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Bixi Zhang; Wolfgang Wiedermann – Society for Research on Educational Effectiveness, 2022
Background: Studying causal effects is an important aim in education. Causal relationships indicate how well implements (e.g., interventions) work for the target subjects. A good strategy to get the inference in such relationships is to conduct randomized experiments. However, random assignment is limited in education research, even is discouraged…
Descriptors: Statistical Analysis, Causal Models, Algorithms, Simulation
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Emanuele Bardelli; Matthew Ronfeldt; Matthew Truwit – Society for Research on Educational Effectiveness, 2023
Background: Recent field experiments confirm that learning to teach under a more instructionally effective mentor causes teacher candidates to feel more prepared (Ronfeldt et al., 2020; Ronfeldt, Goldhaber, et al., 2018) and demonstrate more effective teaching (Goldhaber et al., 2022). One of these experiments--designed under a research-practice…
Descriptors: Simulation, Equal Education, Teacher Education, Intervention
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Wei Li; Walter Leite; Jia Quan – Society for Research on Educational Effectiveness, 2023
Background: Multilevel randomized controlled trials (MRCTs) have been widely used to evaluate the causal effects of educational interventions. Traditionally, educational researchers and policymakers focused on the average treatment effects (ATE) of the intervention. Recently there has been an increasing interest in evaluating the heterogeneity of…
Descriptors: Artificial Intelligence, Identification, Hierarchical Linear Modeling, Randomized Controlled Trials
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Xue Wang; Gaoxiang Luo – Society for Research on Educational Effectiveness, 2024
Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…
Descriptors: Meta Analysis, Artificial Intelligence, Computational Linguistics, Computer Software
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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
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Anika Alam; A. Brooks Bowden – Society for Research on Educational Effectiveness, 2024
Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…
Descriptors: Dropout Characteristics, Prediction, Artificial Intelligence, At Risk Students