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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
Memik Yildiz; Özlem Oguz; John E. Pierce – International Journal of Language & Communication Disorders, 2025
Background: The adaptation of aphasia therapy tools into different languages and cultural contexts is essential for broadening access to effective rehabilitation resources. Currently, most online aphasia therapy software is available primarily in English with limited resources for Turkish-speaking individuals. Aims: This study aimed to address…
Descriptors: Aphasia, Speech Therapy, Computer Oriented Programs, Turkish
Gedrimiene, Egle; Celik, Ismail; Mäkitalo, Kati; Muukkonen, Hanni – Journal of Learning Analytics, 2023
Transparency and trustworthiness are among the key requirements for the ethical use of learning analytics (LA) and artificial intelligence (AI) in the context of social inclusion and equity. However, research on these issues pertaining to users is lacking, leaving it unclear as to how transparent and trustworthy current LA tools are for their…
Descriptors: Learning Analytics, Accountability, Trust (Psychology), Artificial Intelligence

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