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Students’ Acceptance of the i-Teacher e-Learning System

Students’ Acceptance of the i-Teacher e-Learning System
Based on Technology Acceptance Model

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  • 2nd International Malaysian Educational Technology Convention Students’ Acceptance of the i-Teacher e-Learning System Based on Technology Acceptance Model Kathy Belaja, Foo Kok Keong, Hanafi Atan, Omar Majid, Zuraidah Abdul Rahman School of Distance Education, Universiti Sains Malaysia kathybelaja@gmail.com Abstract Nowadays, many tertiary education institutions have been adopting the Learning Management System (LMS) in the course delivery and course management. Compared to secondary education institutions, LMS has never been utilized at secondary level school yet. Moreover, studies on the users’ acceptance towards this system has not been measured and understood thoroughly. Hence, this paper illustrates a proposed research framework to investigate the degree of acceptance among the secondary school students in the use of Learning Management System (LMS) as a support system to the conventional classroom teaching and learning. Technology Acceptance Model will be used as the main theoretical framework in this study. A number of 500 higher-secondary school students will serve as the research sample for this study. The sample will be exposed to the i-Teacher e-Learning System and will be required to give responses by answering a set of scales measuring Perceived Ease of Use, Perceived Usefulness, Behavioural Intentions, Attitude Towards Using and Actual Use. Data collected will be analyzed using the Correlation Analysis method. It is expected that the i-Teacher e-Learning System will show positive relationships between the variables in using the system. The future findings of this research will serve as supportive evidence on the usage of LMS in secondary school. Introduction Research Background & Problem Area In the field of education, the internet-based technologies usage for learning has been proven a great success due to its potential to integrate various types of media (such as sound, video, graphics, text, etc.) and to be delivered in various forms, such as collaboration, interaction, simulation, etc. (Saade, Nebebe, & Tan, 2007). Hence, various new technologies start to exist and developing drastically to support the development of online education by providing effective instructional models and software programs to assist teaching and learning. Although, several researchers mentioned that the scenarios of non- utilization of instructional technology by educators are not uncommon (Alias & Zainuddin, 2005). This phenomenon contributes to the factor where students are not ready to make the most of the new technology in their knowledge acquiring process. Therefore, studies on students’ acceptance towards utilizing new educational technologies in their learning should be done for the benefit of continuous development of knowledge and the technology. Learning Management System (LMS) The Learning Management System (LMS) is a software application or web-based technology used to plan, implement and assess a specific learning (Atan et al., 2008). The benefits include automated administration, tracking and reporting of events. LMS also serves as an effective tool in educational perspective to assemble and deliver personalized learning contents on a scalable web-based platform. Currently, most tertiary educational institutions employ the LMS as a platform to support the teaching and learning process. The LMS allows the instructors to manage their courses and exchange information with students, especially for the courses that in most cases that are conducted for several weeks. Most of the LMS are user-friendly and flexible where the instructors can create and deliver their course content, monitor their students’ participation and evaluate their performance online at the comfort from the office or at home. As for the students, they can get the first hands on notes and assignment questions just at the click of a finger. Collaborations effectively occur among the lecturers and the students in the learning platform. This technology, however, has never been applied in secondary level schools in Malaysia. Therefore, interest arises to study the suitability of the LMS to be implemented in secondary level school.
  • 2nd International Malaysian Educational Technology Convention Pedagogical Agent (PA) Pedagogical Agent (PA) are animated life-like characters designed to facilitate and support human learning in an interactive computer-mediated learning environments (Johnson & Rickel, 2000). The PA best serve as the cognitive tool that manages large amount of information, and plays the role as the pedagogical expert and create programming environment for the learners (Atan et al., 2008). PA’s role as a representative of human tutor with the character of a mentor has been proven to improve students’ performance and motivation significantly (Baylor & Kim, 2004). Pedagogical Agent-Based Learning Management System (PALMS) The interactive PA and content-rich LMS has the potential to cater unlimited numbers of learners and providing individualized instructions. Therefore, PALMS is created as a new instructional method and technology which incorporate Pedagogical Agent (PA) in the Moodle open source LMS (Atan et al., 2008). The i-Teacher is a platform developed by adopting the concept of PALMS in e-learning which serves as an alternative solution and method for the teaching and learning of science and mathematics. The 3-D human appearance display exhibits the role of a teacher who gives guidance and feedbacks on the course content. These feedbacks on the course contents are designed based on common questions asked by students in the actual classroom setting. Students are able to experience the authentic learning environment with the high degree of human appearance in the e-learning system. The well designed latest SPM syllabus courseware with colorful graphics, links to multimedia and interactive learning tools incorporated in i-Teacher would motivate the students to learn the instructional materials. Figure 1 below shows a screen display of the i-Teacher e-Learning System. Figure 1. A screen display of a Pedagogical Agent-Based Learning Management System (PALMS) Literature Review Technology Acceptance Model (TAM) TAM model (Davis, 1989) was developed to explain user behavior on using a new technology. The TAM is an adaptation of the Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975) to explain and predict the behavior of organizational members in specific situation. The TRA is adapted by TAM model to identify the general factors that influence users’ acceptance and their behavior towards specific Information System or Information Technology (IS/IT). Five fundamental variables or constructs to determine user’s acceptance towards PALMS are as below: 118
  • 2nd International Malaysian Educational Technology Convention Perceived Usefulness (PU): The degree to which an individual believes that using a particular system would enhance his or her job performance (Davis, 1980, 1989). Perceived Ease of Use (PEU): The degree to which an individual believes that using a particular system would be free of physical and mental effort (Davis, 1980, 1989). Attitude Towards Using (ATU): The degree of evaluative effect (Fishbein & Ajzen, 1975) that an individual associates with using the target system in his or her job (Davis, 1980). Behavioral Intention (BI): A measure of the strength of one’s intention to perform a specified behavior (Fishbein & Ajzen, 1975). Actual Use (AU): An Individual’s actual direct usage of the given system in the context of his or her job (Davis, 1980) in which the use is a repeated multiple-act behavioral criterion (Fishbein & Ajzen, 1975). According to Davis, the two main factors that caused people to accept or reject information technology are perceived usefulness and perceived ease of use. Perceived usefulness is also been seen as being directly influenced by perceive ease of use. TAM suggests that the actual use of the system is determined by the users’ behavioral intentions to use the system, which in turn jointly determined by the users’ attitude towards using the system and their perceived usefulness (Davis, Bagozzi, & Warshaw, 1989). Based on this study, the variables were defined as below: PU: The degree to which students believes that using PALMS would be useful in his or her learning. PEU: The degree to which students believes that learning in PALMS would be user-friendly. ATU: The degree of students’ evaluative effect towards using PALMS. BI: Student’s intention to utilize PALMS. AU: Repeated actual direct usage of PALMS in learning by students. The initial TAM model (Davis et al., 1989) is given in Figure 2 below. Perceived Usefulness (PU) Attitude Behavioral External Towards Actual Use Intentions Variable Using (AU) (BI) (ATU) Perceived Ease of Use (PEU) Figure 2. Technology Acceptance Model (TAM) Research Framework Research Objectives & Questions 119
  • 2nd International Malaysian Educational Technology Convention A proposal of utilizing PALMS in secondary level schools in Malaysia as a complement to the conventional classroom teaching and learning was made by i-Teacher e-learning system. Therefore, the objective of this study is to understand and predict the acceptance and utilization of higher secondary level students towards PALMS in learning science and mathematics subjects. In undertaking this study, the following research questions were put forward: a. Is PALMS accepted among secondary level students for learning of science and mathematics? b. What are the factors influencing students’ acceptance towards PALMS? c. Is the PALMS suitable to be implemented in teaching and learning in secondary level schools? Research Hypotheses Drawing upon the literature and based on the present research context, the proposed hypotheses were as follow: Hypothesis 1 (H1): There will be a strong and positive relationship between perceived ease of use (PEU) and perceived usefulness (PU). Hypothesis 2 (H2): There will be a strong and positive relationship between perceived ease of use (PEU) and attitude towards using (ATU). Hypothesis 3 (H3): There will be a strong and positive relationship between perceived usefulness (PU) and attitude towards using (ATU). Hypothesis 4 (H4): There will be a strong and positive relationship between attitude towards using (ATU) and behavioral intentions (BI). Hypothesis 5 (H5): There will be a strong and positive relationship between behavioral intentions (BI) and actual use (AU). Hypothesis 6 (H6): There will be a strong and positive relationship between perceived usefulness (PU) and behavioral intentions (BI). Figure 3 below summarizes all the aforementioned formulated hypotheses. With such model, the factors influence the acceptance of technologies based on PALMS by students will be indentified. H6 PU H3 H4 H5 AU H1 ATU BI H2 PEU PU = Perceived usefulness, PEU = Perceived ease of use, ATU = Attitude towards using, BI = Behavioral intention, AU = Actual use Figure 3. The Research Framework Methodology Research Sample 120
  • 2nd International Malaysian Educational Technology Convention This study proposed a number of 500 secondary school students from several institutions in Malaysia as the research sample. Random sampling will be used to select samples from the database of i-Teacher. Research Instruments Scales of perceived usefulness, perceived ease of use, attitude towards using and behavioral intentions were adapted from TAM (Davis, 1980) will be appropriately modified specifically for PALMS context. The reliability of the scales and the internal consistency will be determined using Cronbach’s alpha coefficient analisis (Cronbach, 1951). The questionnaire will be assigned and responded after the students had used the i-Teacher e-Learning System for a period of 6 months. Research Procedures Figure 4 below shows the flow chart of the proposed research procedure. The research procedures are divided into four main phases. In first phase (sample enrolment), students from different educational institutions will enroll in the courses provided in i-Teacher e-Learning System early of the academic year. In second phase (system utilization), students will utilize the i-Teacher for their learning of science and mathematics in school or at home for 6 consecutive months. Teaching and learning process will be conducted in the online platform. Later, in the third phase (data collection), the sample is required to give responses by answering a set of scales measuring PEU, PU, ATU, BI and AU. The final phase (data analysis), the relationships between PEU, PU, ATU, BI and AU will be investigated using Pearson product-moment correlation-coefficient in the Statistical Package for the Social Sciences (SPSS) for Windows version 13.0. The findings will then be reported. Sample (n = 500) Phase 1 Enrolment of students into courses in i-Teacher e-Learning System Learning in i-Teacher e-Learning System Phase 2 (6 months) Answering and responding on Phase 3 technology acceptance scales Data analysis (SPSS) Phase 4 Reporting Figure 4. Proposed Research Procedures Expected Outcomes The relationship between the variables (PEU, PU, ATU, BI and AU) will be investigated using Pearson product-moment correlation-coefficient. The expected results are as follows: 121
  • 2nd International Malaysian Educational Technology Convention 1. There is a strong, positive relationship between perceived ease of use (PEU) and perceived usefulness (PU). 2. There is a strong and positive relationship between perceived ease of use (PEU) and attitude towards using (ATU). 3. There is a strong and positive relationship between perceived usefulness (PU) and attitude towards using (ATU). 4. There is a strong and positive relationship between attitude towards using (ATU) and behavioral intentions (BI). 5. There is a strong and positive relationship between behavioral intentions (BI) and actual use (AU). 6. There is a strong and positive relationship between perceived usefulness (PU) and behavioral intentions (BI). Conclusion This paper has presented a review of literatures, research framework and methodology to study students’ acceptance towards PALMS. This systematic research of technology acceptance proposes a new e- learning system, PALMS, to be implemented at secondary level schools. Besides, this study will identify the factors influencing the acceptance and employment of the technology in education. This study will also provide supportive evidence on the suitability of operating the LMS in secondary schools. References Alias, N.A. & Zainuddin, A.M. (2005). Innovation for Better Teaching and Learning: Adopting the Learning Management System. Malaysian Online Journal of Instructional Technology, 2(2), pp. 27-40. Atan, H., Foo, K.K., Aris, B., Wong, S.L., Majid, O. & Rahman, Z.A. (2008, 2-4 July). The Different Roles of Pedagogical Agents in the Open Source Learning Management System. Paper presented at the Conference of Excellence in Education 2008, Paris, France. Baylor, A.L. & Kim, Y. (2004). Pedagogical Agent Design: The Impact of Agent Realism, Gender, Ethnicity, and Instructional Role. Paper presented at the Workshop on "Social and Emotional Intelligence in Learning Environments," held at the International Conference on Intelligent Tutoring Systems, Maceió, Brazil. Cronbach, L.J. (1951). Coeeficient Alpha and the internal Structure of Tests. Psychometrika, 16(3), pp. 297-334. Davis, F.D. (1980). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology. Davis, F.D. (1989, September). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, pp. 318-340. Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research: Addison-Wesley Publishing Company. Johnson, W.L. & Rickel, J.W. (2000). Animated Pedagogical Agent: Face-to-Face Interaction in Interactive Learning Environments. International Journal of Artificial Intelligence in Education 2000, 11, pp. 47-78. Saade, R.G., Nebebe, F. & Tan, W. (2007). Viability of the "Technology Acceptance Model" in Multimedia Learning Environments: A Comparative Study. Interdisciplinary Journal of Knowledge and Learning Objects, 3, pp. 175-184. 122