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Qian Fu; Wenjing Tang; Yafeng Zheng; Haotian Ma; Tianlong Zhong – Interactive Learning Environments, 2024
In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…
Descriptors: Predictor Variables, Psychological Patterns, Programming, Self Management
Huang, Fang; Teo, Timothy; Scherer, Ronny – Interactive Learning Environments, 2022
As a key variable determining technology acceptance and adoption, the perceived ease of technology use (PEU) has been in the focus of a considerable body of research. This research examined the external factors that influence perceived ease of use, such as computer self-efficacy and perceived enjoyment, but yielded inconsistent findings and…
Descriptors: College Students, Internet, Electronic Learning, Usability
Teo, Timothy; Huang, Fang; Hoi, Cathy Ka Weng – Interactive Learning Environments, 2018
Given the paradox between pervasive promotion of technology use in English teaching and lack of studies about teachers' technology acceptance in China, this study aims to examine intentions of English teachers in China to use technology in their classroom teaching. Based on the technology acceptance model, eight variables including perceived…
Descriptors: Foreign Countries, Technology Uses in Education, Intention, English (Second Language)