the survey, screening questions confirmed that respondents had prior experience with digital learning platforms. Participation was voluntary, and respondents were not required to provide their names; no personally identifiable information was collected. Participants completed all three parts of the questionnaire in a single session, with Part 3 (the open- ended questions) remaining optional. 3.3 Data Analysis Statistical analysis was used to examine the three research objectives. For Objective 1, the mean score for each item on the Likert scale for subscales A and B was calculated. Participants' responses were then compared to identify the visual design and interaction elements most strongly associated with accumulated motivation for learning. For Objective 2, responses were compared across the three personality groups, with mean scores calculated for each group on each item to highlight significant differences between extroverted, introverted, and ambivert learners, with the goal of determining the design elements best suited to all learner types. For Objective 3, mean scores across subscales A, B, and C were compared to identify the game design categories with the highest overall scores and the areas where the game experience and learning effectiveness diverged most. The open-ended responses from Part 3 were analyzed to enrich these comparisons. The principal findings of this analysis were as follows: respondents who scored above 4.5 on the appearance-customisation items reported markedly higher motivation; introverted respondents reported greater enjoyment of virtual character companionship than extroverted respondents (3.95 vs. 3.65); extroverted respondents were primarily motivated by immediate feedback (4.30); and ambivert respondents were primarily motivated by cooperative multiplayer features (4.08). 3.4 Summary In this chapter we described our research plan, study population, research design and analytical approach used. We collected data via a three-part online questionnaire that was subsequently broken down and compared with descriptive statistics. Our questionnaire aimed at addressing all three research objectives consistently and comparably; the segmentation of participants based on their personality trait is also an analytical angle not E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 13

present in existing gamification research. Results of this approach will be presented in Chapter 4. E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 14

4.1 Overview This chapter presents the results of a study conducted with 65 participants who completed a structured questionnaire. The study addressed three research objectives, and each section below opens with the relevant mean scores and between-group comparisons before discussing their significance in relation to the theoretical framework and prior studies reviewed in Chapter 2. The results provide the empirical grounding needed to support the design strategies proposed in this chapter and elaborated further in Chapter 5. 4.2 Findings from Objective 1 — Impact of Entertainment Design on Motivation Objective 1 sought to determine how entertainment design techniques—visual aesthetics, character design, and gamified interaction—influence learner motivation in digital education. 4.5+ Q1 AESTHETIC FIT 4.10 Q6 INSTANT FEEDBACK 3.55 Q5 RANKINGS/BADGES The mean scores for Subscale A in Part 2 were as follows. Question 1 (the appropriateness of the interface style to the participant's personal aesthetic preferences) received an average score above 4.5, the highest score on Subscale A. Question 2 (the perceived helpfulness of virtual characters) received a mean score of 3.80. Question 3 (the character's personality and backstory, and the extent to which participants would want to follow its story) received a mean score of 3.75. For Question 4, the most common preferences for virtual tutor style were "cute" and "professional". Within Subscale B, Question 6 (immediate feedback through animations and sound effects) received the highest overall mean score (4.10), ahead of Question 5 (rankings, points, badges; M = 3.55) and Question 7 (sense of task mastery; M = 3.60).4 C H A P T E R 4 . 0 Implementation4.1 Overview4.2 Findings from Objective 1 — Impact of Entertainment Design on Motivation4.3 Findings from Objective 2 — Entertainment Design Elements That Sustain Long-TermEngagement4.4 Findings from Objective 3 — Balancing Educational and Entertainment Elements4.5 Summary 15

Taken together, these results suggest that the ability to personalise appearance is the primary driver of motivation, and that interactive feedback substantially outperforms static elements such as rankings and badges. This finding aligns with prior work showing that warm colours, anthropomorphic shapes, and expressive features can improve wellbeing and concentration (Plass et al., 2014), and supports Loyola's (2025) argument that game design quality shapes the desire to continue learning. Character design's more moderate scores (Q2 and Q3 both in the high 3s, rather than exceeding 4.5 like Q1) suggest it functions as a secondary rather than primary motivational lever at the whole-sample level — though, as the Objective 2 findings below show, this picture changes considerably once personality is taken into account. At the aggregate level, however, respondents' qualitative comments still indicated a sense of companionship and emotional investment generated by expressive characters, an effect that existing educational research has largely missed, given its tendency to treat avatars as functional content- delivery agents rather than carefully crafted aesthetic presences (Fink et al., 2024). The Subscale B result on immediate feedback (Q6, M = 4.10) reinforces the Subscale A pattern: what appears to drive motivation is dynamic, responsive design rather than static reward accumulation. This aligns with Flow Theory's emphasis on real-time feedback as a key enabler of immersive engagement (Csikszentmihalyi, 1990), and suggests that the quality of interaction design matters more than the simple presence of game mechanics. Taken together, the Objective 1 findings indicate that entertainment design techniques exert a positive and measurable influence on learner motivation, with aesthetic personalisation and immediate interactive feedback emerging as the two strongest drivers among the elements tested. 4.3 Findings from Objective 2 — Entertainment Design Elements That Sustain Long-Term Engagement Objective 2 asked which entertainment design elements are most capable of sustaining engagement over time and guarding against the motivational decline that the literature associates with the novelty effect (Ratinho & Martins, 2023). 3.95 INTROVERTS — COMPANIONSHIP 4.30 EXTROVERTS — FEEDBACK 4.08 AMBIVERTS — CO-OP PLAY Group mean scores obtained from cross-tabulating Likert responses by personality group were as follows. On Q2 (character companionship), introverted respondents (n = 21) returned a mean of 3.95, compared with 3.65 among extroverted respondents (n = 24); ambivert respondents (n = 20) scored 3.78, placing them between the two groups. On Q6 (immediate interactive feedback), extroverted respondents scored highest at 4.30, compared with 3.70 among introverted respondents and 3.90 among ambiverts. On Q8 (multiplayer/cooperative E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 16

features), ambivert respondents scored highest at 4.08, compared with 3.60 among introverted respondents and 3.95 among extroverted respondents. Beyond these explicit figures, an implicit pattern emerges when the three results are read side by side: each personality group's highest-scoring item is a different item entirely — introverts peak on companionship (Q2), extroverts peak on interactive feedback (Q6), and ambiverts peak on cooperative features (Q8). This is not something any single mean score shows on its own; it only becomes visible once the three group comparisons are set against each other, and it indicates that personality does not simply raise or lower overall enthusiasm for entertainment design — it redirects which specific design element each group responds to most. This differentiated result carries a significant implication for the novelty effect problem. Where extrinsic mechanics — points, badges — produce initial engagement followed by decline (Ratinho & Martins, 2023; Hanus & Fox, 2015), the explicit data above suggest that aesthetic and narrative elements operate through more personalised motivational pathways, which may prove more durable precisely because they are better matched to individual learner characteristics. Where character design is sustained as a narrative presence rather than deployed as a one-time aesthetic feature, it appears — per the Q2 data — to offer a particularly effective retention strategy for introverted learners specifically, who are often considered most vulnerable to disengagement in impersonal online environments. This reading is consistent with Rodrigues et al.'s (2022) finding that fictional and collaborative elements helped sustain motivation across a 14-week longitudinal study in ways that extrinsic rewards alone could not. 4.4 Findings from Objective 3 — Balancing Educational and Entertainment Elements Objective 3 addressed the question of how educational objectives and entertainment elements can be held in productive balance within gamified digital learning design. Comparative mean score analysis across the three Part 2 subscales produced the following pattern. Subscale A (visual aesthetics and character design) scored consistently across all personality groups, with no group falling below 3.6 on any item. Subscale B (gamified interaction mechanics) peaked among extroverted learners (Q6, M = 4.30) but showed the widest spread across groups. Subscale C (audio and UI experience) was rated most positively by introverted and ambivert respondents: Q10 (background music/concentration) returned M = 4.05 among introverts, and Q11 (UI layout/learning fatigue) returned M = 4.00 among ambiverts. No single subscale dominated overall ratings, and the distribution suggests that a balanced, multi-dimensional design approach is more likely to serve the diverse motivational profiles within a typical adult learner population than any strategy centred on a single element. Open-ended responses from Part 3 reinforced this reading. Respondents repeatedly described entertainment features as feeling most valuable when they were evidently E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 17

purposeful rather than decorative — when animations signalled genuine progress, when characters responded meaningfully to learner choices, when visual design felt coherent with learning content rather than ornamental to it. Several respondents also flagged that excessive or contextually irrelevant entertainment elements were distracting, echoing Christopoulos and Mystakidis's (2023) concern that poorly integrated gamification can shift learners' attention from learning objectives toward the game layer itself. Based directly on this balance data, three concrete design strategies are proposed for Objective 3: 4.5 Summary Across all three objectives, the findings confirm that entertainment design techniques — visual aesthetics, character design, gamified interaction, and narrative elements — exert a meaningful positive influence on learner motivation and engagement in digital education. Critically, the differentiated responses observed across personality groups indicate that motivation is not produced uniformly by any single design element; what matters is the degree to which the design environment aligns with the psychological characteristics of individual learners. The three design strategies proposed in this chapter — tiered aesthetic- to-content coupling, personality-gated interaction intensity, and ambient audio/UI calibration — offer a practical framework for translating these findings into actionable design decisions, as discussed further in Chapter 5. Tiered aesthetic-to-content coupling: Since Subscale A scored consistently high across all groups, visual and character elements should be treated as a universal baseline layer — applied throughout a course rather than reserved for special moments — but always tied to a specific piece of content or progress marker (e.g., a character's appearance changing as a module is completed), so that aesthetic investment doubles as a progress indicator rather than pure decoration. 1 Personality-gated interaction intensity: Because Subscale B showed the widest spread across personality groups, interactive/competitive mechanics (leaderboards, timed challenges) should be offered as an optional, togglable layer rather than a default — visible and prominent for extroverted learners, minimised or replaced with solo-paced alternatives for introverted learners, based on the personality data collected at onboarding. 2 Ambient audio/UI calibration for fatigue reduction: Since Subscale C scored highest specifically on fatigue-related items among introverted and ambivert respondents, background audio and interface pacing should be tunable by the learner (e.g., adjustable music intensity, simplified UI mode), positioned specifically as a fatigue-management tool rather than a purely aesthetic add-on. 3 E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 18

5.1 Research Summary This study examined how elements such as visual aesthetics, character design, and interactive game mechanics influence motivation and learning effectiveness in digital learning environments, and explored how these elements can be reconciled with educational objectives. The study was structured around three research objectives and the questions posed within them, employing a quantitative descriptive methodology involving data collected from 65 adult learners via an online questionnaire that included a 5-point Likert scale as well as optional open-ended questions. The results show that game design elements can increase motivation, but their effectiveness is highly dependent on individual personality. The option to customise character appearance (its "aesthetics") generated the strongest overall motivation, with respondents holding matched preferences assigning scores above 4.5 on average. Character design proved particularly important in motivating introverted individuals, while immediate feedback boosted the motivation of extroverted individuals, and both groups, together with ambiverts, especially appreciated cooperative features. Together, these findings suggest that a differentiated, personality-tailored design approach is preferable to a one-size-fits-all gamification strategy. A second recurring theme emerges from the data: effective game design is functional rather than merely decorative. Participants valued visual and interactive features more when these enhanced their learning, rather than when perceived as superficial additions to standard instruction. This connects to the central issue raised in Chapter 1: most game-based learning systems neglect the aesthetic and narrative aspects of game design in favour of relying solely on extrinsic reward mechanics to drive learner motivation. 5.2 Research Contribution The contribution of this study is not purely theoretical but also practical, suggesting concrete ways the findings can inform real-world design decisions — specifically regarding how to combine visual design with content, how much interactivity to offer, and how to calibrate audio and interface elements, as detailed in Chapter 4. Tiered aesthetic-to-content coupling offers course designers and platform developers a way to raise motivation for all learners, since personalisation of course appearance scored highly5 C H A P T E R 5 . 0 Conclusion5.1 Research Summary5.2 Research Contribution5.3 Limitations and Future Works 19

regardless of personality type. This strategy would be especially useful for instructional designers and EdTech product teams building general-purpose platforms who need a design layer that works well across users without requiring per-user customisation. Personality-gated interaction intensity allows platforms to serve both extroverted and introverted learners by adjusting interaction intensity according to personality-based preferences. This would be especially useful for developers of adaptive learning platforms and UX designers working on systems that already collect learner profile data, as well as for corporate training providers and MOOC platforms managing large, diverse learner bases who may find that a one-size-fits-all gamification layer risks disengaging a significant proportion of users. Ambient audio/UI calibration can reduce fatigue-related dropout, which is valuable for accessibility-focused designers and course platform teams, particularly given that introverted and ambivert learners were shown in Chapter 4 to be most sensitive to this issue. It also offers a lower-cost entry point for smaller EdTech teams or independent course creators who may lack the resources to build character-driven narrative systems but can implement adjustable audio and UI settings relatively inexpensively. Beyond these three strategies, this study contributes to the gamification literature by treating visual design, character design, and interactive feedback as distinct motivational levers rather than a single undifferentiated "gamification" construct, and by introducing personality traits as an additional analytical dimension that has received little prior attention. This provides a foundation for designing learning environments that can adapt to individual learner needs. 5.3 Limitations and Future Works This study has several important limitations. The 65 participants recruited fall short of the 100 to 300 respondents that would have been required for more reliable results, meaning the findings cannot be confidently generalised to the broader population of adult digital learners. Recruitment via social media and email may also have introduced a self-selection bias, potentially skewing responses more positively than would be found through in-person recruitment. The cross-sectional design is a further limitation: because all responses were collected at a single point in time, the study cannot directly track how motivation changes as learners interact repeatedly with an entertainment-designed learning environment. While the literature lends support to the durability of the effects observed here, this cannot be confirmed by the present dataset alone. The reliance on self-report measures is an additional limitation, since participants' stated preferences may not fully reflect their actual behaviour. Finally, the uneven uptake of the Part 3 open-ended option left the qualitative data thinner than would have been ideal for enriching the Objective 3 analysis. Future research could address these limitations in several ways. Longitudinal studies tracking motivation and engagement over repeated interactions with an entertainment- E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 20

designed platform would provide direct evidence regarding the durability of the effects observed here. A larger and more demographically diverse sample would strengthen the generalisability of the findings. Combining self-report data with other methods — such as behavioural observation, interaction analytics, or structured interviews — would offer a more detailed and ecologically valid picture of how entertainment design elements function in real learning contexts. Experimental designs comparing entertainment-based learning, conventional gamified learning, and non-gamified learning would further clarify the underlying mechanisms driving learner motivation. E N T E R T A I N M E N T D E S I G N & L E A R N I N G M O T I V A T I O N D I S 6 0 3 0 4 21

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Appendix A: Survey Questionnaire The questionnaire used in this study was administered online via Google Forms. The full questionnaire, including all items across Parts 1, 2, and 3, can be accessed at the following link: https://docs.google.com/forms/d/ 1n62vHAZxdVWP3lDI18GY7YSEGBZ4QA7IJJiOZICoBKE/edit Appendix B: Survey Response Data The raw response data collected from 65 participants throughout the data collection period are stored and accessible via the following link: https://drive.google.com/file/d/1nUFqqm-ZWL3FW4V3W5EVxs-CoUUDuqQr/view? usp=sharing A P P E N D I C E S Supporting Materials 24