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González-Esparza, Lydia Marion; Jin, Hao-Yue; Lu, Chang; Cutumisu, Maria – AERA Online Paper Repository, 2022
Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…
Descriptors: Student Behavior, Intelligent Tutoring Systems, Feedback (Response), Persistence
Schack, Edna O.; Dueber, David; Thomas, Jonathan Norris; Fisher, Molly H.; Jong, Cindy – AERA Online Paper Repository, 2019
Scoring of teachers' noticing responses is typically burdened with rater bias and reliance upon interrater consensus. The authors sought to make the scoring process more objective, equitable, and generalizable. The development process began with a description of response characteristics for each professional noticing component disconnected from…
Descriptors: Models, Teacher Evaluation, Observation, Bias