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Ecological Momentary Assessment as a Delivery Service for Progress Monitoring Internalizing Concerns
Ishan N. Vengurlekar; Carly Oddleifson; Chelsea Salvatore; Stephen P. Kilgus; Evan H. Dart – Journal of Applied School Psychology, 2025
Progress monitoring data provide important information on student functioning in response to an intervention. Yet, there are several barriers to effective progress monitoring of internalizing symptoms among youth. To address these concerns, the current paper conceptualized the use of ecological momentary assessment (EMA) as a service delivery…
Descriptors: Middle School Students, Progress Monitoring, Student Improvement, Emotional Response
Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
Miray Dogan; Arda Celik; Hasan Arslan – European Journal of Education, 2025
This research investigates how artificial intelligence (AI) influences higher education, specifically exploring the perspectives of academicians regarding associated risks and opportunities. The study is aimed at the implementation of AI within university settings and its impact on both educators and students. Given the swift integration of AI,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Access to Internet
Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence