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Shiyi Liu; Juan Zheng; Tingting Wang; Zeda Xu; Jie Chao; Shiyan Jiang – AERA Online Paper Repository, 2024
This study introduces a novel approach for predicting student engagement levels in a language-based AI curriculum. The curriculum was integrated into English Language Arts classrooms, in which 106 students from five classes participated five web-based machine learning and text mining modules for 2 weeks. Sentiment and categorical analyses,…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Language Arts
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Jisung Yoo; Moonyoung Eom – AERA Online Paper Repository, 2024
This paper aims to identify and compare key factors influencing US States' or an OECD country's decision to employ student test scores or test score value-added (VAM) in evaluating teacher effectiveness. Analysis using multiple linear probability model and logistic regression frameworks indicates that the use of VAM/student test scores was…
Descriptors: Teacher Evaluation, Teacher Effectiveness, Scores, Value Added Models