Abstract
The innovation of immersion tools and online platforms provides more possibilities for the development of online education. Information guidance is a key part of information translation for online education information providers and directly affects the information translation into the receiver, so a more profound discussion and design of guidance methods are needed to optimize the effectiveness of online education information transmission. This study expands the guidance methods by dividing them into traditional guidance and multidimensional guidance according to different interaction modes of online education. Forty subjects were screened by a basic information questionnaire and a two-factor intergroup experimental design with 2 guidance methods (traditional and multidimensional) × 2 digital media (smartphone and tablet) was conducted. Learners evaluated and provided feedback on the experimental material from cognitive and affective goals through questionnaires. The results of the questionnaire analysis showed that the effectiveness of online educational transfer Learners learn better when educators use multidimensional guidance; multidimensional guidance increases learner engagement, thus effectively improving the effectiveness of information transmission. Learners learn better when digital media with large screen sizes are used; educators always improve online learning satisfaction better when they use tablets as digital media when conducting instruction. This finding enriches the research on the influence of guidance methods and digital media on information delivery in synchronous online teaching, where the research on the innovation of guidance methods provides the basis for the innovation and application of interactive technologies in online education.
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Dong, J., Wang, J., Tan, J., Wang, Z., Sun, J. (2023). Optimization Strategy of Guidance Methods of Online Education Information Transmission. In: Marcus, A., Rosenzweig, E., Soares, M.M. (eds) Design, User Experience, and Usability. HCII 2023. Lecture Notes in Computer Science, vol 14033. Springer, Cham. https://doi.org/10.1007/978-3-031-35708-4_4
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