Browsing by Subject "Facilitating conditions"
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ItemFactors affecting intention to E-learning systems in selected Universities in Phnom Penh, CambodiaThis research investigates factors influencing the intention to use e-learning systems in selected universities in Phnom Penh, Cambodia. The conceptual framework has been developed by adopting previous theoretical studies and research models of the modified unified theory of acceptance and use of technology (UTAUT2). Five hundred questionnaires were collected from undergraduate students through Google form survey with universities’ administration assistance. Multi-stage sampling was used: the first stage is stratified random sampling followed by purposive sampling. Collected data were analyzed using the Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) to confirm the model fit and hypothesis testing. The findings showed that performance expectancy, effort expectancy and self-efficacy did not have any influence on behavioral intention. However, social influence had the strongest influence on behavioral intention to use e-learning systems, followed by facilitating conditions. Moreover, facilitating conditions and behavioral intention had a significant influence on use behavior of e-learning systems. This study provided theoretical implications for researchers related to technology adoption and information for training institutions, universities, schools and academic staff on issues they need to focus on when they wish to launch any new system or online services.
ItemFactors influencing the use of ubiquitous learning in higher education in Sichuan, China in the aftermath of COVID-19 pandemic(Bangkok : Assumption University Press, 2021) Huang, MeiziThis research aims to investigate factors for adoption of ubiquitous learning (u-learning) in higher education in China in the wake of the COVID-19 pandemic. Literature and theoretical models for adoption of ubiquitous learning were examined to find the key factors that would influence ubiquitous learning adoption which include performance expectancy, effort expectancy, social influence, facilitating conditions, intention to use and actual use. The research uses a quantitative, survey-based research design, employing online data collection. The study applied multistage sampling. First, a non-probability sampling method, judgmental sampling was used to draw a population of Chinese higher education students in Sichuan, China at three institutions: – Sichuan Normal University Fine Arts College, Sichuan University of Arts and Sciences Academy of Art and Design, and Dazhou Vocational and Technical College Art Department. Second, stratified random sampling was applied to calculate the number of students to represent each program. Lastly, a sample size of 420 was determined based on the ratio of the number of students in each institution to the total number of populations, were selected through convenience sampling. For analysis of data, Confirmation Factor Analysis (CFA) and structural equation modeling (SEM) were utilized. The analysis showed that intention to use has the strongest effect on actual system use. Furthermore, effort expectancy, facilitating conditions, and social influence except performance expectancy were found to positively affect the intention to use u-learning. Hence, policymakers, universities executives, and educators are recommended to consider these factors to ensure technology adoption success.
ItemThe effect of behavioral intention to use hybrid education: a case of Chinese undergraduate studentsPurpose: The purpose of this study is to examining factors affecting undergraduate painting students' behavioral intention toward hybrid education in three public universities in Chongqing, China. Perceived ease of use (PEOU), perceived usefulness (PU), perceived satisfaction (PS), social influence (SI), performance expectancy (PE), Facilitating conditions (FC), and behavioral intention (BI) were used to develop the conceptual framework of this study. Research design, data, and methods: The researchers used quantitative study to distributing questionnaire to 500 participants, who are undergraduate students in the major of painting. The survey was conducted in three sample techniques which are judgmental sampling, quota sampling and convenience sampling methods. An item-objective congruence (IOC) of content validity and Cronbach's Alpha reliability test with 30 pilot samples were earlier assessed. Statistical analyses involve Confirmatory Factor analysis (CFA) and Structural Equation Model (SEM), including model goodness of fit, validity, and reliability. Results: Most hypotheses were supported with the strongest influence between perceived ease of use and perceived usefulness, except facilitation conditions which had no significant influence on behavioral intention. Conclusion: The recommends are that administrators in the educational sector of public institutions should emphasize the main contributors to hybrid learning implementation to increase student engagement and learning efficiency.