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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
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Hwang, Wu-Yuin; Hariyanti, Uun; Abdillah, Yan Amal; Chen, Holly S. L. – Educational Technology & Society, 2021
Geometry is essential for mathematics learning given that it is strongly related to our surroundings; however, few studies concentrated on using geometry in our daily life, especially using mobile devices with their sensors. Thus, this study proposed one app, Ubiquitous Geometry (UG), and explored its effects on learning angles and polygons in…
Descriptors: Geometry, Mathematics Instruction, Computer Oriented Programs, Educational Technology
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Atanga, Comfort; Jones, Beth A.; Krueger, Lacy E.; Lu, Shulan – Journal of Special Education Technology, 2020
Assistive technology (AT) helps bridge the gap between students with learning disabilities (LD) and their peers without LD. However, this implies a need for teachers to become well-trained and proficient in the use of AT. There are established AT competencies for educators, and AT services professionals must be knowledgeable about AT to select and…
Descriptors: Students with Disabilities, Learning Disabilities, Assistive Technology, Teacher Competencies