Investigating the influence of external variables and mediators on learning management system utilization among educations students of three Malaysian research universities

Recently, in the context of higher education, the use of learning management systems involving the application of Information and Communication Technologies has become widespread. Despite the advantages of learning management systems in enhancing the quality of learning, it is not fully utilized by...

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主要作者: Zadeh, Sousan Baleghi
格式: Thesis
语言:English
出版: 2014
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在线阅读:http://psasir.upm.edu.my/id/eprint/50637/1/FPP%202014%2044RR.pdf
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总结:Recently, in the context of higher education, the use of learning management systems involving the application of Information and Communication Technologies has become widespread. Despite the advantages of learning management systems in enhancing the quality of learning, it is not fully utilized by students. Review of the related studies shows that although there is an enormous amount of research on online tools, only a few of them have investigated how students use the online tools found within LMS. The main purpose of the present study is to investigate the influence of external factors and mediators on Learning Management Systems utilization among full-time undergraduate students of faculties of education at Universiti Putra Malaysia (UPM),Universiti Kebangsaan Malaysia (UKM) and Universiti Malaya (UM) based on Technology Acceptance Model, Theory of Reasoned Action, and Fit Model. By reviewing the related literature, the influence of nine factors on LMS utilization tasktechnology fit, subjective norm, technical support, system interactivity, system functionality, Internet experience, perceived ease of use, perceived usefulness, and behavior intention to use) were examined. The present study was entirely quantitative with a descriptive design. The main instrument used was a questionnaire whose content validity was checked by a panel of experts. A pilot study was conducted on 40 students of UPM and UM to assess the reliability of the instrument. The value of Cronbach’s alpha was from .75 to .95. The sampling technique was stratified and the sample size was 400. To analyze the data,descriptive statistics and the Structural Equation Modeling technique were used. After testing the measurement model, the construct of Internet experience was removed, and as a result, nine predictors of LMS use remained. The outcome of testing the structural model revealed that among the 16 paths of the structural model,12 paths were significant and four were not. The 12 significant paths were: 1) tasktechnology fit influences LMS use (β=.212, p<.01); 2) task-technology fit influences perceived usefulness (β=.334, p<.001); 3) subjective norm influences perceived usefulness (β=.200, .001); 4) subjective norm influences behavior intention to use (β=.158, p<.05); 5) system functionality influences perceived usefulness (β = .222,p<.001; 6) system functionality influences perceived ease of use (β= .221, p<.01); 7);technical support influences perceived ease of use (β=.197, p<.001); 8) system interactivity influences perceived usefulness (.126, p<.05); 9); perceived ease of use influences perceived usefulness (β=.123, p<.05); 10) perceived ease of use influences behavior intention to use (β=.232, p<.001); 11) perceived usefulness influences behavior intention to use (β= .324, p<.001); and 12) behavior intention to use influences LMS use (β=.479, p<.001). The findings of the study revealed that the influence of technical support on perceived usefulness (β= .003, p>.05), the influence of system interactivity on perceived ease of use (β= -.046, p>.05), the influence of perceived usefulness on LMS use (β=.015,p>.05), and the influence of perceived ease of use on LMS use (β = -.084, p>.05) were not significant. After testing the structural model, two new significant paths emerged:1) the influence of task-technology fit on perceived ease of use (β=.248, p<.001) and 2) the influence of subjective norm on perceived ease of use (β=.200, p<.01). The results of mediation tests indicated that behavior intention to use indirectly mediated the influence of perceived ease of use on LMS use and fully mediated the influence of perceived usefulness on LMS use. Perceived usefulness partially mediated the influence of perceived ease of use on behavior intention to use and partially mediated the influence of subjective norm on behavior intention to use. Perceived ease of use indirectly mediated the influence of technical support on perceived usefulness, partially mediated the influence of system functionality on perceived usefulness, partially mediated the influence of task-technology fit on perceived usefulness, and partially mediated the influence of subjective norm on perceived usefulness. The proposed structural model explained 42.8% of perceived ease of use, 65.9% of perceived usefulness, 37.6% of behavior intention to use, and 32.1% of LMS use.