THE ROLE OF PERCEIVED USEFULNESS AND PERCEIVED ENJOYMENT IN ASSESSING STUDENTS INTENTION TO USE LMS USING 3-TUM

THE ROLE OF PERCEIVED USEFULNESS AND PERCEIVED ENJOYMENT IN ASSESSING STUDENTS INTENTION TO USE LMS USING 3-TUM Nurkaliza Khalid International Islamic University College Selangor, Malaysia. nurkaliza@kuis.edu.my ABSTRACT Today, e-learning is emerging as the new paradigm of modern education. Worldwide, the e-learning market has a growth rate of 35.6%, but failures still exist. Little is known about why many users stop their online learning after the initial experience. In order to understand the problem, this study examines undergraduate students responds to the use of e-learning. A questionnaire was used to collect data about the e-learning s quality, and the students perceived enjoyment, perceived usefulness and behavioral intention. The preliminary results from the study reveals two major findings. First, the 3-TUM model is suitable to understand students continuance intention in the context of e-learning. Secondly, perceived enjoyment was a bigger predictor to students continuance intention compared to perceived usefulness. Finally, conclusions, implications and future direction of study are also provided. Field of Research: E-learning, Behavioral Intention, 3-TUM, System Quality -------------------------------------------------------------------------------------------------------------------------------------- 1. Introduction The introduction of technology into the traditional classroom has provided teachers and students with the ability to form e-learning environment. By utilizing e-learning technology, the teacher can choose to deliver part of the course content online, and students can communicate with peers and the teacher online at any time outside the classroom. Wu, Tennyson, & Hsia (2010) stated that e- learning system utilized in classrooms can help overcome certain barriers to pure online learning. Although the initial acceptance of e-learning does have effect on its success (Bhattacherjee, 2001), there still exists questions as to why some users accept the e-learning and why others stop engaging e-learning after their initial experience (Sun, Tsai, Finger, Chen, & Yeh, 2008). E-learning systems have several names which have the same meaning; Learning Management System (LMS), Course Management System (CMS), Virtual Learning Environment (VLE), Learning Support System (LSS), Integrated Learning System (ILS) and Learning Platform (LP). Although e- learning system is probably the most commonly used term, the focus of this study will be LMS which is a recently coined term that goes beyond basic content delivery. LMS is the framework that handles all aspects of the learning process. The major roles for LMS include record keeping, planning, instruction, and assessment for student s learning. Secondary roles for LMS includes communication, general student data, instructor information, and LMS administration (Watson & Watson, 2007). As far as students are concerned, the expectations of 21st century learner are varied. Recent research by Wang & Wu(2008) argued that students who are adapted to the traditional didactic teaching methods may have problems to adjust to Web-based learning which utilizes a particular system. This is in line with the study by Oye, A.Iahad, Madar, & Ab.Rahim (2012) that stated positive perception on e-learning use is crucial. Therefore, this study focused on utilizing the 3-TUM in an 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 425

effort to elaborate the students perceptions (perceived usefulness and perceived enjoyment ) on LMS. 2. The Three-Tier Technology Use Model The 3-TUM (Three-Tier Use Model) (Figure 1) is a model that integrate multidisciplinary perspectives such as motivation, social cognitive theory (SCT), theory of planned behavior (TPB), and technology acceptance model (TAM)(Liaw, 2008). Based on the concept of 3-TUM (Three-Tier Use Model), individual attitudes toward information technology can be divided three different tiers: the tier of individual experience and/or system quality, the affective and/or cognitive tier, and behavioral intention tier. The concept proposed that the first tier of individual experience and system quality can influence the second tier. The second tier of affective and cognitive tier continues to influence the third tier which is the behavioral intention tier. This study applies the 3-TUM to understand how students use the LMS as a supplement to face-to-face learning process. The first tier: The individual characteristics and/or system quality tier The second tier: The affective and/or cognitive tier The third tier: Behavioral intention tier Figure 1: The three-tier Use Model (3-TUM) 3. The Research Model H 1 Perceived Usefulness H 3 System Quality H 5 Behavioral Intention H 2 Perceived Enjoyment H 4 Figure 2: The research model 3.1 Perceived usefulness and perceived enjoyment Perceived usefulness is users' perception of the expected benefits of LMS use. (Davis, 1989) defined perceived usefulness as the degree to which a person believes that using a particular system would enhance his or her job performance. Perceived enjoyment is defined as the extent to which the 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 426

activity or services offered by the LMS and is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated (van der Heijden, 2004). The cognitive tier in 3-TUM represented via perceived usefulness is visualized through the comprehension and retention of knowledge. In addition to the cognitive tier, another important indicator mentioned in 3-TUM is the affective tier which is represented via perceived enjoyment. The affective tier represents the attitudes that students develop about the course, the materials, and the instructor. LMS provides students with a new channel to learn and also as a supplement to their face-to-face learning. Through its use, students may learn in a self-paced and interactive way, feeling more playful and challenging. When students have positive affect about the LMS, it can be argued that they will be more likely to use the LMS while completing their courses, become more involved intellectually with the provided learning materials and also become more motivated to feel connected to other students in the class, and be more satisfied. Indeed, LMS offers students with substantial potential benefits. They can access and download lecture materials anytime, anywhere, in or out of the classroom. They can learn at their own pace. They can share aspects of learning with their classmates and instructors in different locations through collaborative andcommunity-building activities. They can also access a wide range of resources and obtain immediate feedback to correct misunderstood material. When students conceive the LMS to be useful then the students are more likely to use it and simultaneously achieve better performance in their learning. 4. Aim of Study The aims of this study were: 1) To find out the relationship between the system quality and students perceived enjoyment in using LMS. 2) To find out the relationship between the system quality and students perceived usefulness in using LMS. 3) To find out the relationship between the students perceived enjoyment and perceived usefulness with their behavioral intention in using LMS. 5. Methodology 5.1 Participants Participants were 119 students (46 males and 73 females) who voluntarily participated in this study at an academic institution in Selangor. These students were purposely selected because they indicated that they had been using LMS as a supplement to face-to-face learning for at least one semester (fourteen weeks). All participants were undergraduate students. All participants needed to answer a questionnaire that includes demographic information combined with four different components (demographic information, system quality, perceived enjoyment, perceived usefulness and intention to use more LMS as a supplement to face-to-face learning). The questionnaire with a covering letter was distributed to subjects and their responses were guaranteed confidentiality. Questionnaires with missing responses were eliminated. 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 427

Table 1: Hypothesis to be tested Hypothesis H1: LMS perceived enjoyment will be influenced by the quality of the e-learning system. H2: LMS perceived usefulness will be influenced by the quality of the e-learning system. H3: Students behavioral intention to use LMS will be influenced by the LMS perceived enjoyment. H4: Students behavioral intention to use LMS will be influenced by the LMS perceived usefulness. H5: Students perceived usefulness will be influenced by their perceived enjoyment. Relative supporting references Cheng (2012) Al-busaidi (2012) Heijden(2004) Heijden(2004) Hsu, Chang, & Chen(2012) 5.2 Instrumentation The data for this study was gathered by means of a questionnaire which included four major components. The following Table 2 indicates the measures of the study variables used in the study. The instrument items were adopted from previous studies by Pituch and Lee (2006), Lee, Cheung, & Chen (2005), Davis (1989) and Roca, Chiu, & Martínez(2006). Table 2: Instrumentation of the study variables Study Variables No. of items Source of scale Type of scale System Quality 12 Pituch and Lee (2006) 7-points Likert scale Perceived Enjoyment 3 Lee et al. (2005) 7-points Likert scale Perceived Usefulness 4 Davis (1989) 7-points Likert scale Behavior Intention 3 Roca et al. (2006) 7-points Likert scale 6. Finding & Discussion 6.1 Reliability analysis The internal consistency reliability was assessed by computing Cronbach s alpha coefficient value. The alpha coefficient value for all variables in the study revealed a range of coefficient value from.81 to.92 accordingly (Table 3). The internal consistency reliability of perceived usefulness, perceived enjoyment, and behavioral intention were found to be highly accepted and these coefficients were presented in Table 4. The values range from 0.62 to 0.87. Given the exploratory nature of the study, reliability of the scales was deemed adequate. Table 3: The overall item-total correlations Items M SD Item-total correlation System Quality 4.02 0.92 0.84 Perceived Enjoyment 3.97 1.01 0.81 Perceived Usefulness 4.04 1.07 0.92 Behavior Intention 4.16 1.07 0.91 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 428

Table 4: Item-total correlations of perceived usefulness, perceived enjoyment and behavioral intention Items M SD Item-total correlation Perceived usefulness Using the LMS improves my learning performance. 3.89 1.18 0.83 Using the LMS enhances my learning effectiveness. 4.02 1.14 0.82 Using the LMS gives me greater control over 4.02 1.28 0.87 learning. I find the LMS to be useful in my learning. 4.23 1.18 0.74 Perceived Enjoyment I find using the LMS to be enjoyable. 3.94 1.26 0.70 The actual process of using the LMS is pleasant. 3.97 1.06 0.66 I have fun using the LMS. 3.98 1.24 0.62 Behavioral Intention I will use the LMS on a regular basis in the future. 4.11 1.13 0.81 I will frequently use the LMS in future. 4.13 1.15 0.87 I will strongly recommend others to use the LMS. 4.24 1.21 0.79 The Pearson correlation coefficients among the variables were presented in Table 5. The bivariate relationships indicated that most of the variables were significantly correlated with each other and the correlation was all less than 0.80. These values signify a controlled multicollinearity among variables as mentioned by Emory & Cooper (1991). In addition, multicollinearity was also ruled out because the variance inflation factor (VIF) was less than 10. Table 5: Correlation analyses Variables 2 3 4 1. System Quality 0.52* 0.54* 0.46* 2. Perceived Enjoyment 1 0.54* 0.73* 3. Perceived Usefulness 1 0.49* 4. Behavior Intention 1 * p < 0.01. 6.2 Descriptive statistics & analysis The findings showed that the distribution of gender was higher for females with a total of 73 female respondents (61.3%). On the other hand, there were 46 male respondents or 38.7 percent out of the total respondents. Amongst the participants, 57 (47.9%) were degree students and the rest were diploma students (52.1%). Table 6: Regression results for predicted path relationships Dependent Variable Independent Variables β R2 p Perceived Enjoyment System Quality 0.52 0.27 0.00 Perceived Usefulness System Quality 0.54 0.30 0.00 Behavior Intention Perceived Usefulness 0.49 0.24 0.00 Perceived Enjoyment 0.73 0.53 0.00 Perceived Usefulness Perceived Enjoyment 0.54 0.30 0.00 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 429

For examining H1, a regression analysis was performed to check the influence of system quality on perceived enjoyment. The result show that the system quality had accounted for 27% of the variance in perceived enjoyment (F = 43.82, p = 0.00, R 2 = 0.27). For testing H2, a regression analysis was conducted to check the effect of system quality on perceived usefulness. The result show that the system quality had accounted for 30% of the variance in perceived usefulness (F = 49.27, p = 0.00, R 2 = 0.30). For examining H3 and H4, a regression analysis was performed to check the influence of perceived usefulness and perceived enjoyment on behavior intention to use LMS. The result which gave the biggest predictor variable was perceived enjoyment (F = 132.89, p = 0.00, R 2 =0.53). The result shows that perceived enjoyment accounted for 53% of the variance in behavioral intention to use LMS. For examining H5, a regression analysis was performed to check the influence of perceived enjoyment on perceived usefulness. The result show that perceived enjoyment had accounted for 30% of the variance in perceived usefulness (F = 49.06, p = 0.00, R 2 =0.30). Table 7 summarized the results of the hypotheses. Table 7: Summary of results of hypotheses Hypothesis H1: LMS perceived enjoyment will be influenced by the quality of the e-learning system. H2: LMS perceived usefulness will be influenced by the quality of the e-learning system. H3: Students behavioral intention to use LMS will be influenced by the LMS perceived enjoyment. H4: Students behavioral intention to use LMS will be influenced by the LMS perceived usefulness. H5: Students perceived usefulness will be influenced by their perceived enjoyment. Remarks 6.3 Correlation among variables There are significant correlations that are not presumed from the research model. First, the correlation between system quality and behavioral intention to use LMS is significant. This evidence provides an explanation that system quality is vital in enhancing users acceptance not only to adopt LMS but also to continue utilizing the LMS. Second, the research hypotheses in this study all have meaningful correlations (from 0.49 to 0.73). These correlations support the evidence that the research hypotheses are all highly acceptable. 6.4 The affective or cognitive measurement on behavioral intention The results in this study supported previous study (van der Heijden, 2004) that perceived usefulness and perceived enjoyment was a positive factor on behavioral intention. In this study, when users believed LMS are useful and they enjoy using the LMS then they would exhibit more behavioral intention to use more LMS during their study. 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 430

7. Conclusion and Future Recommendation Based on the 3-TUM approach, the study provides two major findings. First, system quality should be considered when understanding users attitude or usage towards LMS. Secondly, perceived usefulness and perceived enjoyment plays an important role for understanding individual intention to use LMS. This study is one of the few attempts to investigate student acceptance of LMS as a supplement to face-to-face learning. In response to the call for a holistic model explaining LMS adoption and usage, we have adopted 3-TUM to explain student acceptance of LMS. All hypotheses were found statistically significant. One significant contribution of the study is the integration of system quality with 3-TUM in the context of LMS as a supplement to face-to-face learning. The findings show that system quality plays a major role in the intention to use LMS. Therefore, a successful LMS should always consider the impact of system quality. A primary goal of utilizing LMS is to use Internet technologies to support and improve learning. This goal cannot be achieved without the active participation and involvement of students as proposed by the second tier in 3-TUM. Moreover, both affective and cognitive tiers represent different types of behavioral evoking drivers which are susceptible to different kinds of treatments. The findings shows that perceived usefulness and perceived enjoyment are found to be key drivers for the adoption and usage of LMS. The emergence of such perceptions in e-learning should be considered as a salient factor by instructors, developers and institutions in order to provide a more sustainable use of technology in the educational environment. Therefore, a successful and effective LMS should emphasize on including the components of utility and fun. This study has limitations. First, the sample was collected from one academic institution in Selangor. More studies can be conducted at several organizations in different institutions to improve the generalization of the findings. Second, the study only assess LMS intention to use from the student s perspective, future studies may assess it from instructors perspective. Third, in this study, instructors voluntarily adopt LMS to supplement the face-to-face classes. Further investigations are needed in the context of mandatory usage. Moreover, future research might also examine in detail the effects of system quality on LMS success with the help of a more established quality model. References Al-busaidi, K. A. (2012). Learners Perspective on Critical Factors to LMS Success in Blended Learning: An Empirical Investigation. Communication of the Association for Information Systems, 30(2), 11 34. Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation- Confirmation Model. MIS Quarterly, 25(3), 351 370. Cheng, Y. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361 390. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319 340. Emory, C. W., & Cooper, D. R. (1991). Business Research Methods (4th ed.). Irwin, Boston. Hsu, C.-L., Chang, K.-C., & Chen, M.-C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and E-Business Management, 10(4), 549 570. 4-5 March 2014, Kuala Lumpur, MALAYSIA. Organized by WorldConferences.net 431

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