Therefore, our research has added the impact of Satisfaction on Individual Impact II and from the Individual Impact II factor that affects students' intention to continue using the appli
INTRODUCTION
PROBLEM STATEMENT
With the ongoing evolution of education, innovative learning methods are constantly being explored, one of which is gamification (GAM) This effective approach integrates various gaming elements into non-gaming contexts to encourage desired behaviors and address challenges (Zichermann & Cunningham, 2011) Initially utilized in marketing, GAM has since been applied in diverse fields, including healthcare (Schoechet et al.).
2013), learning environments (Filsecker & Hickey, 2014), sports (Hamari & Koivisto,
2014), engineering (Huotari & Hamari, 2017), mathematics (Attali & Arieli-Attali,
2015), computer science (Dominguez et al., 2013) and psychology (Landers & Landers,
Research indicates that gamification can effectively encourage the initiation and continuation of goal-directed behaviors, particularly in educational settings Notably, student participation in learning activities has emerged as a key focus area, highlighting the importance of engagement in the learning process.
In the learning environment at UEH, effective knowledge transmission between lecturers and students is crucial; however, traditional one-way communication often leads to distractions and a lack of motivation, negatively impacting learning outcomes (Liu et al., 2012) To address this issue, UEH student groups have implemented gamification techniques, particularly through the Kahoot! application, to foster an engaging and enjoyable learning atmosphere while enhancing concentration According to James Paul Gee, well-designed video games serve as effective learning tools, as they engage players in a way that promotes learning unconsciously (Gee, 2003) Gamification is recognized as a form of active learning (Garcia-Jurado et al., 2018), utilizing the emotional enjoyment derived from games to create a relaxed and receptive mindset conducive to learning (Demkah).
Kahoot! is a pioneering Student Response System (SRS) that leverages game design principles rooted in intrinsic motivation and game flow theories to create engaging learning experiences By transforming classroom learning into interactive game performances, Kahoot! allows lecturers to present questions via a laptop, which are displayed on a screen, while students respond using their mobile devices This innovative approach enhances student engagement and motivation in the learning process.
Kahoot! enhances the student learning experience by incorporating audio, images, and videos within its Student Response System (SRS) The platform employs key gamification elements such as personalized names, immediate feedback, grading, podium rankings, competitive challenges, and time constraints to boost student engagement and performance.
Kahoot! significantly boosts student motivation and performance, as evidenced by Vranesic et al (2019) Unlike similar platforms like Quizizz and Google Forms, Kahoot! enhances participant concentration, perceived learning, enjoyment, engagement, and satisfaction more effectively (Chaiyo & Nokham, 2017) Consequently, Kahoot! is ideal for educational settings, particularly for presentations, as it fosters enjoyable learning experiences and increases student engagement.
The study “Understanding The Factors Contributing To The Continued Use Of
Kahoot! serves as an engaging gamification platform for learning, particularly beneficial for UEH students This case study evaluates its effectiveness as an easy and interesting learning method, highlighting students' positive experiences The findings suggest that incorporating Kahoot! into the educational process can enhance student performance, indicating its potential for continued use in the learning environment.
RESEARCH GAPS
This study was conducted for several reasons.
In various countries, studies have explored the continuance intention to use gamification, particularly focusing on Kahoot! in educational settings While Kahoot! enjoys popularity in Vietnam's educational landscape, there is a notable lack of research regarding learners' intentions to continue using the application Recognizing this gap, the authors conducted a study at UEH University to assess the impact of Kahoot!'s gamification elements on students' intention to persist in using the platform The findings aim to provide insights and suggestions for future research in this area.
This study synthesizes and builds upon the research models established by Wirani and Romadhon (2022), Al-Rahmi et al (2018), Idowu and Kissi (2020), Cho et al (2023), Lu et al (2019), Shin and Kang (2015), and Zhang.
Previous studies have highlighted that Satisfaction (SA) significantly influences behavior and the intention to continue using technology, with Individual Impact (II) also playing a crucial role According to Levy (2007) and Howell and Buck (2011), student satisfaction with a course is a vital determinant of their decision to persist or withdraw However, prior research lacked a model examining the relationship between Satisfaction (SA) and Individual Impact (II) Our study aims to fill this gap by investigating how Satisfaction (SA) affects Individual Impact (II) and, subsequently, students' intention to continue using the application.
This study uniquely explores the connection between student satisfaction and personal achievement, as well as the impact of personal achievement on the intention to continue using Kahoot! While previous research, including works by Janicki and Liegle (2001), Fogerson (2005), Rohan et al (2021), and Chu et al (2022), has acknowledged the significance of the Achievement (AC) factor in influencing Continued Use (CU), there has been a lack of research models addressing the interplay between these two elements Consequently, the authors propose that personal achievement should be considered a key factor influencing the intention of UEH students to continue utilizing Kahoot!.
RESEARCH OBJECTIVES
Our research aims to illustrate how Competitiveness, Enjoyment, and Challenge influence Continued Use intention, mediated by Perceived Usefulness, Satisfaction, Individual Impact, and Achievement This approach distinguishes our study from that of Yekli Wirani et al (2022) Based on these objectives, we have formulated specific research questions to guide our investigation.
What factors influence the continued use of Kahoot! by UEH students when the authors apply it as a gamification tool to enhance the learning experience?
The study examines how gamification elements such as competitiveness, challenge, and enjoyment impact students' perceived usefulness, satisfaction, and individual impact when using Kahoot! as a learning tool It highlights the correlation between these elements and students' achievement, as well as their intention to continue utilizing Kahoot! in their educational journey.
To enhance the effectiveness of gamification apps like Kahoot!, it is essential to implement targeted recommendations that foster engagement among students Encouraging creativity and agility in using these tools, particularly for UEH students unfamiliar with them, can be achieved through tailored training sessions, interactive workshops, and incentives that highlight the benefits of gamification in learning By creating a supportive environment that promotes experimentation and collaboration, educators can motivate students to actively embrace these innovative learning methods.
This study's findings support the ongoing use of Kahoot! as a gamified learning method that enhances student achievement, offering a more comprehensive explanatory model than those presented in previous research.
RESEARCH QUESTIONS
From the above research objectives, our research questions are:
What factors influence the continued use of Kahoot! by UEH students when the authors apply it as a gamification tool to enhance the learning experience?
The degree of influence of each factor on academic achievement and, ultimately, the intention to continue using Kahoot! by students as learning tools?
To enhance the effectiveness of gamification applications like Kahoot!, it is essential to implement targeted recommendations that foster creativity and agility among UEH students Encouraging active engagement with these tools, especially for first-time users, can be achieved through tailored incentives such as interactive workshops, competitive challenges, and recognition of achievements By promoting a supportive learning environment and integrating gamified elements into the curriculum, students can be motivated to explore and utilize these applications more effectively in their studies.
SCOPE OF THE STUDY
Research object: Factors affecting the intention to continue using Kahoot! of UEH students.
Target population: Full-time students of UEH University from course 46 to course 48.
Sampling method: Conduct surveys and interviews with full-time students of UEH University through the survey form.
This study will conduct an exploratory factor analysis (EFA) with a sample size of 300 participants for its quantitative research To ensure data quality, the research team will eliminate unsatisfactory responses, focusing on the remaining samples for comprehensive analysis.
RESEARCH METHOD
The study conducted at UEH University focused on the use of Kahoot! among students, involving a sample of 327 respondents, with 300 participants who had utilized the application The research took place from July 10 to July 17, 2023, employing a random survey method to ensure data representativeness Participants included students living and working in Ho Chi Minh City, and data was gathered through an online questionnaire using Google Forms for efficient information collection The questionnaire consisted of two sections: the first addressed demographic details such as gender, age, and course of study, while the second assessed support variables using a Likert scale ranging from 1 (complete disagreement) to 5 (complete agreement).
This study developed a model based on supporting theories, including the GAM and Kahoot!, while incorporating concepts such as Competitiveness, Enjoyment, Challenge, Perceived Usefulness, Satisfaction, Individual Impact, Achievement, and Continued Use Utilizing quantitative research methods, data was collected through survey questionnaires and encoded using Excel 2019 To address the research questions and validate the hypotheses, the authors employed Smart PLS (Partial Least Squares) for descriptive statistical analysis The PLS technique was chosen for its effectiveness in examining relationships between exogenous and endogenous constructs, as well as for hypothesis testing (Handayani et al., 2018).
THE CONTRIBUTION OF THIS RESEARCH
Research on the integration of gamification elements in Kahoot! reveals that factors such as Perceived Usefulness, Achievement, Satisfaction, and Individual Impact significantly influence its continued use among students at Ho Chi Minh City University of Economics (UEH) The findings suggest effective strategies to enhance student engagement with Kahoot! in their learning processes, promoting knowledge diversity and flexibility for improved academic performance This positive research outcome serves as a valuable resource for both students and instructors, enabling the use of Kahoot! as a teaching support platform that allows lecturers to monitor student progress and academic achievements Consequently, educators can make informed adjustments to enhance teaching quality, thereby strengthening UEH's reputation for producing high-quality graduates in today's competitive job market Additionally, this study offers insights for gamification developers, guiding them in creating engaging learning applications that boost productivity and efficiency.
RESEARCH STRUCTURE
Our research is divided into the following chapters:
This chapter outlines the key elements of our research, including the problem statement, research gap, objectives, methodology, and contributions Chapter 1 begins with a broad introduction to our research, gradually narrowing down to specific topics and areas of focus It concludes by discussing the implications of the research findings upon completion.
Chapter 2: Literature Review and Hypothesis development
Chapter 2 defines key concepts such as scales, variables, and objects pertinent to the research, while also presenting prior studies that serve as the foundation for outlining the research model.
This chapter will be divided into two parts:
Part 1 will describe and present an overview of the process, from data collection to research results.
Part 2 will include a detailed description of the research steps In addition, the authors will provide scales for factors, standards, and requirements as a basis for analysis and conclusions.
This chapter will present our analysis, scale validation, and conclusions.
This chapter delves into the detailed implications of the research findings, highlighting their significance Additionally, the authors will outline key policy recommendations for government action and propose avenues for future research, while also addressing the limitations encountered in this study.
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT
INTRODUCTION
In Chapter 1, the authors provide an overview of the research, outlining its significance and establishing clear objectives to guide the analysis Chapter 2 will introduce key concepts and theoretical foundations for the proposed research model, including definitions of relevant terms, a review of related research, and the formulation of hypotheses.
2.2.1 The Technology Acceptance Model (TAM)
Figure 1: The Technology Acceptance Model
Davis's technology acceptance model (Silva, 2015; Davis et al., 1989) is formulated based on the theory of reasoned action (TRA) and the theory of planned behavior (TPB) (King & He, 2006; Marangunic & Granic, 2015).
The Technology Acceptance Model (TAM), developed from the Theory of Reasoned Action (TRA) in 1986, focuses on user acceptance of information technology by incorporating perceived usefulness and perceived ease of use as key variables (Lai, 2017) Davis's modifications introduced 'attitude' as a mediator between belief constructs and usage intention, broadening the understanding of computer acceptance and user behavior (Davis et al., 1989) Silva (2015) emphasized the importance of including external factors such as system functions, interfaces, development methods, training, and user participation, which can influence perceived usefulness and ease of use.
Venkatesh and Davis formulated the final version of TAM by removing the mediator
The Technology Acceptance Model (TAM) outlines a three-stage process where external factors influence cognitive responses, specifically perceived ease of use and perceived usefulness, which then shape attitudes toward technology and ultimately affect usage behavior This model has proven to be consistent and valid across various contexts, making it a foundational framework in technology acceptance research Numerous studies have applied TAM in diverse fields, including education, healthcare, and entertainment, highlighting its broad applicability and significance in understanding user behavior.
Building on the Technology Acceptance Model (TAM), this study investigates the factors influencing UEH University students' intention to continue using Kahoot!, specifically focusing on perceived usefulness and satisfaction By analyzing user behavior and its impact on learning outcomes, the research identifies external factors that enhance students' perceived usefulness and satisfaction with the platform The authors developed a streamlined model based on TAM to pinpoint the key elements that significantly affect students' continued engagement with Kahoot!.
2.2.2 The expectation-confirmation model of Information Systems continuance (ISC)
Figure 2: The expectation-confirmation model of Information Systems continuance
The expectancy-confirmation model of IS continuance, developed by Bhattacherjee in 2001, is based on the expectancy disconfirmation theory and focuses on the confirmation/disconfirmation process that starts with users' initial expectations of technology After using the system, users evaluate its actual performance against their expectations, leading to a confirm/disconfirm rating Bhattacherjee's model suggests that IS users' decisions to continue using a system are akin to consumers' repurchase decisions, as they are influenced by prior experiences and can result in a reversal of initial choices Key factors influencing continued use include user satisfaction and perceived usefulness, with satisfaction primarily stemming from the confirmation of expectations and, to a lesser extent, from the perceived usefulness of the IS.
The expectancy-confirmation model of information systems (IS) continuance, developed by Bhattacherjee, established the foundational scales for assessing ongoing IS usage and offered an initial framework to understand the phenomenon of IS discontinuation This theory has been widely referenced in numerous studies focused on IS continuance.
The Perceived Usefulness variable in the model highlights users' beliefs regarding the advantages of utilizing a system, service, or technology Initially, users may adopt the application out of curiosity, but as they gain experience, their focus shifts towards evaluating its performance and the benefits derived from the information system (Karahanna & Chervany, 2001).
The expectancy-confirmation model of information system (IS) continuance, established by Bhattacherjee (1999), emphasizes the importance of user satisfaction, which arises when initial needs and expectations are fulfilled post-usage This satisfaction is crucial for fostering user loyalty and influencing future behaviors (Bolen & Ozen, 2020; Limayem et al., 2007) Recent studies exploring the continuance intention to use gamified applications have built upon this foundational model, as seen in the works of Huang et al (2019), Aydinliyurt et al (2021), and Rosian et al (2023).
2001) Similarly, his study focused on investigating the relationship between Perceived Usefulness and Continued Use Intention, Satisfaction, and Continued Use Intention of UEH students after using a gamified learning application - Kahoot!.
DEFINITION CONCEPTS
Gamification platforms enhance learning by fostering competitive interactions among users through individual or group leaderboards This competitive social engagement is a key strategy in gamification, as it can elevate learners' participation and engagement levels (Burguillo, 2010) The element of competitiveness not only boosts motivation but also encourages players to invest more time in knowledge-related tasks within the game (Wan et al., 2017) Ultimately, gamification is designed to inspire users to continually enhance their skills and compete with peers (Wirani et al., 2022; Bitrián et al., 2021).
Enjoyment is defined as the positive feelings that arise from surpassing personal limits and achieving new or unexpected goals, particularly when facing challenging tasks (Li et al., 2018; Zhang et al., 2021) It encompasses the pleasure derived from using technology (Aparicio et al., 2019) and serves as a crucial value source for gamers, motivating them to engage in enjoyable activities (Yang et al., 2017) Consequently, enjoyment is recognized as a key element of gamification (Wirani et al., 2017).
Recent studies highlight the significant role of enjoyment in gamification for learning, as noted by Mitchell et al (2020) and supported by Wirani et al (2022) This enjoyment not only enhances user happiness but also incorporates emotional energy, which is crucial for engaging learners (Aparicio et al., 2019; Wu et al., 2015; Csikszentmihalyi, 1997) Furthermore, Koo (2009) emphasizes that enjoyment serves as a key motivator for participation in online games, underscoring its importance in educational gamification.
Challenge (CH) is the desire to achieve predetermined goals (Aparicio et al.,
Gamification in education presents challenges that enhance skill sets, boost motivation, and improve learning outcomes Research indicates that such challenges not only increase motivation but also expand players' abilities (Fullagar et al., 2013) Theories by Csikszentmihalyi (1990) and Bronfenbrenner (1979) suggest that cognitively complex and challenging tasks lead to deeper student engagement Studies confirm that students are more focused and engaged when faced with challenges in the classroom Experimental games can foster this engagement and yield effective learning results (Jaaska et al., 2022) Additionally, research by Wirani et al (2022) highlights challenge as a key gamification factor that affects user satisfaction and the intention to continue using platforms like Kahoot!
Perceived usefulness (PU) is a crucial factor influencing usage behavior, as established by research, including the technology acceptance model (TAM) (Davis, 1989), which defines PU as the likelihood that using a specific application will enhance job performance Numerous studies have demonstrated that PU significantly affects users' intentions to adopt systems For example, Abdullah et al (2016) found that perceived usefulness positively impacts students' intentions to utilize e-portfolios for learning Additionally, Zhou et al (2017) revealed that perceived usefulness is a strong predictor of individual behavioral intentions regarding mobile video call usage.
Satisfaction (SA) encompasses the overall experience of purchasing and using technology Gamification tools enhance user engagement, fostering a state of flow that encourages students to adopt pro-learning habits (Aguiar-Castillo et al., 2020) Research indicates a strong connection between flow, user satisfaction, and the acceptance of information technology (Ghani et al., 1994) Various methods exist to define and assess student satisfaction, with Rubin et al (2013) building on the Communities of Inquiry framework (Garrison et al., 2000) to highlight the importance of social, cognitive, and instructional presence in enhancing the learning experience Furthermore, Ke et al (2013) identified five key factors influencing student satisfaction: learner relevance, active learning, authentic learning, learner autonomy, and technological capacity.
Keengwe et al (2012) emphasize that understanding student expectations is crucial for instructors to design effective technology tools, which significantly impacts student satisfaction, primarily driven by learning convenience Dziuban et al (2007) identified six essential factors that enhance student satisfaction: a rich learning environment, clearly defined engagement rules, instructor commitment, reduced ambiguity, an engaging atmosphere, and diminished ambivalence regarding course values Engaged and satisfied students tend to be motivated and responsive, fostering a productive learning environment and achieving higher academic success Conversely, dissatisfied or ambivalent students can create challenges for instructors, making it harder to facilitate effective learning experiences (Dziuban et al., 2015).
Individual Impact (II) refers to how participants perceive their personal task achievement and productivity improvements as a result of using information systems (Wirani et al., 2022; DeLone et al., 1992) It encompasses various dimensions, including job performance, task performance, and decision-making effectiveness (Igbaria et al., 1997; Deng et al., 2022).
According to Wirani et al (2022), Individual Impact evaluates how effectively participants utilize technology Previous studies, including those by Jeyaraj, have highlighted the important connection between system use and Individual Impact.
Utilizing Kahoot! as a gamification-based learning platform enhances students' learning experiences by helping them improve their scores, deepen their understanding of the material, and ultimately boost their productivity.
Previous studies have distinguished three learning effects perceived by learners, including cognitive, behavioral, and emotional outcomes (Wei et al., 2021); Yu et al.,
A study from 2010 highlights the significance of personal achievement in relation to cognitive and behavioral learning outcomes, as perceived by learners Cognitive learning outcomes are typically evaluated through tests and self-assessments of knowledge, as noted by Kraiger et al (1993) In contrast, behavioral learning outcomes focus on the practical application of knowledge and skills, reflecting actual cognitive behaviors.
Incorporating gamification into learning must prioritize effective outcomes and high achievement levels To maintain quality in educational achievements, gamification techniques should at least match the effectiveness of traditional learning methods.
Previous studies have distinguished three learning effects perceived by learners, including cognitive, behavioral, and emotional outcomes (Wei et al., 2021; Yu et al.,
The study highlights that personal achievement is linked to cognitive and behavioral learning outcomes, as perceived by learners Cognitive learning outcomes are typically evaluated through tests and self-assessments of knowledge, while behavioral outcomes reflect the practical application of acquired knowledge and skills To ensure effective learning through gamification, it is crucial that these methods yield results comparable to traditional learning approaches, thereby maintaining high standards of achievement.
The success of an IT tool like Kahoot! hinges on sustained user engagement, as highlighted by Bhattacherjee et al (2015) Continuous use intention, defined as the long-term commitment of users, emerges after initial acceptance, which is the first step towards effective utilization (Bhattacherjee, 2001) While initial acceptance is crucial, the long-term viability and success of a product rely more on ongoing usage than on first-time use Therefore, evaluating users' intentions to continue using Kahoot! is essential for understanding its impact and benefits.
Research indicates that continued technology use can stem from a rational decision-making process influenced by perceived ease of use, usefulness, and past experiences (Bhattacherjee, 2000; Venkatesh et al., 2008) Additionally, emotional responses such as satisfaction and cognitive absorption play a significant role in this behavior (Agarwal et al., 2000; Kim et al., 2007; Zhang et al., 2006) Furthermore, habitual use may occur without intentionality, driven by automatic behavioral patterns triggered by environmental cues (Limayem et al., 2007; De Guinea & Markus, 2009).
RELEVANT STUDIES
Evaluation of continued use on Kahoot! as a gamification based learning platform from the perspective of Indonesia students.
This study evaluates Kahoot! as an effective and enjoyable learning tool for students in Indonesia during the Covid-19 pandemic The findings highlight the potential of Kahoot! to enhance student achievement through gamification elements Additionally, the study provides recommendations for educators looking to implement Kahoot! in their teaching practices.
This research highlights the potential of integrating gamification into the learning process during the Covid-19 pandemic, with a specific focus on the use of Kahoot! The findings offer valuable insights for both academics and practitioners, as they evaluate the effectiveness of Kahoot!'s gamification elements in promoting continued student engagement Additionally, the study provides practical recommendations for instructors looking to utilize Kahoot! as an effective learning support platform.
Affecting Learning Performance through the Use of Social Media in Malaysian Higher
This study focuses on the influencing factors of using social media for learning along with its active participation and influence on the academic performance of Malaysian students.
This study reveals that students' satisfaction, ease of use, and perceived usefulness of social media significantly enhance their learning, collaborative engagement, and academic performance It concludes that fostering active collaborative learning and interaction via social media enriches educational activities and promotes group discussions, suggesting that higher education institutions should encourage its use in teaching and learning processes.
Student perception of usefulness and ease using
This study focuses on examining the impact of the match between
The results indicate that the TAM model's assertion that perceptions of usefulness and perceptions of ease of use
In a tertiary education setting, a web-based tool was utilized to explore the systemic interaction with technology, particularly focusing on the Kahoot game-based learning method This study examined the conflict between learning and play, highlighting how it influences students' behavioral intentions and individual choices when engaging with the platform.
Enhancing usefulness, guidance, and reducing conflict between game and learning, will enhance students' behavioral intentions and the practical use of
User Satisfaction Study for Sustainability of YouTube
This study aims to enhance the sustainability of YouTube's quality by exploring the connections between user satisfaction, achievement, and the intention to consistently engage with high-quality, ski-related content on the platform.
This research equips YouTubers with vital information and background data on ski technology, establishes the connections between key variables, and offers inspiration for navigating unforeseen challenges, including future pandemics.
Understanding Key Drivers of Mooc
Satisfaction and Continuance Intention To Use.
This study examines the factors influencing satisfaction in Massive Open Online Courses (MOOCs) through the lens of Expectation-Confirmation Theory (ECT), highlighting how satisfaction impacts user behavior It presents a research model that illustrates the connections between validation, perceived usefulness, user interest, overall satisfaction, and the intention to continue using MOOCs.
Research results show that with ECT, usefulness, interest, and flow can enhance user satisfaction with
Our findings indicate that cognitive usefulness, cognitive interest, and the experience of flow significantly mediate the relationship between validation and satisfaction in MOOCs This study enhances existing research by examining how satisfaction influences users' referral intent, highlighting its role as a crucial factor in the intention to continue using MOOCs Ultimately, this research contributes to the understanding of the effectiveness of MOOCs based on the Expectation-Confirmation Theory (ECT).
The Use of a Mobile Learning Management
This study investigates students' acceptance of mobile online
The results showed that factors such as self efficacy, personal innovation, and system accessibility capacity had
University and Its Effect on Learning Satisfaction and Achievement. learning and its effect on academic achievement using the eTAM and ISS models
This study empirically validates a theoretical model for successful mobile learning management systems, highlighting that ease of use significantly influences user perception, while perceived usefulness directly affects behavioral intent These findings underscore the practical implications for designing and implementing online learning in new and distance education institutions Furthermore, the research thoroughly explores factors from the Technology Acceptance Model (TAM) and extended TAM (eTAM), illustrating the connections between behavioral intent, academic satisfaction, and student achievement.
Investigating and Comparing the Effects on Learning
Achievement and Motivation for Gamification
This study aims to investigate and compare the impacts on academic achievement and motivation of two
Research results suggest that game-related pedagogies can positively influence achievement and motivation for learning and that positive effects on achievement
HYPOTHESIS DEVELOPMENT
Utilizing Kahoot in educational settings highlights the significance of gamification and game-based learning Research indicates that gamification plays a more crucial role in enhancing motivation for learning compared to game-based learning These findings align with previous studies, underscoring the importance of this research in understanding effective pedagogical strategies.
2.5.1 The impact of Competitiveness (CO) on Perceived Usefulness (PU)
Competitiveness in gamification significantly influences both cognitive and emotional responses, highlighting the perceived importance of usefulness (Ames, 1984) This drive for competition motivates players to enhance their skills and performance Engaging in challenges with others encourages players to identify and cultivate their strengths to surpass their rivals, as demonstrated by Ozcelik et al.
Research from 2013 highlights that the aspects of play, competition, and challenge in video games significantly enhance players' motivation and engagement, encouraging them to invest more time in learning activities Kahoot! leverages this competitive element by allowing students to compete against each other, with points awarded based on response speed.
In 2022, research highlighted that Kahoot! is a valuable tool for players eager to enhance their skills and knowledge This platform encourages students to recognize its benefits in the learning process, leading to the proposal of hypothesis H1.
Hl: Competitiveness (CO) has a positive influence on Perceived Usefulness (PU).
2.5.2 The impact of Competitiveness (CO) on Satisfaction (SA)
Game design elements, particularly competitiveness, significantly influence user satisfaction, as noted by Sailer et al (2017) and Chang Huyn Jin (2014) Gamification incorporates competitiveness to encourage users to enhance their skills and engage with other players (Wirani et al., 2022; Bitrián et al., 2021) This drive to compete fosters strong motivation, prompting participants to strive for higher achievements and develop new skills, ultimately leading to increased satisfaction as they accomplish challenging goals Thus, we propose hypothesis H2.
H2: Competitiveness (CO) has a positive influence on Satisfaction (SA).
2.5.3 The impact of Enjoyment (EN) on Perceived Usefulness (PU)
Enjoyment serves as an intrinsic motivator that significantly impacts extrinsic motivation, such as perceived usefulness (Koo & Chung, 2014) Individuals who view a system as enjoyable are more likely to find it useful (Sun and Zhang, 2008) According to the Technology Acceptance Model (TAM) proposed by Davis et al (1992), cognitive enjoyment aligns with intrinsic motivation, which drives engagement in activities for their own sake Research comparing traditional training and game-based training methods indicates that game-based training, designed to enhance intrinsic motivation, leads to greater enjoyment and perceptions of ease of use compared to traditional methods (Venkatesh and Speier, 2000; Venkatesh, 1999).
Research indicates that enjoyment significantly influences perceived usefulness, making it a crucial factor in user acceptance of various systems and technologies Studies have demonstrated this relationship in contexts such as e-learning systems, search engines, and instant messaging Additionally, the Moodie platform research supports the notion that enjoyment serves as a determinant of perceived usefulness Consequently, we propose hypothesis H3.
H3: Enjoyment (EN) has a positive influence on Perceived Usefulness (PU)
2.5.4 The Impact of Enjoyment (EN) on Satisfaction (SA)
Koo (2009) identified enjoyment as a key motivator for online gaming, closely linked to perceived ease of use, perceived usefulness, and overall satisfaction Kahoot! enhances student engagement by integrating playful elements into the learning experience, reinforcing the importance of enjoyment in educational contexts, as supported by Trevino & Webster (1992) and Tse & Wilton.
Research indicates that higher enjoyment correlates with positive subjective experiences, such as mood and satisfaction (1988) Kahoot! incorporates gamification elements like audio, images, video, and achievement points, enabling teachers to enhance the learning experience with multimedia (Wirani et al., 2022) Studies show that enjoyment is positively linked to satisfaction (Lin et al., 2005) and leads to favorable attitudinal outcomes, including joy and satisfaction (Sandelands et al., 1983) Enjoyment serves as an intrinsic motivator, significantly affecting satisfaction in e-learning environments (S0reb0 et al., 2009; Lin et al., 2005; Shiau & Luo, 2013) The goal of fostering enjoyment is to enhance user happiness while engaging with gamified platforms (Wirani et al., 2022) Consequently, when learners find interest in their studies, creating enjoyable learning experiences can boost their achievements and overall satisfaction, leading to the proposal of hypothesis H4.
H4: Enjoyment (EN) has a positive influence on Satisfaction (SA)
2.5.5 The impact of Challenge (CH) on Satisfaction (SA)
Research by Tan Ai Lin et al (2018) highlights that challenges, such as answering questions and competing with peers, enhance learner engagement Establishing clear goals for tasks positively impacts students' perceptions of these challenges, leading to increased user satisfaction and lower dropout rates, as noted by Guo et al.
Aparicio et al (2019) suggest that certain factors can foster a stimulating environment that presents challenges, while also offering resources to address them They note that peer-reviewed tasks can be demanding for users, yet ultimately rewarding Consequently, hypothesis H5 is introduced.
H5: Challenge (CH) has a positive impact on Satisfaction (SA).
2.5.6 The impact of Satisfaction (SA) on Achievement (AC)
Numerous studies indicate that student satisfaction significantly influences academic performance (Kim et al., 2021; Lee et al., 2015; Sowan & Jenkins, 2013; Shih & Sanchez, 2006) Research highlights a strong correlation between the fulfillment of basic psychological needs and academic success (Jang et al., 2012; Skinner et al., 2008; Wang et al., 2019) Sowan et al (2013) found a notable relationship between overall satisfaction scores and achievements in distance learning, including expected course scores and material access frequency Additionally, Perez-Perez et al (2020) emphasize that satisfaction plays a crucial role in enhancing student learning performance, making it a key determinant of perceived learning outcomes Consequently, we propose hypothesis H6.
H6: Satisfaction (SA) has a positive impact on Personal Achievement (AC).
2.5.7 The impact of Satisfaction (SA) on Impact Individual (II)
Student achievement and satisfaction are crucial indicators of educational quality, with research indicating that higher satisfaction correlates with improved academic performance and self-regulated study habits in online learning environments This relationship highlights the importance of cognitive satisfaction in influencing both student behavior and academic success Furthermore, a student's satisfaction with a course significantly impacts their decision to continue or withdraw, underscoring the need for educational institutions to prioritize student satisfaction to enhance learning outcomes.
Satisfaction plays a crucial role in effective learning (Sinclaire, 2014) The use of Kahoot! fosters student satisfaction, which in turn enhances their scores, deepens their understanding of the material, encourages a positive learning environment, and boosts overall productivity Consequently, we propose hypothesis H7.
H7: Satisfaction (SA) has a positive impact on Impact Individual (II).
2.5.8 The impact of Perceived Usefulness (PU) on Continued Use (CU)
Previous studies have demonstrated that perceived usefulness has a positive impact on users' usage behavior (Grenier Ouimet et al., 2020); Lacka & Chong, 2016)
Perceived usefulness plays a crucial role in the sustained intention to utilize clinical information systems, smart devices, and health applications This notion is supported by various studies, including those conducted by Davis in 1989, Naidoo and Leonard in 2007, and Xu et al in recent years.
PROPOSED RESEARCH MODEL
The proposed research model builds upon established theoretical frameworks, including Davis's Technology Acceptance Model (1989) and Bhattacherjee's Expectation Confirmation Model of Information Systems Continuance (2001) It also integrates insights from recent studies, such as Yekti Wirani et al.'s (2022) evaluation of Kahoot! as a gamification-based learning platform from the perspective of Indonesian students, and Idowu et al.'s (2020) examination of student perceptions regarding the usefulness and ease of using Kahoot in higher education Additionally, it references T Cho's user satisfaction study focused on the sustainability of YouTube content quality, particularly in the context of ski technology.
(2023) and Investigating and Comparing the Effects on Learning Achievement and Motivation for Gamification and Game-Based Learning: A Quantitative Study Employing Kahoot by Qi Zhang et al (2022)
Research Evaluation of the continued use on Kahoot! as a gamification-based learning platform from the perspective of Indonesian students by Yekti Wirani et al.
A 2022 study examined the impact of gamification on the continued use of Kahoot!, highlighting the importance of ease of use, satisfaction, and individual impact The research found that elements such as excitement, competition, and challenge significantly enhance user engagement in a developing country context Notably, competitiveness and enjoyment were shown to positively affect the perceived usefulness of Kahoot!, while enjoyment also contributed to individual impact through satisfaction Consequently, the study anticipates that perceived usefulness, satisfaction, and individual impact will collectively enhance the continued use of Kahoot! as an effective gamified learning method, ultimately improving student learning outcomes.
The study "User Satisfaction Study for Sustainability of YouTube Content Quality: Focusing on Ski Technology" by T Cho (2023) examines the sustainability of social media by analyzing the connection between user satisfaction, perceived achievements, and the intention to continue using the platform It provides YouTube users with crucial information and foundational data, while exploring the relationships among these variables The findings suggest that higher user satisfaction and perceived performance positively influence users' intentions to keep engaging with social media.
SUMMARY
Chapter II discussed and provided theoretical foundations related to previous research on gamification factors influencing continued use intention through perceived usefulness, satisfaction, and impact on individual and personal achievement The authors have built a proposed research model with hypotheses built on background theory.
RESEARCH METHOD
INTRODUCTION
Chapter 2 lays the theoretical groundwork for the research methodology detailed in Chapter 3, which encompasses three key components: the quantitative research process and methods, relevant measurements, and the sample and survey sampling techniques.
RESEARCH PROCESS DESIGN
This study utilized quantitative research methods, employing the second generation SEM linear structural modeling technique to test a complex structural model The authors selected this approach due to the direct and indirect relationships among variables, which could result in systematic errors if multiple regression techniques were used.
Structural equation modeling (SEM) is essential for researchers aiming to explore relationships between variables through intricate modeling techniques Traditional analytical methods, including multiple regression and exploratory factor analysis, serve as foundational tools for this purpose In this study, the authors employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to enhance the accuracy of their results by reducing errors that impact the dependent variable, ultimately maximizing the R² value for improved predictive capability (Hair et al., 2016).
Data is processed and analyzed using SmartPLS, focusing on the measurement model's reliability through metrics like Cronbach's alpha, composite reliability (CR), and average variance extracted (AVE) Convergence is evaluated via external loadings, while discriminant validity is assessed using Fornell-Larcker criteria and HTMT The structural model is examined for multicollinearity using VIF, and the coefficient of determination (R²) is determined according to the research context Additionally, impact assessment is conducted with f², and predictive power is measured using Q².
The research process follows a systematic scientific approach, focusing on Kahoot! as a gamification-based learning platform to establish research metrics The authors develop an official scale, assess its reliability, and analyze the measurement and structural models They conclude by comparing their findings with existing literature, drawing conclusions, and suggesting implications for business and management Additionally, the authors acknowledge the limitations encountered during the study.
SCALES OF MEASUREMENT
This study utilizes theoretical foundations and established scales from global research to develop its framework It focuses on eight key constructs, which include Competitiveness (CO), Enjoyment (EN), and Challenge (CH).
(4) Perceived Usefulness (PU), (5) Satisfaction (SA), (6) Personal Impact (II), (7) Personal Achievement (AC) and (8) Continued use (CU).
3.3.1 Scale of the variable Competitiveness (CO)
This scale inherits the original scale of Wirani et al (2022) The scale includes 3 observed variables measured from CO1 to CO3:
COI: I feel competitive with other students when using Kahoot!.
CO2: Kahoot Platform! provides a competitive system when I'm in the game.
CO3: I want to get the highest rating using Kahoot!.
3.3.2 Scale of the variable Enjoyment (EN)
This scale inherits the original scale of Wirani et al (2022) The scale includes 4 observed variables measured from EN 1 to EN4:
ENI: I feel very happy using Kahoot!.
EN2: I feel comfortable with the processes in Kahoot!.
EN3: I'm very excited to go through the learning process with Kahoot!.
EN4: I feel great spending time studying with Kahoot! platform.
3.3.3 Scale of the variable Challenge (CH)
This scale is modified from the original scale of Wirani el al (2022) The scale includes 4 observed variables measured from CHI to CH4:
Table 2: Scale of the variable Challenge (CH)
Original observed variable and crude translation
CHI Kahoot! indicates the number of questions to be answered.
Kahoot indicates the number of questions that need to be completed.
CH2 Kahoot! provide video or image aids to help solve questions.
Kahoot has a limited number of words, causing questions and answers to be shortened and details lost.
CH3 Kahoot! Provide a time limit for answering questions.
Kahoot sets a time limit for answering questions.
CH4 I feel challenged when competing in
I find it challenging to compete on the Kahoot platform.
3.3.4 Scale of the variable Perceived Usefulness (PU)
This scale inherits the original scale Wirani et al (2022) The scale includes 4 observed variables measured from PƯ1 to PU4:
PU1: Games in Kahoot! allows me to understand more and go deeper in my studies.
PU2: Game in Kahoot! took me to the highest point.
PU3: Games in Kahoot! helps me achieve results.
PƯ4: Game in Kahoot! helps me be more proactive in studying.
3.3.5 Scale of the variable Satisfaction (SA)
This scale is inherited from the original scale of Wirani et al (2022) The scale includes 3 observed variables measured from SAI to SA3:
SAI: Generally use Kahoot! During the learning process, it gives me a feeling of satisfaction.
SA2: Kahoot! that 1 used during my studies met my expectations.
SA3: I'm very happy with the experience I've had using Kahoot!
3.3.6 Scale of the variable Individual Impact (II)
This scale is inherited from the original scale Wirani et al (2022) The scale includes 5 observed variables measured from III to IĨ5:
Ill: Kahoot! can enhance my enthusiasm to attend university.
112: Kahoot! can improve my score.
113: Kahoot! helps me understand the lesson material quickly.
114: I feel my study productivity increases when using the Kahoot! application. 115: Kahoot! very helpful for my presentation activities.
3.3.7 Scale of the variable Achievement (AC)
This scale is adapted from the original scale of Zhang el al (2022) The scale includes 5 observed variables measured from AC1 to AC5:
Table 3: Scale of the variable Achievement (AC)
Original observed variable and crude translation
ACl I believe I will receive an excellent grade in this class.
I believe that using Kahoot! Help me will receive excellent grades in class.
3.3.8 Scale of the variable Continued Use (CU)
This scale is inherited from the original scale of Wirani et al (2022) The scale
AC2 Tm certain 1 can understand the most difficult material presented in the reading for this course.
1 can understand difficult material while studying when using Kahoot!.
AC3 Tm confident I can learn the basic concepts taught in this course.
1 can understand basic concepts in the learning process using Kahoot!.
AC4 Tm confident I can understand the most complex material presented by the instructor in this course.
I can understand the most complex material presented by the instructor during my studies using Kahoot!.
AC5 Tm confident I can do an excellent job on the assignments and tests in this course.
I can successfully complete assignments and tests during my studies when using Kahoot!. includes 4 observed variables measured from CUI to CU4:
CUI: I will continue to use Kahoot! compared to offline learning methods.
CU2: If I had to choose a learning method, I would choose to use Kahoot!.
CU3: I would suggest instructors use Kahoot!.
CU4: I would suggest instructors use Kahoot!.
RESEARCH SAMPLE
Table 4: Target Audience Gender Male - Female
The research focuses on students at UEH University in Ho Chi Minh City who have utilized Kahoot! for learning To optimize costs and align with the research context, a non-probability sampling method, specifically convenience sampling, was employed to select participants.
Data was collected through online questionnaires distributed to students at UEH University via Google Forms The survey comprised two primary sections: the first gathered demographic information such as gender, course of study, and previous usage of Kahoot!, along with the reasons for its use The second section focused on evaluating the respondents' sensory experiences and overall satisfaction with Kahoot! as a gamification-based learning platform for students.
According to Comrey & Lee (1992): n = 50 is very bad; n = 100 is bad; n = 200 is fine; n = 300 is good, n = 500 is very good, n = 1000 is excellent.
According to Tabachnick & Fidell (2007): n = 300 is the appropriate number.
According to Roscoe (1974): the appropriate sample size is from 3 0 to 500.
Determining an appropriate sample size for exploratory factor analysis (EFA) in quantitative research can be challenging, especially when researchers face time constraints and lack financial support EFA, along with regression analysis, typically requires larger sample sizes to yield reliable results According to Hair Jr et al (2014), the minimum sample size for EFA is 50, with a preference for 100 or more participants The ideal observation-to-analyte ratio is between 5:1 and 10:1, where "observations" refer to valid questionnaires collected In our study, which includes 32 questions utilizing a 5-point Likert scale, we have identified 39 observed variables across different factors By applying the recommended ratios, the minimum sample sizes required would be between 160 and 320, exceeding the minimum guidelines for EFA.
Based on the recommendations of Forrest et al (1974); Comrey et al (1992); Tabachnick et al (2007) and Hair Jr et al (2014), our study will use a sample size of n
Our research focuses on students at UEH University in Ho Chi Minh City who utilize the Kahoot! application We gathered survey data through a Google Form, collecting responses from a total of 300 participants in the city between July and August 2023.
SUMMARY
Chapter 3 discusses the research methodology as well as describes how the research process was conducted From there, the authors provide a basis for building a measurement scale and an overview of the sampling formula.
RESEARCH ANALYSIS AND RESULTS
This chapter outlines the findings of a recent study, detailing the data analysis process and outlining future steps Key components include a description of the sample, an overview of the post-test research model, an explanation of the scale testing process, and the results of the multivariate regression analysis.
In Ho Chi Minh City, a study was conducted among students from UEH University, specifically from courses 46, 47, and 48, using Google Forms for data collection A total of 327 surveys were gathered, with 300 valid samples retained after thorough screenings and tests, showcasing the demographic characteristics outlined below.
Course: The sample's course ranges from 46 to above 48 Of these, 187 people
The data reveals that 57.19% of respondents belong to course 47, making it the largest group, while 15.9% are from course 46 and 26.91% from course 48 Notably, the age group of 18 to 22 years constitutes the majority, likely due to the author's strong interpersonal skills Since all authors are students from course 47 at UEH University, this connection has resulted in a predominantly homogenous sample.
The survey comprised 153 men (46.79%) and 183 women (53.21%), indicating a slight predominance of female participants Despite this, the gender ratio remains relatively balanced, providing a comprehensive perspective on the interest in using Kahoot! as a gamification-based learning platform Both male and female students demonstrated equal enthusiasm for the software, highlighting its appeal across genders.
A survey conducted among UEH University students revealed that 300 participants, representing 91.74% of the valid sample, have utilized Kahoot! for educational purposes, while 27 individuals, or 8.26%, reported never using the platform, rendering their responses invalid Consequently, the authors focused their analysis exclusively on the 300 valid responses to assess the continued use of Kahoot! among students, eliminating the invalid samples for further processing and analysis.
Table 5: Demographic characteristics of the sample Characteristic Frequency % Ratio % Accumulation
Source: Analysis results from survey data
The evaluation of the causal measurement model in this study employs key metrics including Cronbach's alpha (CA), Composite Reliability (CR), and Total Variance Extracted (AVE) According to established guidelines, CA should exceed 0.6, CR should be greater than 0.7, and AVE must surpass 0.5 to be considered acceptable.
4.3.1 Internal consistency reliability - Cronbach’s alpha
The Cronbach's Alpha reliability system assesses the association between measurements but does not indicate which surveys to discard To refine the analysis, calculating the correlation coefficient between the variable and the total can help identify and eliminate variables that do not significantly contribute to the measurement concept (Trong et al., 2005) According to Trong et al (2008), alpha values should ideally exceed 0.8, fall between 0.7 and 0.8, or be at least 0.6 for new research topics (Nunnally, 1978; Peterson, 1994; Slater et al., 1995; Trong et al., 2005) The results presented in the table below indicate that all constructs have alpha values above 0.7.
Table 6: Reliability and validity results of the measurement scales
Source: Analysis results from survey data
Construct reliability can be assessed using Cronbach's alpha and composite reliability (CR), with higher values indicating greater confidence in the measurement Both reliability metrics should ideally exceed 0.70, while values between 0.60 and 0.70 are deemed acceptable for exploratory research Values ranging from 0.70 to 0.90 are categorized as satisfactory to good Notably, composite reliability offers a more precise measure than the unweighted Cronbach's alpha, making it essential to evaluate and report CR for accurate reliability assessment (Hair et al., 2019).
Composite reliability offers a more accurate assessment of internal consistency by weighting items according to their individual loadings, often yielding higher reliability than Cronbach’s alpha However, it is important to note that extremely high reliability values, particularly those exceeding 95, can signal redundancy among items, which may compromise construct validity (Drolet et al., 2001).
In this study, the scale selection criteria was when alpha reliability was greater than 0.6 (the greater the alpha, the higher the internal consistency) (Nunnally et al.,
1994) The scale was satisfactory, as evidenced by the fact that all Cronbach's Alpha and Composite Reliability coefficients were above 0.6 and below 0.95 according to the results.
4.3.3 Convergent validity - external loadings and average variance extracted (AVE)
Convergent validity is assessed using the Average Variance Extracted (AVE), which averages the indicator reliability of a construct, reflecting the shared variance between the construct and its indicators A valid AVE value is 0.50 or higher, indicating that the construct accounts for at least 50% of the variance in its items (Hair Jr et al., 2021) In this model, all abstract variables exhibit AVE values exceeding 0.5, confirming the validity of the observed variables and scales As shown in Table 6, the convergent validity with AVE above 0.50 is accepted.
4.3.4 Discriminant Value - Heterotrait-Monotrait Criterion - HTMT
Discriminant validity assesses the uniqueness of a construct, confirmed when the average variance extracted (AVE) within a construct surpasses the variance shared among different constructs This validity ensures that measurement factors are distinct from one another To evaluate discriminant validity, the Heterotrait-monotrait (HTMT) correlation ratio is employed, which analyzes the correlation ratio between different traits compared to the correlation within the same trait of two constructs.
The article analyzes the correlation of indicators between constructs and within a construct, utilizing the HTMT criterion compared to a set threshold A HTMT value exceeding this threshold indicates a lack of discriminant validity, while a value below 0.90 confirms its presence between two reflective constructs The results presented in Table 7 show that all HTMT indexes for the variables are below 0.9, confirming that all structures maintain discriminant validity.
Table 7: Evaluation of discriminant value using HTMT
AC CH CO cu EN II PU SA
Source: Analysis results from survey data
Before testing the hypothesized model, multicollinearity assessment was performed to determine whether multicollinearity existed in the structural model.
Table 8: Collinearity statistics: Variance inflation factor (VIF) results
Source: Analysis results from survey data
(AC: Achievement, CH:Challenge ,C0: Competitiveness ,CU: Continued use, EN:Enjoyment, IIindividual impact, PU:Perceived Usefulness, SA: Satisfaction)
Table 8 shows that all indicators in this study have VIF values below the threshold of 5, indicating that our research model is free from multicollinearity issues (Hair Jr et al., 2017).
4.4.2 Path coefficients and hypothesis testing
The research teams implemented a bootstrapping method with 5,000 subsamples to validate the structural model and enhance the precision of the PLS estimates (Hair Jr et al., 2017) Key constructs examined included Perceived Usefulness (PU), Satisfaction (SA), Individual Impact (II), Achievement (AC), and Continued Use (CU).
R2 values of 0.210, 0.122, 0.093, 0.017, and 0.560 in Table 9 The next section of the following chapter will provide an explanation of the path coefficients shown in the illustration.
Figure 5: Structural model and PLS-SEM results
(AC: Achievement, CH 'Challenge ,CO: Competitiveness ,CU: Continued use, EN:Enjoyment, ỈEIndividual impact, PU'.Perceived Usefulness, SA: Satisfaction)
The analysis presented in Table 9 reveals that most hypotheses in the model are accepted, with the exceptions of H4 and H8 Specifically, Enjoyment (EN) does not significantly influence Satisfaction (SA), evidenced by a path coefficient of -0.081 and a P-value of 0.098 Furthermore, the data contradicts the expected positive relationship between Perceived Usefulness (PU) and Continued Use (CU), showing path coefficients and a P-value of 0.031 and 0.476, respectively.
In contrast, Competitiveness (CO) shows a highly positive relationship with Perceived Usefulness (PU) with a uniform path coefficient of 0.372 and P-value of 0.000 Besides, Competitiveness (CO) has a close relationship with Satisfaction (SA) (P
CONCLUSION AND RECOMMENDATIONS
The authors have established a proposed research model and formulated research hypotheses based on theoretical foundations and prior studies They effectively employed qualitative and quantitative research techniques, including group discussions, reliability testing, exploratory factor analysis, hypothesis testing, and evaluation of the research model's appropriateness.
This study investigates the factors influencing the continued use of Kahoot! among UEH university students, revealing a positive correlation between these factors and the intention to persist with the platform Despite variations from previous research, the findings align with the study's objectives, highlighting the roles of Perceived Usefulness (PU), Satisfaction (SA), Impact Individual (II), and Achievement (AC) as mediating variables The results indicate that the gamification elements of Kahoot! enhance student motivation, satisfaction, and perceived usefulness, ultimately improving learning efficiency and encouraging ongoing engagement with the platform.
Research findings indicate that Impact Individual (II) significantly influences Continued Use (CU) of the Kahoot learning platform This suggests that incorporating Kahoot into lectures enhances student engagement, motivating them to pursue higher education Additionally, the study reveals that enjoyment (EN) positively affects student satisfaction (SA) while using Kahoot These results underscore the effectiveness of gamification in education, demonstrating that Kahoot not only boosts student enthusiasm but also aligns with their expectations for an interactive learning experience.
Integrating Kahoot! into the study process significantly enhances student engagement and excitement, fostering a sense of satisfaction that encourages ongoing use of the platform The research indicates that when gamified systems align with students' goals and needs, their commitment to using gamification in learning increases Additionally, participants reported that they gained valuable knowledge and found the platform useful, reinforcing their intention to continue utilizing Kahoot! as a gamification-based learning tool at UEH University.
The study revealed that while most hypotheses were accepted, two were rejected; however, these rejections did not significantly impact UEH university students' intention to continue using Kahoot! Students who recognize the platform's usefulness for enhancing learning motivation and knowledge application are inclined to keep using it Nonetheless, some students perceive Kahoot! as less effective than anticipated, favoring traditional learning methods or personalized approaches This mismatch between expectations and performance leads to dissatisfaction, resulting in students being less likely to recommend Kahoot! for learning purposes.
This study builds upon the work of Wirani et al (2022) by introducing "Achievement" as an intermediary variable to explore its relationship with personal satisfaction and continued usage intention of the Kahoot! gamification-based learning platform While previous research has primarily focused on Satisfaction and Perceived Usefulness, this study highlights the significant and positive influence of personal achievement on students' intention to continue using Kahoot! The findings reveal that students recognize the positive impact of Kahoot! on their knowledge and skills, supporting the proposed model that includes gamification factors and intermediary variables such as Satisfaction (SA), Individual Impact (II), Achievement (AC), and Perceived Usefulness (PU) Overall, the research effectively explains the intention to continue using Kahoot!, along with all dependent variables, thereby validating the proposed model's relevance in the context of gamified learning.
This study offers a valuable theoretical insight into information systems research, particularly as Vietnam embraces technological advancements The increasing integration of technology in education is becoming a prevalent trend among students, with platforms like Kahoot and gamification (GAM) leading the way It provides comprehensive findings on the interplay between GAM, Kahoot, and the intermediary factors that influence users' intentions to continue utilizing these tools.
This study highlights the practical contributions of Kahoot! in education, revealing that Perceived Usefulness, Satisfaction, Individual Impact, and Achievement significantly influence students' intention to continue using the platform Key predictors of satisfaction with Kahoot! include the expectation of an enjoyable experience, the effectiveness of the learning process, and the confirmation of learner expectations, all of which encourage ongoing engagement with this gamification-based learning tool.
Kahoot! is a learning platform that enhances student achievement and satisfaction, encouraging continued use when it meets their expectations and provides enjoyable experiences To optimize user satisfaction, gamification designers must ensure the platform is well-constructed, focusing on features that improve information quality, perceived usefulness, individual impact, and overall achievement The information technology industry should prioritize system quality to deliver a user-friendly and engaging experience, as gamification elements significantly boost user engagement and satisfaction Continued usage and satisfaction are crucial for the success of Kahoot! and similar platforms, as integrating gamification factors into learning tools not only enhances individual productivity but also motivates organizational effectiveness Thus, gamification is essential for the ongoing success of Kahoot! and the broader landscape of educational platforms.
This study offers valuable insights into Kahoot!, benefiting both scholars and practitioners By integrating gamification elements from Kahoot! with existing theories, it assesses students' continued use of the platform Additionally, the research presents practical recommendations for instructors aiming to effectively utilize Kahoot! as a supportive learning tool.
This study explores how gamification elements in Kahoot! affect UEH university students' perceptions of Perceived Usefulness (PU), Satisfaction (SA), Individual Impact (II), and Achievement (AC), aiming to deepen the understanding of Continued Use (CU) behavior The findings provide significant theoretical implications for future research on gamification's influence on students' intentions to continue using such platforms Additionally, the study offers valuable suggestions based on the new insights gained from the research.
This study uncovers a significant relationship between Satisfaction (SA), Achievement (AC), and Continued Use (CU) in the context of Kahoot!, integrating findings from Wirani et al (2022) and Cho et al (2023) At UEH University, students are more likely to persist in using gamified learning applications like Kahoot! when they experience satisfaction, which in turn enhances their learning achievements The research introduces a new theoretical model for future studies on Kahoot!, encouraging a deeper analysis of user behavior on gamified learning platforms Additionally, it advocates for the exploration of diverse research models to assess influential variables in various relationships.
This study reveals that Satisfaction (SA) significantly influences Continued Use (CU) more than Individual Impact (II) and Achievement (AC), highlighting its role as a crucial intermediary variable for future research Additionally, Competitiveness (CO) is identified as the strongest factor affecting Satisfaction (SA), enriching the understanding of the relationships among Competitiveness, Satisfaction, and Continued Use These findings align with previous research by Hamari et al (2013) Furthermore, while Satisfaction is a potent intermediary, Perceived Usefulness (PU) appears to have minimal impact on students' continued use behavior, suggesting that future studies could benefit from focusing on other variables like Perceived Ease of Use, Social Gain, and Motivation for deeper insights and contributions to both theory and practice.
The learning platform Kahoot! incorporates various gamification factors, including Enjoyment (EN), Challenge (CH), and Competitiveness (CO), but not all significantly influence Continued Use (CU) among UEH university students Specifically, Challenge (CH) and Competitiveness (CO) demonstrate strong effects, while Enjoyment (EN) does not contribute to CU Instead, Enjoyment (EN) only impacts Perceived Usefulness (PU), which fails to adequately meet students' needs for Continued Use (CU) Future research on Kahoot! could explore replacing Enjoyment with more impactful variables, such as Autonomy Support, Achievement Visibility, or Interactivity with Peers and Lecturers.
The findings of this study indicate that integrating Kahoot! into the learning process at UEH University significantly enhances students' motivation and learning effectiveness, fostering engaged behavior and encouraging future usage Future research could build on this study by reexamining its variables or incorporating additional factors beyond Continued Use (CU) to broaden the research scope and investigate outcomes like Increased Awareness, Increased Engagement (Ourdas & Ponis, 2023), Word-of-Mouth Intention, and Higher App Ratings (Bitrián et al., 2021) Additionally, researchers may reference this study's results when exploring similar educational applications such as Duolingo, Quizlet, and Monkey Junior.