Exploring the Online Gamified Learning Intentions of College Students: A Technology-Learning Behavior Acceptance Model

Yan, Haoqun; Zhang, Hongfeng; Su, Shaodan; Lam, Johnny F. I.; Wei, Xiaoyu

doi:10.3390/app122412966

Cited by 8 publications

(7 citation statements)

References 62 publications

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“…Additionally, perceived enjoyment is also found to be one of the antecedents of continuance use intention among HEI learners on a gamified m-learning application, as it was found to have a positive influence, supporting hypothesis H3. This also agrees with the finding by Yan et al (2022), which proved that perceived enjoyment has a significant positive influence on the student's intention to participate in an online gamified classroom. Each participation will boost their desire for further usage.…”

Section: Verification Of Th E Structural Modelsupporting

confidence: 91%

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

et al. 2023

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Aim/Purpose: The main purpose of this study is to identify the factors affecting the continuance use intention of gamified m-learning applications by Higher Education Institution (HEI) learners in Malaysia. Background: Mobile learning (m-learning) has been a popular choice among learners in HEIs due to its convenient ‘on-the-go’ concept. On the other hand, embedding gamification elements in m-learning applications help in increasing the users’ interest in continuous use. Therefore, many HEIs have invested in producing their own m-learning products apart from utilizing existing m-learning applications that are widely available online. One of the challenges faced by HEIs is the low technology usage rates towards the ‘in-house’ developed applications, which affect the receptiveness of education stakeholders in investing or maintaining educational applications. Meanwhile, the lack of continuous usage had given a negative impact on their academic-related tasks and performance. Hence, it is important to understand the significant factors that influence learners’ intentions in continuance usage of a gamified m-learning application. This will serve as an insight to the HEIs management regarding the needs and design that better suits their users’ expectations. Methodology: This study employed a correlational cross-sectional research design using an online survey. The participants of the final survey involved first-year students from one of the Malaysian public universities. For the final analysis, 269 responses were analysed using the partial least square-structural equation modelling (PLS-SEM) technique, which is a powerful multivariate analysis mechanism. The Expected Confirmation Model (ECM), which is a post-acceptance model, was extended with the pre-acceptance model named Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), to form the research proposed model that describes the continuance intention in using a gamification-based m-learning application. Contribution: This research contributes to the body of knowledge and helps better understand users’ continuance intention in the post-acceptance phase of the gamified m-learning application. It exposes information at the individual level, regarding the continuance intention of using an m-learning tool that is equipped with gamification elements. This will mostly benefit the educational resource developers in the HEIs in producing effective ‘in-house’ learning tools. Findings: This research develops a theoretical enhancement of the Expectation Confirmation Model (ECM) that affects the HEIs’ m-learning resource developers and management, dealing with IT-related behaviour. Moreover, a solid continuance usage intention conceptual model, which incorporated two important models, was also introduced. Out of all ten hypotheses, only two were not supported that are related to factors facilitating conditions and social influence. Those two factors negatively influence the HEI learners’ continuance use intention. Meanwhile, the core factors for satisfaction, which are perceived usefulness and confirmation, were found to be significant. Lastly, satisfaction was proven to mediate the positive path between perceived usefulness and the continuance intention of using the gamified m-learning application. Recommendations for Practitioners: This study offers insights into strategies that the HEIs’ management should perform in securing continuance usage of the ‘in-house’ developed m-learning products. One of the strategies could be organising technology workshops that will prepare their educators in implementing the institutions’ gamified teaching and learning tools. Another highlighted issue is regarding the need for faculties to design an effective approach to entice educators and learners towards applying new learning technologies. Recommendation for Researchers: This study contributes to the micro-level analysis of the continuance use intention of gamification-based m-learning applications by fostering the understanding of the phenomenon at the individual level. It is recommended that other researchers extend the research model by incorporating other theories, as this study was only based on two models (i.e., ECM and UTAUT2). Additionally, a longitudinal study could be another approach that enables researchers to collect much richer data that includes a wide array of background characteristics or control variables. Another suggestion would be applying related factors that may contribute to the discovery of effective gamified m-learning application designs. Impact on Society: The findings of the study show the importance of confirmation made by the applications’ users towards usefulness and usage satisfaction. Confirmation and perceived usefulness also have an increasingly similar impact on users’ satisfaction with the application and their subsequent continuance use intention. It is also revealed that easy-to-use products are commonly expected nowadays, as users might be reluctant to spend much time on them. On the other hand, for a specific gamification-based product, it is also expected by the users for it to be capable of giving an ‘enjoyable’ experience, hence motivating continuance usage. As a result, an effective gamified m-learning application or product will be able to be used by Malaysian HEI learners if the developers and stakeholders develop and evaluate the usage of their products with the consideration of the information provided by this research. Future Research: Future studies could include respondents from other diploma programmes, resulting in an in-depth analysis. It is needed to support the generalizability of the findings in this study by considering larger populations from all different programmes. In addition, similar research can be done based on different circumstances; for instance, use of the gamified m-learning application during the in-campus physical classes instead of virtual classes (online), which might influence the users’ perception in terms of the social influence and facilitating condition.

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Section: Verification Of Th E Structural Modelsupporting

confidence: 91%

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

et al. 2023

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“…Researchers have continuously upgraded and extended TAM based on TAMs such as TAM2, TAM3, UTAUT, UTAUT 2, etc. [26][27][28][29][30][31][32]. Moreover, the Robotic Architectural Technology Acceptance Model (RATAM), a new high-tech acceptance theory model for AI robot architecture design contexts, provides new insights into the future development of AI in architectural design [33].…”

Section: Introductionmentioning

confidence: 99%

Is Everyone an Artist? A Study on User Experience of AI-Based Painting System

Zhang

et al. 2023

Applied Sciences

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Artificial Intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with an AI-based Painting System (AIBPS). A questionnaire was administered to 528 Chinese participants, and validated factor analysis data and Structural Equation Modeling (SEM) were used to test our hypotheses. The findings showed that Hedonic Motivation (HM) and Perceived Trust (PE) had a positive effect (+) on users’ Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), while Previous Experience (PE) and Technical Features (TF) had no effect (−) on users’ Perceived Usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for the further extension of TAM, thus helping to improve the user experience of AIBPS. The results of this study provide insights for system developers and enterprises to better motivate users to use AIBPS.

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“…TAM is now widely used in different aspects of new technologies and confirmed that perceived usefulness (PU) and perceived ease of use (PEOU) have a significant impact on user acceptance. Researchers have continuously upgraded and extended TAM based on TAM, such as TAM2, TAM3, UTAUT, UTAUT 2, etc [26][27][28][29][30][31][32]. Although RATAM, a new high-tech acceptance theory model for AI robot architecture design contexts, provides new insights into the future development of AI in architectural design [33].To our knowledge.…”

Section: Of 22mentioning

confidence: 99%

“…These models provide system developers with a better way to control user BI [46]. For example, the Technology Acceptance Model for the Elderly (STAM) explores the acceptance of new technologies among older Hong Kong Chinese [47]; the Technology-Organization-Environment (TOE) framework combined with TAM examines the factors influencing end-user ATT and BI of AI-based technologies in construction companies [28]; the Learning Behavior Acceptance Model (T-LBAM) explores students' participation in gamified online courses intrinsic influences on willingness [26]. It is important to notice that there are many influencing factors in TAM, and these factors vary significantly across different research areas.…”

Section: Technology Acceptance Model (Tam)mentioning

confidence: 99%

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

Xu¹,

Zhang²,

Li³

et al. 2023

Preprint

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Artificial intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with the AI-based Painting System (AIBPS).A questionnaire was administered to 528 Chinese participants, using validated factor analysis data and Structural Equation Modeling (SEM) was used to test the hypotheses. The findings showed that hedonic motivation (HM) and perceived trust (PE) had a positive effect (+) on users' perceived usefulness (PU) and perceived ease of use (PEOU), while previous experience (PE) and technical features (TF) had no effect (-) on users' perceived usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for further extension of TAM, thus helping to improve the user experience of AIBPS. The results of the study provide insights for system developers and enterprises to better motivate users to use AIBPS.

show abstract

Exploring the Online Gamified Learning Intentions of College Students: A Technology-Learning Behavior Acceptance Model

Cited by 8 publications

References 62 publications

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

Is Everyone an Artist? A Study on User Experience of AI-Based Painting System

Everyone's an Artist? Exploring User Acceptance of AI-Based Painting Systems

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