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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
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

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