Implementation and evaluation of cloud-based e-learning in agricultural course

Abstract

ABSTRACT In recent years, governments have paid much more attention to online learning platforms. This study establishes a high-performance agricultural digital learning platform (hereafter referred to as the Platform), in an attempt to (1) achieve learning diversity, improve users’ learning ability and willingness to learn, and unblocking geo-restrictions, and (2) design cloud-based e-learning materials and assess their learning effectiveness through the use of satisfaction surveys. A cloud-based high-efficiency online course platform for the agricultural community uses a real-time streaming analysis to determine the network string flow during users’ video playback and enables dynamic allocation to obtain the best server effectiveness. Users can remain motivated while taking high-quality online courses. With the establishment of cloud-based course materials, and the specificity of agricultural information, we hope to improve users’ learning motivation and learning effectiveness. Furthermore, this study uses satisfaction surveys and the UTAUT model to assess the research findings according to whether the users’ performance expectancy, effort expectancy, social influence, and facilitating conditions have a positive impact on the perceived satisfaction and perceived usefulness. We verified this point and inferred that digital learning can support the agricultural community significantly.