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Direct linkLee, Hsin-Yu; Cheng, Yu-Ping; Wang, Wei-Sheng; Lin, Chia-Ju; Huang, Yueh-Min – Journal of Educational Computing Research, 2023
Given the inadequacy of assessed outcomes (e.g., final exam) and the importance of evaluating the learning process in STEM education, we use deep learning to develop the STEM learning behavior analysis system (SLBAS) to assess the behavior of learners in STEM education. We map learner behavior to the ICAP (interactive, constructive, active,…
Descriptors: Learning Processes, Instructional Effectiveness, STEM Education, Student Behavior
Wang, Cheng-Hung; Lin, Hao-Chiang Koong – Journal of Educational Computing Research, 2018
Computers and the Internet are indispensable in modern life. Increasingly useful digital environments and technological developments have reshaped models of knowledge acquisition. Studies on the development of online learning have yielded valuable insights. In the design of online teaching systems that can replicate face-to-face teaching,…
Descriptors: Affective Objectives, Tutoring, Learning Processes, Educational Technology
Reigeluth, Charles M.; Aslan, Sinem; Chen, Zengguan; Dutta, Pratima; Huh, Yeol; Lee, Dabae; Lin, Chun-Yi; Lu, Ya-Huei; Min, Mina; Tan, Verily; Watson, Sunnie Lee; Watson, William R. – Journal of Educational Computing Research, 2015
The learner-centered paradigm of instruction differs in such fundamental ways from the teacher-centered paradigm that it requires technology to serve very different functions. In 2006, a research team at Indiana University began to work on identifying those functions and published their results in 2008. Subsequently, the team elaborated and…
Descriptors: Individualized Instruction, Learner Controlled Instruction, Intelligent Tutoring Systems, Interdisciplinary Approach
