Zobeidi Tahereh, Homayoon Seyedeh Bahar, Yazdanpanah Masoud, Komendantova Nadejda, Warner Laura A
Cooperation and Transformative Group, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.
Department of Agricultural Extension and Education, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran.
Front Psychol. 2023 Feb 17;14:1104653. doi: 10.3389/fpsyg.2023.1104653. eCollection 2023.
Online learning systems have become an applied solution for delivering educational content, especially in developing countries, since the start of the COVID-19 pandemic. The present study is designed to identify the factors influencing the behavioral intention of agricultural students at universities in Iran to use online learning systems in the future. This research uses an extended model in which the constructs of Internet self-efficacy, Internet anxiety, and output quality are integrated into the technology acceptance model (TAM). Data analysis was performed using the SmartPLS technique. The analyses showed the proposed model to be strong in terms of predicting the attitude to online learning and the intention to use it. The extended TAM model fit the data well and predicted 74% of the intention variance. Our findings show attitude and perceived usefulness to have directly affected intention. Output quality and Internet self-efficacy indirectly affected attitude and intention. Research findings can help with the design of educational policies and programs to facilitate education and improve student academic performance.
自新冠疫情爆发以来，在线学习系统已成为提供教育内容的一种应用解决方案，尤其是在发展中国家。本研究旨在确定影响伊朗大学生未来使用在线学习系统行为意向的因素。本研究使用了一个扩展模型，其中将互联网自我效能感、互联网焦虑和输出质量等构念整合到技术接受模型（TAM）中。使用SmartPLS技术进行数据分析。分析表明，所提出的模型在预测对在线学习的态度和使用意愿方面表现强劲。扩展的TAM模型与数据拟合良好，预测了74%的意愿方差。我们的研究结果表明，态度和感知有用性直接影响意愿。输出质量和互联网自我效能感间接影响态度和意愿。研究结果有助于设计教育政策和项目，以促进教育并提高学生的学业成绩。
