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Direct linkFiona King; Philip Poekert; Takeshia Pierre – Professional Development in Education, 2023
Professional learning (PL) encompasses the complexity of teacher learning and teacher agency in the process of learning. This paper aims to shed light on this complexity and proffers a conceptual meta-model of PL grounded in pragmatism to inform action in the design and evaluation of PL. It will firstly explore the aim and implications of the…
Descriptors: Faculty Development, Models, Professional Autonomy, Professional Continuing Education
Tekleselassie, Abebayehu Aemero; Choi, Jaehwa – Educational Policy, 2021
Despite a growing body of turnover literature, much remains unknown about the factors predicting career transitional behaviors of school principals. To bridge this gap, we examined variations in principal, school, and district characteristics influencing administrator leaver and mover behaviors, using Hierarchical Generalized Linear Modeling. Our…
Descriptors: Principals, Occupational Mobility, Hierarchical Linear Modeling, Career Development
Qian, Quan; Lau, Kit-ling – Journal of Research in Reading, 2022
Background: Research has shown that achievement goals and reading instruction play important roles in students' reading performance. However, little is known about the specific effects of different types of achievement goals and reading instructional practices on reading performance in mainland China. Methods: This study used Programme of…
Descriptors: Achievement Gains, School Districts, Teaching Methods, Reading Achievement
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
