Analysis of Students Factors Influencing the Integration of E-Learning in Higher Education. Case Study:University of Tetovo (European Journal of Formal Sciences and Engineering, 2019)
E-Learning is an Important tool for delivery, interaction, and facilitation of both teaching and learning processes in higher education. The purpose of this paper is the investigation of students attitudes about the use of ICT and integration of e-learning at the University of Tetovo. This study also examines the factors contributing to students attitudes towards E-Learning as well as identifying the important factors to its successful integration. The conceptual research framework of e-learning integration, which is used in the analysis, is based on the technology acceptance model (TAM). The research developed an extended TAM model (Technology Acceptance Model for E-learning) for predicting the intention to integrate E-Learning using the constructs of the TAM. Statistical analysis was conducted to assess student attitudes towards integrationof e-learning, and to analyses the relationships between their attitudes and their demographic characteristics, Perception about ICT,ICT experience and ICT Competence that predict the integration of e-learning. Questionnaire was used to collect data from a sample of 314 undergraduate students from different program studies. Statistical techniques are used for the analyses of data. Factor analysis was used to validate the instrument, however; the partial least square method was used to test the model for the study, moreover; stepwise regression analysis were used to test the hypotheses of the study. The findings indicate that students have an important role in prediction of the integration of E-Learning in University of Tetovo. The reported findings might be of interest to institution, academics administrators, and decision-makers involved in planning, developing and implementation of e-learning in University of Tetovo and similar universities in developing countries.
Keywords: Atittude, TAM, ICT competence, ICT experience, ICT perception, Prediction