BÁO CÁO TỐNG KẾTĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024 ANALYZING THE EFFECT OF GAMIFICATION ON LEARNING EFFECTIVENESS THROUGH APPLICATION
OVERVIEW
Necessity of the research
The evolution of technology began with hydraulic and steam-powered machines in the late 18th century, leading to the second technological revolution characterized by electric motors and mass production lines By 1969, the advent of computers and automation marked the emergence of the 4.0 technology era, where systems increasingly connect the real and virtual worlds This innovation highlights advancements in human intellectual capital, alongside a rise in mobile applications, heightened demand for Internet-enabled services, and the promising potential of 5G technology.
The demand for distance learning has surged, driven by geographical barriers, health issues, and significantly accelerated by the Covid-19 pandemic Even post-pandemic, the interest in online education remains strong As digital technology transforms various industries, the global online learning market is poised for significant growth, with a projected increase of 13.28% from 2022 to 2028, making it one of the fastest-growing sectors in education.
The rise of online learning has coincided with the emergence and growth of the gamification market, particularly in education As demand for gamified systems continues to increase, the global gamification market is projected to expand from 9.1 billion USD in 2020 to 30.7 billion USD by 2025, reflecting a compound annual growth rate (CAGR) of 27.4% In the educational sector, gamification is becoming increasingly prevalent.
"maturing” To date, education and research is the second most popular sector applying gamification solutions after the retail industry according to Fortune Business Insight.
Gamification is becoming a preferred method of learning, as evidenced by the rise of self-directed learning applications like Duolingo, Kahoot!, and Quizizz Duolingo, a language-learning app with over 500 million downloads, experienced a 67% increase in active users in Vietnam from January 2021 to January 2022 Kahoot!, valued at $5.7 billion, is utilized by 87% of top universities and 97% of Fortune 500 companies worldwide These platforms incorporate gamified elements to enhance student learning, resulting in improved attention, engagement, confidence, and satisfaction.
Recent research highlights the growing interest in gamification among scientists worldwide A study by Wirani et al (2022) revealed that elements of gamification, specifically Competitiveness and Enjoyment, significantly enhance the perceived usefulness of learning methods like Kahoot!, thereby encouraging continued use Additionally, Ayoung Suh et al (2016) demonstrated that game motivation can foster user engagement in prosocial behaviors These findings offer valuable insights for system designers and managers aiming to promote positive social actions, such as addressing social issues, environmental protection, and raising awareness on critical topics.
The increasing use of gamification in Vietnam's education sector aims to innovate learning, particularly among university students, as the adoption of electronic devices in lower education levels remains limited This research emphasizes self-directed learning, enabling students to set goals, evaluate their learning effectiveness, and make informed choices about their educational paths By incorporating gamification elements into program design, educators seek to enhance motivation and learning efficiency The study proposes utilizing the ARCS model (Keller, 1984) to optimize self-directed learning applications through gamification, addressing the current gap in research on its effectiveness in Vietnam Motivation is crucial for improving learning outcomes, and the ARCS model has gained traction in technology-enhanced learning environments This research aims to analyze gamification elements and their impact on learning dynamics through the ARCS model, providing valuable insights for educators and application designers to enhance learner efficiency and contribute to the advancement of modern education quality.
Objectives
General objective: Analyze the effect of gamification factors on student learning effectiveness.
- Measure the effect of gamification factors used in applications for self-directed learning on the learning effectiveness of university students in Vietnam.
- Measure the effect of gamification factors used in self-directed learning applications on ARCS elements.
- Examining the mediating role of ARCS elements on university students' learning performance through Gamification.
- Based on the research results, some recommendations are made for educators and application programmers for self-directed learning to use Gamification effectively to improve students' learning effectiveness, student.
Gamification factors in applications for self-directed learning significantly influence the learning performance of university students in Vietnam These elements enhance engagement, motivation, and retention, leading to improved learning outcomes Understanding the extent of their impact is crucial for optimizing educational tools and strategies.
- How do ARCS elements affect learning effectiveness with the mediating role in gamified environments?
- Based on the research results, what recommendations can we make to help enhance the learning effectiveness of students in Vietnam through ARCuS factors?
Research Subject and Scope of the research
- Research Subject: The effect of gamification factors on students' learning effectiveness.
- Respondents: Students using applications for self-directed learning that contain gamification factors.
- Regarding the geographical range: This study only investigates those who are studying in Ho Chi Minh City.
- Execution time: This study is conducted from November to February 2023 - 2024.
Research Methodology
Qualitative research was conducted to refine the research model and develop a questionnaire focused on gamification factors that influence learning effectiveness This process involved a focus group discussion with ten university students who had experience using self-directed learning applications that incorporate gamification elements Their feedback played a crucial role in enhancing the questionnaire.
Quantitative research was conducted by collecting data through an online survey targeting college students in the Ho Chi Minh City area to validate research models and hypotheses The survey data was filtered using Excel, while data encryption and processing were carried out with SPSS and Smart PLS software The PLS-SEM tool was employed to verify the models and hypotheses, alongside tools for evaluating the measurement scale, including Cronbach's Alpha, Combined Reliability (CR), and Average Error.
Research Applications
This study explores the influence of gaming elements on learning effectiveness, specifically through the ARCS model factors: attention, relevance, confidence, and satisfaction Unlike previous research (Wirani et al., 2022; Aparicio et al., 2018) that primarily focused on the intention to continue using apps, this research targets the specific gaming factors affecting students at universities in Ho Chi Minh City.
The study evaluates the effectiveness of gamification factors on student learning outcomes, aiming to inform strategies for designing learner-centric educational applications By focusing on enhancing engagement, connectivity, confidence, and satisfaction, the findings will provide valuable insights for educators and application designers Ultimately, this research seeks to foster the development of practical applications that enhance modern education quality and improve learning efficiency for students.
Research Structure
The authors present the necessity of the topic, the research objectives, the research subjects and scope, as well as the preliminary research methods and significance of the study.
Chapter 2: Theoretical framework and research model
The authors explore various concepts and theories pertaining to the topic while analyzing relevant research They develop a research model aimed at examining the impact of gamification elements on learning effectiveness, utilizing the ARCS motivation model as a framework.
The authors present the research process, methods of sample selection and collection, qualitative research, scale calibration and quantitative research.
Chapter 4: Research Results and Discussion
The authors present the research results after collecting data and conducting analysis, testing the measurement model and structural model.
The authors present conclusions and recommendations to serve groups of subjects who aim to improve learning effectiveness through gamified environments and limitations of the topic.
THEORETICAL FRAMEWORK AND RESEARCH MODEL
Concepts
Gamification is the integration of game elements into non-game environments to enhance user experience and engagement, as defined by Deterding et al (2011) It draws on the motivational qualities of games, which are known to be engaging, inspiring, and enjoyable (Bozkurt and Durak, 2018; Songer and Miyata, 2014) Unlike simply turning activities into games, gamification focuses on applying the principles of motivation derived from games to improve learners' motivation, attitudes, and performance Research shows that using game-inspired designs in educational activities can boost student engagement and learning outcomes (Denny, 2013; Dominguez et al., 2013) Common gamification elements include levels, points, badges, leaderboards, and avatars, which encourage goal orientation, persistence, collaboration, and friendly competition among learners (Zamzami Zainuddin et al., 2020; Ding, 2019) The role of competition, enjoyment, and rewards in gamification is further supported by studies such as those by Ayoung Suh et al (2016) and Wirani et al.
(2022) from then evaluate and comment on the effect on learning effectiveness through the elements in the ARCS motivational design model.
Gamification in education involves incorporating game mechanics like points, badges, and leaderboards to enhance learning experiences by clarifying task goals, providing clear feedback, and allowing for personal goal-setting By utilizing game-based mechanics, aesthetics, and thinking, gamification effectively engages learners, motivates them to take action, and fosters problem-solving skills (Zichermann and Cunningham, 2011) This approach not only boosts motivation and memory retention but also captures learners' attention and encourages active participation (Treiblmaier et al., 2018).
Table 1 Gamification factors caused by gamification features
Gamification factors Gamification features in Apps Description
Users earn reward points, levels, badges, and trophies as compensation for completing designated tasks, creating incentives to engage further These points serve as a key game element, motivating users to strive for additional rewards and enhancing their overall experience.
Rewards Levels create incentives that encourage users to try to improve their status by achieving predetermined goals or by achieving milestones in the curriculum.
Badges or trophies represent a person's valuable activities, thus encouraging people to strive for tangible rewards that demonstrate their achievements.
Competition points, levels, and leaderboards enable users to compare their performance and engage in friendly competition By striving to achieve higher scores in activities, users can ascend leaderboard rankings and earn additional badges, enhancing their overall experience.
Enjoyment Goals setting/ Objectives determine what the player must do to win the game and (Papadimitriou A , story/ visual/ give the player a sense of accomplishment and progress A goal is
Incorporating sound effects and assigning values to game outcomes enhances the learning experience by allowing players to achieve defined goals The construction of a mental image within a game world, populated by individual characters and objects, is further enriched by fixed narratives, cutscenes, in-game actions, dialogue, and voice-overs These elements can be integrated into educational settings to boost student enjoyment and engagement in tasks.
Learner enjoyment increases with games that feature realistic graphics and sound effects 3D graphics, and lifelike animations.
Learning effectiveness is defined variably by researchers, with Panigrahi et al (2018) describing it as a measure of foundational learning activities Krath et al (2021) highlight that in the context of gamification, learning effectiveness reflects the impact of games on user outcomes, including engagement, enjoyment, and satisfaction Bureau et al (2021) further emphasize that it involves planning learning outcomes tailored to specific programs for evaluation purposes Ultimately, learning effectiveness is viewed as the ultimate goal of the educational process, with successful online learning platforms relying on achieving desired outcomes Understanding the factors influencing these outcomes is crucial, as different learning interventions can yield varying results (Panigrahi et al., 2018) Key factors, particularly motivation, have been identified to enhance learning outcomes In this study, learning effectiveness will be assessed through students' scores and achievements, focusing on their knowledge gains, attitudes, and behaviors when utilizing gamified applications and platforms.
The ARCS model, developed by John Keller, is a design framework for enhancing learning motivation, derived from a comprehensive review of motivation literature that categorizes motivation into four key areas Initially created for traditional classroom settings, the ARCS model is now applicable in online and computer-based learning environments It highlights essential aspects of human motivation, guiding the development of strategies to stimulate and sustain learner engagement This model not only aids in assessing student motivation but also empowers educators and instructional designers to refine their motivational strategies The four categories within the ARCS model play a crucial role in influencing learning motivation.
According to Keller (2010, pp 44—45), four categories in the ACRS model must be met for people to be motivated to learn:
(A) People's attention and interests should be stimulated and maintained.
(R) Before people can be motivated to learn, they will have to believe that instruction is related to important personal goals or motivations and feel connected to the environment.
Even when individuals find content relevant and are eager to learn, their motivation can be hindered by a lack of self-confidence or unrealistic expectations of success Established fears surrounding certain topics, skills, or situations may also impede their ability to fully engage in their studies.
Keller (2010, p 46) indicates that accomplishing these initial three motivational objectives (attention, relevance, and confidence) leads individuals to be motivated to learn.
(S) To have a desire to continue learning, individuals must experience a sense of satisfaction with either the process or the outcome of the learning experience.
Continued motivation to learn ị r v ị i ị Motivation to learn ỉ ỉ
Figure 2.1 ARCS motivational design model, Loorbach et al (2015)
The ARCS model synthesizes various concepts and theories of human motivation into a straightforward framework that aids educators in crafting engaging teaching methods Its primary goal is to stimulate interest and sustain motivational learning strategies within instructional designs.
Attention serves as a crucial bridge between cognition and memory, significantly impacting learners' ability to retain information In educational contexts, learner attention is vital for motivation and effective learning, acting as the initial step in the learning process To foster and maintain this attention, strategies such as cognitive stimulation, inquiry stimulation, and variability are essential Cognitive stimulation engages learners' senses and emotions, while inquiry stimulation piques their curiosity, particularly when presented with contradictory facts Effective teaching methods must incorporate variations to sustain attention, as excessive distractions can hinder motivation Achieving a foundational level of attention allows for deeper engagement in inquiry-based activities, ultimately enhancing the relevance of the learning experience.
Relevance plays a crucial role in gamified learning environments, as it reflects individuals' perceptions of attraction toward goals aligned with their motivations and values (Keller, 2010) The more appealing a goal, the higher the likelihood of pursuit, provided it seems attainable Often, students seek practical applications for their learning, emphasizing the need for relevance in education, which is deemed essential for effective communication and cognition (Sperber & Wilson, 1986) To enhance learning motivation, it is vital to connect lessons to learners' backgrounds, interests, and goals Three key strategies for fostering relevance include goal-relevance, interest-relevance, and experience-relevance.
To enhance learning, it's crucial for individuals to define their objectives, as this clarity helps establish connections with the subject matter, even if indirectly In cases where learners lack clear goals or fail to see the relevance of the content, the future wheel technique can be employed to highlight the potential future value of the material Additionally, personal recognition and valuing learners as individuals significantly boost motivation and engagement, fostering a sense of care regardless of their performance Ultimately, the goal of education is to broaden students' minds and promote critical and creative thinking A practical strategy to achieve this is by linking new content to learners' existing knowledge and experiences, paving the way for the introduction of new ideas and perspectives.
Confidence often involves belief in one's own ability to perform (Bandura, 1977;
The ARCS model emphasizes the importance of confidence in enhancing learners' expectations of success, which empowers them to take control of their learning journey (Chemers et al., 2000; Clark et al., 2008) A strong correlation exists between confidence levels and success expectations, making it crucial to provide learners with an assessment of their likelihood of success This confidence is rooted in cognitive control, with a loss of such control often leading to psychological issues like fear and depression (Keller, 2010) Key concepts in this context include Locus of Control and Self-Efficacy Locus of Control, introduced by Rotter (1966), refers to individuals' beliefs about their control over life events, distinguishing between those with an internal locus, who expect rewards based on their efforts, and those with an external locus, who believe outcomes depend on external factors Self-Efficacy, defined by Bandura (1977), reflects a person's confidence in their ability to accomplish specific tasks, influencing their coping strategies, effort levels, and persistence in the face of challenges (Bandura, 1986).
Satisfaction is a complex emotional state influenced by both internal and external factors, as described by Keller A person's past experiences with goal-directed behaviors shape their future expectations and the value they place on those goals For instance, a student who has previously won significant prizes may develop heightened expectations for future competitions; if they win again but the prize is less prestigious, they may feel dissatisfied despite achieving a good result To enhance satisfaction, Keller identifies three key strategies: fostering intrinsic motivation, providing extrinsic rewards, and ensuring fairness Encouraging students' intrinsic interest can make learning enjoyable without the need for external incentives, while extrinsic rewards, such as praise or gifts, can further boost satisfaction Lastly, maintaining fairness in reward criteria is crucial, as students often compare their results to others If they perceive unfairness in evaluations, it can lead to negative emotions and hinder their academic performance.
Self-Directed Learning, as defined by Knowles (1975), is a widely accepted concept that emphasizes the individual's initiative in the learning process It involves diagnosing personal learning needs, setting goals, identifying resources, selecting strategies, and evaluating outcomes, with or without external assistance This active approach to learning is increasingly prioritized in higher education, as it enhances the quality of the learning experience compared to passive reliance on teachers.
Related theory
Flow theory, introduced by Mihaly Csikszentmihalyi, describes a mental state where individuals are fully immersed in an activity, losing track of time and focusing entirely on the task This state fosters "optimal experiences," where people engage in activities for their intrinsic joy and satisfaction, rather than for external rewards Csikszentmihalyi (2008) highlights that during flow, individuals experience emotions such as happiness and fulfillment, emphasizing the importance of concentration and effort in achieving this state Research by Huang et al further explores these concepts, underscoring the benefits of flow in enhancing overall well-being.
Research from 2018 indicates that learning experiences significantly impact educational outcomes, prompting educators to foster a flow state among students Incorporating gamification elements, such as excitement and competition, has been shown to enhance student engagement and enthusiasm for learning (Wirani et al., 2022) This study utilizes flow theory as a foundational framework to identify gamification factors that promote a flow state, ultimately aiming to enhance learning efficiency.
Building on Thorndike’s law of effects, B.F Skinner developed Operant Conditioning Theory, which posits that animals learn to associate behaviors with consequences Positive outcomes increase the likelihood of behavior repetition, while negative outcomes deter it Skinner identified methods to reinforce behaviors, such as positive reinforcement, where rewards encourage repetition, and negative reinforcement, which removes unpleasant outcomes To diminish behaviors, positive punishment introduces unpleasant results, and negative punishment removes positive outcomes Incorporating gamification elements like rewards, feedback, and praise can effectively reinforce students' learning behaviors, enhancing their overall learning efficiency.
Experimental studies
2.3.1 Study 1: Validation of the Instructional Materials Motivation Survey (IMMS) in a self-directed instructional setting aimed at working with technology
(1) Authors: Nicole Loorbach, Oscar Peters, Joyce Karreman and Michael Steehouder
The ARCS motivational design model effectively enhances student motivation by focusing on attention, relevance, confidence, and satisfaction The Instructional Materials Motivation Survey (IMMS), consisting of 36 items, assesses individuals' responses to instructional materials based on the ARCS framework Despite its frequent use, the IMMS lacks extensive validation regarding its statistical and theoretical foundations.
This article presents a comprehensive validation study utilizing the Instructional Materials Motivation Survey (IMMS) in a self-directed learning environment focused on cell phone technology The findings from structural equation modeling indicate that the IMMS can be condensed to 12 items, resulting in a streamlined version known as the Revised Instructional Materials Motivation Survey (RIMMS) The RIMMS is favored over the original IMMS, as it effectively measures the four key constructs of the ARCS model: attention, relevance, confidence, and satisfaction, while also highlighting the conditional nature of these constructs.
This study involved a questionnaire distributed to 59 respondents aged 60 to 70, all of whom had no prior knowledge of brand usage The research focused on cell phone usage, and the collected data will be analyzed using Linear Structural Equation Modeling (SEM).
(5) Grounded theory: The ARCS model of motivational design.
Figure 2.1 ARCS motivational design model, Loorbach et al (2015)
(7) Main Results/Contributions of the Study:
This study validates the A to Z 1MMS, recommending the use of RIMMS over IMMS for self-directed teaching, particularly for individuals who can benefit from motivational instructions It confirms IMMS as an effective posttest tool for assessing the achievement of the four ARCS goals in instructional materials However, RIMMS is favored in self-directed learning environments due to its simplicity and absence of factual items, ambiguities, or references to success or failure.
(8) Limitations and future research directions:
However, validation of this self-reported measure of motivation is in its infancy, and our study has several limitations mainly related to its relatively small sample size.
While the current sample size was adequate for evaluating model fit, future validation studies should utilize larger samples to reliably detect any existing statistical differences.
Further validation studies should further demonstrate whether the greater suitability of RIMMS over IMMS holds true in self-directed teaching settings with other populations.
Future research should focus on validating the RIMMS framework within traditional instructional environments, specifically those for which the ARCS and IMMS models were initially developed, like face-to-face classroom settings Additionally, it is essential to explore its application in contexts where the ARCS model has been utilized, including self-directed computer-based instruction and distance education.
2.3.2 Study 2: Measuring Chinese Middle School Students’ Motivation Using the Reduced Instructional Materials Motivation Survey (RIMMS): A Validation
Study in the Adaptive Learning Setting
(1) Authors: Shuai Wang, Claire Christensen, Yuning Xu, Wei Cui, Richard Tong and Linda Shear (2020)
Research indicates that student motivation can significantly influence the benefits derived from adaptive learning systems However, motivation often declines as students progress through KI2 education systems To counteract this trend, it is crucial to identify the sources of lost motivation Measuring student motivation is essential for enhancing adaptive learning systems and improving the accuracy of learning records This study employs the ARCS model to assess student motivation and evaluates the effectiveness of the Reduced Instructional Document Motivation Survey (RIMMS) as a measurement tool aligned with the ARCS framework.
The study confirms that the RIMMS effectively maintains its four-factor structure—attention, relevance, confidence, and satisfaction—designed to evaluate motivation based on the ARCS model Additionally, it explores the correlation between student motivation and their background characteristics within adaptive learning environments.
The study employs the Reduced Instructional Materials Motivation Survey (RIMMS) to gather data from 429 students across 21 provinces in China Utilizing a multi-indicator multi-causation (MIMIC) model, it connects CFA-based outcomes with various student and family background factors Data analysis was performed using Mplus software.
(6) Definition of main concepts of the study:
Adaptive learning systems use different learning algorithms, such as machine learning and item response theory, to personalize the learning sequence for each student.
Attention: The learning experience must capture and maintain the learner’s attention.
Relevance: The learning experience must be relevant and relevant to the individual learner.
Confidence: The learning experience should foster confidence in the learner’s ability to learn.
Satisfaction: The process or outcome of the learning experience must help the learner feel satisfied.
Figure 2.2 Research model of Shuai Wang et al (2020)
This study confirms the effectiveness of the Reduced Instructional Materials Motivation Survey (RIMMS) as a valid measure of student motivation in adaptive learning environments for mathematics The findings provide additional evidence that RIMMS can be utilized to make valid inferences across diverse cultural contexts.
At the same time, research also shows that the four-factor ARCuS model is valuable for making assessments of student motivation.
The study's findings have limitations regarding their generalizability, as they exclusively examined 9th-grade students and a narrow range of math topics To enhance understanding, future research should investigate whether the ARCS model maintains its four-factor structure and if the relationship between student characteristics and motivation is consistent across different grades and subjects.
2.3.3 Study 3: Evaluation of continued use on Kahoot! as a gamification-based learning platform from the perspective of Indonesian students
(1) Authors: Yekti Wirani, Tifanny Nabarianb, Muh Syaiful Romadhon (2022)
In Indonesia, lecturers are challenged to create engaging lectures to enhance student achievement, particularly during the Covid-19 pandemic One effective strategy is the integration of gamification elements into the learning process, with platforms like Kahoot! serving as a valuable tool This study evaluates the effectiveness of Kahoot! as an engaging and beneficial learning method for Indonesian students.
This study highlights the effectiveness of Kahoot! as a gamified learning method that enhances student achievement By examining key gamification elements such as enjoyment, competition, and challenge, the research provides valuable insights into its application within a developing country context.
(4) Research methodology: This study collected data from a questionnaire distributed to 301 student respondents in Indonesia The obtained data will be processed with Partial Least Squares Structural Equation Modeling (PLS-SEM).
(5) Grounded Theory: Technology Acceptance Theory (TAM)
(6) Definition of main concepts of research
Gamification is defined as creating a non-gaming environment that includes game elements to create a better user experience and achieve user engagement.
Kahoot! is the first Student Response System (SRS) designed to provide game experiences by implementing game principles from motivation and gameplay theory.
Competition (CO) means the ability to compete in games can increase motivation, engagement and willingness to spend more time.
Enjoyment (EN) is defined as the excitement and joy of using technology.
Challenge (CH) is defined as the desire to achieve predetermined goals.
Satisfaction (ST) means all aspects of the experience you feel when purchasing and using technology.
Perceived usefulness (PU) is defined as the degree of confidence a user has that a technology will improve performance.
Personal impact (II) is defined as the participant's perception of personal task achievement and increased productivity
Figure 2.3 Research model of Yekti Wirani et al (2022)
This study explores the key constructs of Competitiveness, Challenge, and Enjoyment within gamification, alongside Perceived Usefulness, Satisfaction, and Personal Impact Findings indicate that Competitiveness and Enjoyment significantly enhance continued use by fostering perceived usefulness These results highlight the potential of Kahoot! as an effective gamified learning method to boost student achievement.
This study's limitations include its geographical focus, which does not encompass all of Indonesia, and its exclusive evaluation of the Kahoot! platform Future research should aim to include students from various universities across Indonesia and explore additional educational platforms such as Mentimeter, Quizizz, Quizlet, Schoology, and Poll Everywhere to provide a more comprehensive understanding.
2.3.4 Study 4: Enhancing User Engagement through Gamification
(1) Authors: Ayoung Suh, Christian Wagner & Lili Liu (2016)
Research model and research hypotheses
Gamification factors in applications for
Figure 2.6 Model proposed by the author group Competition
Competition plays a crucial role in enhancing the effectiveness of games by fostering player interaction (Chen et al., 2020; Dondlinger, 2007) It is a key element of gamification, motivating users to improve their skills and engage in rivalry with others (Wirani et al., 2022) This competitive aspect can boost learners' motivation, engagement, and time investment in the learning process (Jinlin Wan et al., 2017) Gamified learning systems often incorporate design elements like leaderboards and competitor profiles, which enhance participants' involvement in the competition (Chen et al., 2012) Research indicates that score-based competition can positively influence students' learning attitudes and interests while preventing cognitive overload (Hwang and Changtom, 2016) Additionally, competition is linked to improved effort-based learning and focus (Dimenichi et al., 2015) Cognitive Evaluation Theory suggests that fulfilling basic psychological needs—competence, autonomy, and relatedness—during activities can enhance motivation (Chia-Lin, 2022) This study aims to explore how gamification mechanisms, particularly competition, impact users' psychological satisfaction and internal motivation (Sailer et al.).
(2017) shows that competitive elements in game design have an impact on user satisfaction Therefore, the group proposed the following hypothesis:
Hypothesis la: Competition has an effect on Attention.
Hypothesis lb: Competition has an effect on Relevance.
Hypothesis 1c: Competition has an effect on Confidence
Hypothesis Id: Competition has an effect on Satisfaction.
Enjoyment is characterized as the positive feelings derived from surpassing personal limits and achieving new goals, particularly when faced with challenges (Li et al., 2018; Zhang et al., 2021) As a key element of gamification, enjoyment aims to enhance user happiness through technology For learners, gamification incorporates audio, visuals, videos, and achievement points to enrich the educational experience (Aparicio et al., 2019) Numerous studies (Koufaris, 2002; Park et al., 2014; Venkatesh, 2000) indicate that cognitive enjoyment significantly influences attitudes towards technology use, operationalized as either task enjoyment (Koufaris, 2002) or system enjoyment (Chin and Gopal, 1995) While interest fosters intrinsic motivation by guiding attention and exploration, enjoyment sustains motivation by encouraging persistence in activities (Reeve, 1989) Additionally, positive emotions, as suggested by Fredrickson's broaden-and-build theory, enhance attention and cognitive flexibility (Fredrickson, 1998; Fredrickson and Branigan, 2005) Research by Park et al (2019) further highlights that enjoyment positively affects user satisfaction, with Ords et al (2016) noting that students find satisfaction in using online videos for teaching, thereby making learning more engaging and effective.
Hypothesis 2a: Enjoyment has an effect on Attention.
Hypothesis 2b: Enjoyment has an effect on Satisfaction.
Numerous scientific studies have explored the influence of rewards on human behavior, stemming from Skinner's outcome conditioning theory and evolving into the widely used Reward-based learning method (Deci, 1999) While opinions vary on whether rewards enhance or diminish intrinsic motivation (Filsecker & T.H., 2014), our research posits that rewards can indeed boost motivation In educational gamification, completing tasks can yield points or coins redeemable for tangible rewards like badges and gifts These rewards, which can also include praise and performance feedback (Deci, 1999), significantly engage the human brain, as reward-related stimuli attract attention (Bourgeois et al., 2022) Berridge (2009) notes that desire, or incentive salience, propels individuals toward rewards, indicating that games offering rewards can enhance player engagement Praise, as a form of reward, aligns with reinforcement theory, promoting desired behaviors (Skinner et al., 1930-1940) Furthermore, performance feedback enhances work output (Casas-Arce et al., 2017) and informs players about their progress, impacting their confidence in achieving goals (Tondello et al., 2016) The relationship between rewards and satisfaction is evident, as game features like badges and feedback can elevate student satisfaction (Mishra, 2023; Kim et al., 2018) Thus, we propose the following hypothesis.
Hypothesis 3a: Reward has an effect on Attention.
Hypothesis 3b: Reward has an effect on Confidence.
Hypothesis 3c: Reward has an effect on Satisfaction.
Recent studies highlight the significant impact of attention on performance and learning (Wulf & Prinz, 2001) Keller's ARCS motivational design model emphasizes the crucial link between attention, motivation, and effective learning, asserting that learner engagement is essential for any learning to occur (Keller, 2010) Even the best instructional methods can be ineffective if learners are not fully attentive Additionally, research by Zaky and colleagues (2020) reinforces this connection, demonstrating that a lack of attention can hinder performance and productivity by slowing or stopping responses.
Hypothesis 4: Attention has an effect on Learning Effectiveness.
Relevance plays a crucial role in the gamification of communication and cognition, significantly impacting academic performance Research by Liberman and Chaiken (1996) indicates that relevant learning experiences enhance learning outcomes, while Lan and Hew (2020) found a direct correlation between academic relevance and students' scores Additionally, studies show that active participation in learning activities leads to higher scores and course completion rates (Tang et al., 2018) Furthermore, Trimmel and Bachmann (2004) discovered that students utilizing technology in their learning exhibit greater involvement, interest, and motivation compared to those who do not Thus, we propose the following hypothesis.
Hypothesis 5: Relevance has an effect on Learning Effectiveness.
Research indicates that student confidence significantly impacts the learning process, with studies showing a positive correlation between high confidence and academic achievement (Akbari, 2020; Tuncel, 2015) Verma et al (2016) found that self-confidence levels directly influence the academic performance of elementary students, revealing notable differences between high and low confidence groups Similarly, Fischer and Sliwka (2018) demonstrated that confidence in one's learning abilities enhances motivation and attention, particularly among students with lower prior knowledge Tridinanti (2018) further highlighted that confidence is a stronger predictor of academic performance than anxiety among college EFL students Overall, these findings suggest that fostering student confidence can lead to improved academic outcomes, prompting the hypothesis that enhancing self-confidence is crucial for better performance.
Hypothesis 6: Confidence has an effect on Learning Effectiveness.
Satisfaction in the learning process is defined as the degree to which students feel content with their experiences and outcomes (Uka, 2014) Numerous studies have established a correlation between satisfaction and learning effectiveness, with Shih, Muroz, and Sanchez (2006) demonstrating that satisfying learning experiences enhance academic performance Furthermore, research by Perez-Perez et al (2020) and Ifinedo, Pyke, and Anwar (2018) indicates that satisfaction positively influences learning outcomes in online environments (Moodie) Keller's model suggests that satisfaction levels are affected by expectations formed from prior achievements This group's research specifically examines how experiences during the learning process contribute to satisfaction and its subsequent impact on learning outcomes, leading to the formulation of their hypothesis.
Hypothesis 7: Satisfaction has an effect on Learning Effectiveness.
Chapter 2 provides a comprehensive review of existing studies on gamification elements that influence learning effectiveness, utilizing the ARCS motivation model as a framework Drawing from foundational theories, the authors have developed a proposed research model to further explore these relationships.