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Yu-Hung Chiang; Yu-Chen Su; Wei-Tsong Wang; Tien-Chi Huang – Journal of Educational Computing Research, 2025
As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model…
Descriptors: Business Education, College Students, Foreign Countries, Data
Ali, Amira D.; Hanna, Wael K. – Journal of Educational Computing Research, 2022
With the spread of the COVID-19 pandemic, many universities adopted a hybrid learning model as a substitute for a traditional one. Predicting students' performance in hybrid environments is a complex task because it depends on extracting and analyzing different types of data: log data, self-reports, and face-to-face interactions. Students must…
Descriptors: Predictor Variables, Academic Achievement, Blended Learning, Independent Study
Song, Yanjie; Kong, Siu-Cheung – Journal of Educational Computing Research, 2017
The study aims at investigating university students' acceptance of a statistics learning platform to support the learning of statistics in a blended learning context. Three kinds of digital resources, which are simulations, online videos, and online quizzes, were provided on the platform. Premised on the technology acceptance model, we adopted a…
Descriptors: Academic Achievement, Technology Uses in Education, Statistics, College Students
Xu, Yaoying – Journal of Educational Computing Research, 2010
The purpose of this study was to examine the effects of using Tablet PC to provide feedback on student engagement and achievement in hybrid special education courses. Student engagement was determined by the number of hits and postings in online discussions. Student achievements were compared through pre- and post-tests on course content areas,…
Descriptors: Special Education, Graduate Study, Blended Learning, Graduate Students