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Manel van Kessel; Inge Molenaar; Carolien A. N. Knoop-van Campen; Mario de Jonge; Nadira Saab – Journal of Learning Analytics, 2025
Adaptive learning technologies (ALTs) provide teachers with student data in teacher dashboards (TDs). However, there is substantial variation in dashboard use among teachers, and many find it difficult to draw conclusions based on student data. Teachers' skills, knowledge, and contextual conditions are believed to be essential in effective…
Descriptors: Elementary School Teachers, Technology Uses in Education, Teacher Attitudes, Data Collection
De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
McCoy, Chase; Shih, Patrick C. – Journal of Learning Analytics, 2016
Educational data science (EDS) is an emerging, interdisciplinary research domain that seeks to improve educational assessment, teaching, and student learning through data analytics. Teachers have been portrayed in the EDS literature as users of pre-constructed data dashboards in educational technologies, with little consideration given to them as…
Descriptors: Case Studies, Semi Structured Interviews, Educational Research, Data Collection

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