International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol. 15, No. 17, 2021 Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for Learning Physics https://doi.org/10.3991/ijim.v15i17.23731 Lisana Lisana(*), Marcellinus Ferdinand Suciadi University of Surabaya, Surabaya, Indonesia lisana@staff.ubaya.ac.id Abstract—This study explores the determinants that influence the acceptance of mobile learning, with a case study of a 3D simulation Android app, as an innovative tool for learning physics for high school students. The research model is developed based on prior studies in mobile learning acceptance, where Perceived Usefulness and Perceived Ease of Use are the two most popular deter- minants, with the addition of Perceived Enjoyment. Data are collected through questionnaires distributed to 50 high school students using Google Form. This study uses the structural equation modeling (SEM) technique to conduct the final analysis. The findings confirm that Perceived Enjoyment becomes the most influencing factor considered by high school students to use mobile learning, 3D simulation Android app, followed by Perceived Usefulness. However, the Perceived Ease of Use is an insignificant predictor that influences the acceptance of the 3D simulation Android app. Keywords—m-learning, 3D-simulation, android 1 Introduction Nowadays, mobile devices seem to become an inseparable part of human life. Mobile technology with internet connectivity has been evolved and increased convenience for its users due to its diverse functionality. A survey reported that in January 2021, there were 202.6 million (73.7% of the total population) internet users in Indonesia [1]. Furthermore, 96 percent of the internet users in Indonesia were using mobile phones [2]. Therefore, Indonesia has become one of the fastest-growing mobile app markets globally. Indonesian publishers had produced 47,573 mobile apps, which are prioritized on apps rather than game development, with the percentage of app and games are 89% and 11%, respectively [3]. The mobile phone functionalities are not only for communication but also for learn- ing purposes, commonly referred to as mobile learning (m-learning). Mobile phones have become an essential device to create innovative learning methods, self-exploratory learning outside the classroom, problem-solving, and enhancing student’s academic performance [4]. A recent study showed that incorporating multimedia and use of iJIM ‒ Vol. 15, No. 17, 2021 205 https://doi.org/10.3991/ijim.v15i17.23731 mailto:lisana@staff.ubaya.ac.id Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… touchscreens on mobile phones into learning can be performed to as early as kinder- garten and primary school students to enhance their skills in an engaging environment, as well as increasing their motivation on the subject, compared to traditional teaching methods [5]. Thus, m-learning becomes an essential part of academic society. During the Covid-19 pandemic, students or learners have to switch their learning method from face-to-face to online learning using mobile devices as the main tools. As a part of m-learning, mobile app usage has also been investigated as an innova- tive tool to achieve the student’s cognitive level in physics learning [6]. The high school students can be categorized as Generation Z (Gen Z), that prefer to use the mobile phone to perform their daily activities [7]. Furthermore, Gen Z students are more attracted to multimedia, especially 3D simulation, when they learn something. This condition might happen because they are raised in a technology-savvy environment [8]. A prior study also argued that 3D simulation could produce a powerful immersive envi- ronment so learners can gain knowledge and create higher-level thinking skills [9]. Unfortunately, the adoption of m-learning in education is still considered slow [10]. There are also limited studies in m-learning acceptance that focused on the usage of 3D simulation mobile app. A literature review study conducted by Reisoğlu et al. found that the percentage of research in using the 3D virtual learning environment in science subjects is still less than ten percent [11]. Therefore, this study is expected to fill this gap by investigating the determinants that influence high school student’s intention to adopt m-learning, specifically a 3D simulation Android app. The application is developed to create student’s understanding of the concept in physics. The results provide the theoretical contribution due to the limited studies that explored the factors that significantly affect the adoption of 3D sim- ulation mobile app in the education field, especially in science subjects. Furthermore, the findings can be used by mobile application developers as a guideline to develop a successful mobile app, especially in education fields using 3D technology. 2 Literature review There are various definitions related to m-learning. In general, m-learning com- bines mobility with the electronic learning (e-learning) concept. Wang et al. [12] defined m-learning as using mobile devices to deliver learning materials to learners through wireless internet anytime, anywhere. Crompton [13] referred to m-learning in terms of accessibility and flexibility since learners can learn across multiple contexts using their personalized electronic devices. In this study, the definition of m-learning refers to student’s ability to perform learning activities anytime, anywhere using their internet-enabled mobile devices through wireless technology. The research in m-learning has increased in the last decade since the emergence of smartphones and other internet-enabled mobile devices. Mobile technology has sup- ported the strategic goals in the education field by enhancing student’s participation and achievements and improving the collaboration and interaction among students [14]. Some authors had examined the factors that influence m-learning adoption among students in various countries such as New Zealand [15], China [16], Jordan [17], and Sweden [18]. A study conducted in Greece showed that preschool teachers generally 206 http://www.i-jim.org Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… welcome ICT usage, particularly m-learning, in their daily teaching, regardless of age and gender [19]. One popular model in adopting new innovative technology is TAM (Technology Acceptance Model), proposed by Davis [20]. TAM suggested two variables, Perceived Usefulness and Perceived Ease of Use, which determined the attitude toward using technology that affects the Behavioral Intention. Many prior studies used TAM in their theoretical model to explore user acceptance of m-learning [17], [21]. Several authors used extended TAM in their theoretical model by adding some essential determinants to increase the explanatory power of the research. Some studies confirmed that Perceived Enjoyment was another crucial predictor that significantly influences m-learning adoption [9], [22]. 3 Methodology This study is a quantitative research that uses a cross-sectional survey to obtain data based on the individual’s experience using a 3D simulation Android app. A two-part self-administered questionnaire is then developed based on prior studies to maintain the content validity. The first part is related to the respondent’s characteristics (age, gender, and education). The second part contains questions associate with each variable used in the research model. The instruments are adopted from the existing studies in m-learning adoption measured using a 5-point Likert scale, ranging the options from Strongly Disagree to Strongly Agree. The measuring instruments are listed in Table 1. Table 1. Instruments of Variables Variable [Ref] Measuring instrument Perceived Usefulness [14] 3D simulation Android app is useful in my learning 3D simulation Android app enables me to perform learning activities more quickly 3D simulation Android app increases my learning productivity 3D simulation Android app will increase my chances to get a better grade Perceived Ease of Use [23] The interaction of 3D simulation Android app is clear and understandable It is easy to become skillful at using 3D simulation Android app 3D simulation Android app is easy to use It is easy for me to learn how to operate 3D simulation Android app Perceived Enjoyment [21] I believe that using 3D simulation Android app will be interesting to me I believe that 3D simulation Android app will stimulate my curiosity I believe the use of 3D simulation Android app will fit well with the way I like to study I believe that using 3D simulation Android app can solve my problems Behavioral Intention [14] I intend to use 3D simulation Android app in the future Given the opportunity, I will use 3D simulation Android app I plan to use 3D simulation Android app in the future I predict I would use 3D simulation Android app in the future iJIM ‒ Vol. 15, No. 17, 2021 207 Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… Since the purposive sampling method is applied, the questionnaire was distributed to the targeted respondents from high schools located in two cities in Indonesia. Next, a preliminary analysis of the final data is addressed to examine the validity and reliability of the constructs. Component factor analysis is used to ensure the validity of all constructs, while the reliability of instruments is established using Cronbach’s alpha coefficients. The final analysis is conducted by using structural equation modeling (SEM) developed in SmartPLS. Meanwhile, the 3D simulation Android app is developed as a tool to support the study. All user interfaces are designed with the user-centered design principle proposed by Rogers et al. [24] to ensure the Android app will be user-friendly, intuitive, and inter- active. The 3D simulation Android app is developed using Unity 5.6 and then packaged into an Android app. 4 The development of research model and hypotheses A research model is developed based on existing studies in m-learning acceptance. Perceived Ease of Use was defined as the degree of difficulty when an individual uses m-learning [20]. The easier an m-learning application to be used by the students, the higher their intention to accept it. Many authors argued that Perceived Ease of Use effectively influences the Behavior Intention in adopting the m-learning [22], [25]. However, studies of Chao [26] and Hamidi [27] declared that the impact of Perceived Ease of Use on Behavior Intention was insignificant. Meanwhile, most studies in m-learning usage showed the high significance of Perceived Ease of Use on Perceived Usefulness, yet a study by Saroia and Gao [18] showed otherwise. Therefore, this study proposes the following hypotheses: H1: Perceived Ease of Use significantly affects the Behavioral Intention to use m-learning (3D simulation Android app). H2: Perceived Ease of Use significantly affects the Perceived Usefulness related to m-learning (3D simulation Android app usage). Perceived Usefulness refers to an individual’s belief that using m-learning would enhance his or her job performance [20]. Students have more willingness to accept m-learning if it offers some benefits for them. Usefulness was found to be the most sig- nificant predictor of a user’s intention to use m-learning [14], [22], [25]. Another study reported there was no significant impact of Perceived Usefulness on Behavior Intention [27]. Thus, the following hypothesis is proposed: H3: Perceived Usefulness significantly affects the Behavioral Intention to use m-learning (3D simulation Android app). Perceived Enjoyment was defined as the degree of an individual’s perception that using m-learning will be enjoyable [14]. The more enjoyable mobile learning is, the higher student’s willingness to use it. The significance of Perceived Enjoyment on the 208 http://www.i-jim.org Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… intention of m-learning usage had been proved by several studies [14], [26]. Therefore, the following hypothesis is proposed: H4: Perceived Enjoyment significantly affects the Behavioral Intention to use m-learning (3D simulation Android app). Behavioral intention refers to the individual’s intention to perform a specified behav- ior that has an effect on the actual usage [23]. Figure 1 depicts the research model used in this study which incorporates three determinants: Perceived Usefulness, Perceived Ease of Use, and Perceived Enjoyment, that may affect an individual’s intention to adopt the 3D simulation Android app. Perceived Usefulness Behavioral Intention Perceived Ease of Use Perceived Enjoyment H1 Fig. 1. Research model 5 Results and discussion As the target respondents, high school students have to install the 3D simulation Android app on their smartphones. Students may interact with the Android app, play with the provided simulations, and immediately see the results. Next, they were given a set of tasks to perform in a certain period. After completing all tasks, they have to fill in the questionnaires through Google Forms. The total participants were 50 respondents, 32 males, and 18 females. Table 2 shows that the validity of all constructs is satisfactory since all loading val- ues are above 0.4, based on Straub et al. [28] guidelines. The Cronbach’s alpha values of all variables also exceeded the acceptable value of 0.7, following the guidelines from George and Mallery [29]. In addition, both composite reliability (CR) and average vari- ance extracted (AVE) are computed to check the composite reliability and convergent validity of each latent variable. The result shows that the values of CR are greater than the minimum threshold values of 0.7, and all AVE values for all the latent variables are also above 0.5, as suggested by Fornell and Larcker [30]. iJIM ‒ Vol. 15, No. 17, 2021 209 Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… Table 2. Validity and reliability result Variable Indicator Loading Cronbach α Result CR AVE (√AVE) Perceived Enjoyment PE2 0.857 0.890 Good 0.923 0.751 (0.866) PE1 0.852 PE4 0.885 PE3 0.871 Perceived Usefulness PU2 0.872 0.869 Good 0.911 0.718 (0.847) PU3 0.872 PU4 0.811 PU1 0.832 Perceived Ease of Use PEU3 0.824 0.834 Good 0.887 0.664 (0.815) PEU2 0.895 PEU4 0.796 PEU1 0.737 Behavioral Intention BI2 0.814 0.840 Good 0.891 0.671 (0.819) BI4 0.763 BI1 0.811 BI3 0.884 Next, to ensure the model variables can be analyzed using SEM, this study performs the descriptive data analyses. Based on the results presented in Table 3, all variables are satisfactory since the values of the magnitudes of skewness and kurtosis for all indicators are within the acceptable limits of 3 and 7, respectively, following Kline [31] criteria. Table 3. Descriptive statistics Indicator Mean Median Min Max Stand Dev Kurtosis Skewness PE1 4.020 4.000 2.000 5.000 0.707 0.132 –0.380 PE2 4.180 4.000 3.000 5.000 0.517 0.296 0.221 PE3 3.900 4.000 3.000 5.000 0.640 –0.525 0.094 PE4 4.040 4.000 3.000 5.000 0.599 –0.114 –0.015 PU1 4.400 4.000 4.000 5.000 0.490 –1.900 0.421 PU2 4.220 4.000 3.000 5.000 0.642 –0.623 –0.243 PU3 3.980 4.000 3.000 5.000 0.678 –0.783 0.025 PU4 3.860 4.000 3.000 5.000 0.600 –0.249 0.067 PEU1 4.020 4.000 3.000 5.000 0.510 1.065 0.034 PEU2 3.880 4.000 3.000 5.000 0.621 –0.389 0.088 PEU3 4.020 4.000 2.000 5.000 0.648 1.016 –0.475 PEU4 4.000 4.000 3.000 5.000 0.600 –0.116 0.000 BI1 4.420 4.000 3.000 5.000 0.533 –1.156 –0.078 BI2 4.080 4.000 3.000 5.000 0.523 0.729 0.100 BI3 4.260 4.000 3.000 5.000 0.482 –0.371 0.563 BI4 4.260 4.000 3.000 5.000 0.522 –0.300 0.217 210 http://www.i-jim.org Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… T-tests are used to investigate whether there are significant differences between the mean values of a latent variable and the neutral value of 3. The result indicates that all mean values are above the neutral value of 3 at a level of 0.05 or less. Furthermore, the fit statistics of the research model show that the variance of the intention to adopt a 3D simulation mobile app is 48.5% that indicates good explanatory power. Table 4 presents the result of the hypotheses. The shaded cells correspond with the three supported hypotheses. Perceived Enjoyment significantly influences the student’s intention at a level of 0.001 (***). It means that students are willing to use the 3D simulation Android app only if they enjoy using it. This finding aligns with a study conducted by Pramana [14] and Chao [26]. Perceived Usefulness also significantly influences the intention to use the 3D simulation Android app at a level of 0.05 (*), which supports several prior studies [14], [22], [25]. Surprisingly, Perceived Ease of Use does not significantly impact the Behavioral Intention at a level of 0.05 or less. This means that high school students place less importance on Perceived Ease of Use as a motivation for accepting 3D simulation Android app. One factor that we argue might influence this result is the behavior of Generation Z students, which are already familiar with technologies from their youth days [7], so they can use complex Android app. This result fits with Chao’s and Hamidi’s studies [26], [27]. However, the outcome might be different if the 3D simulation Android app users are more general, not limited to Generation Z students only. Another finding proves the influence of Perceived Ease of Use on Perceived Usefulness at a level of 0.01 (**) as many other studies have proven this hypothesis. Table 4. Hypotheses test Hypothesis Original Sample Sample Mean Stand Dev T Statistics P Values Decision H1 PEU→BI –0,155 –0,149 0,155 0,997 0,319 Rejected H2 PEU→PU 0,345 0,366 0,116 2,961 0,003 Accepted H3 PU→BI 0,308 0,310 0,122 2,523 0,012 Accepted H4 PE→BI 0,529 0,530 0,109 4,837 0,000 Accepted 6 Conclusion The study finds that Perceived Enjoyment is the strongest factor influencing the student’s intention to use the 3D simulation Android app, followed by Perceived Use- fulness. Surprisingly, the Perceived Ease of Use factor does not significantly affect the acceptance of the 3D simulation Android app. This study concludes that high school students are willing to adopt the 3D simulation Android app since it can help them in learning physics (Usefulness) by working on the problems and playing with the simu- lations (enjoyment). Besides having theoretical contribution, this study is expected to have a practical contribution to mobile app developers (especially Android app) who want to develop an educational app for mobile learning. They have to provide the stu- dents with useful mobile app content and 3D simulation to make an enjoyable mobile app for students to complement their studies. iJIM ‒ Vol. 15, No. 17, 2021 211 Short Paper—The Acceptance of Mobile Learning: A Case Study of 3D Simulation Android App for… 7 Limitations and future research There are some limitations to this study. This study is conducted in Indonesia with all respondents from Indonesia, so the findings may not apply to other countries nor education in general. Due to the limited number of respondents (50 respondents), fur- ther study may be needed with more respondents and different groups of respondents, which can yield different results. 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Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, vol. 18, no. 1, 1981, doi: https://doi.org/10.2307/3151312 [31] R. B. Kline, Principles and practice of structural equation modeling. Guilford publications, 2015. 9 Authors Lisana Lisana is a lecturer at the Department of Informatics, University of Surabaya, Indonesia. She is a PhD candidate at Vincent Mary School of Science and Technol- ogy, Assumption University, Thailand. She got a Bachelor degree in Computer Science from Sekolah Tinggi Teknik Surabaya, Indonesia and a Master degree in Information Technology from Swinburne University, Australia. Email: lisana@staff.ubaya.ac.id. Marcellinus Ferdinand Suciadi is a Lecturer at the Department of Informatics, University of Surabaya, Indonesia. He was graduated from the same department and continued his study at the School of Computing, National University of Singapore, Singapore. Email: ferdi@staff.ubaya.ac.id. Article submitted 2021-05-04. Resubmitted 2021-07-04. Final acceptance 2021-07-06. Final version published as submitted by the authors. 214 http://www.i-jim.org https://doi.org/10.2307/3151312 mailto:lisana@staff.ubaya.ac.id mailto:ferdi@staff.ubaya.ac.id