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Usher, Maya; Hershkovitz, Arnon – Journal of Science Education and Technology, 2022
Higher education instructors constantly rely on educational data to assess and evaluate the behavior of their students and to make informed decisions such as which content to focus on and how to best engage the students with it. Massive open online course (MOOC) platforms may assist in the data-driven instructional process, as they enable access…
Descriptors: College Faculty, Data Use, MOOCs, Teaching Methods
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Botvin, Maya; Hershkovitz, Arnon; Forkosh-Baruch, Alona – Education and Information Technologies, 2023
Decision-making is key for teaching, with informed decisions promoting students and teachers most effectively. In this study, we explored data-driven decision-making processes of K-12 teachers (N = 302) at times of emergency remote teaching, as experienced during the COVID-19 pandemic outbreak in Israel. Using both quantitative and qualitative…
Descriptors: Foreign Countries, COVID-19, Pandemics, Emergency Programs
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Hershkovitz, Arnon – Technology, Instruction, Cognition and Learning, 2015
Data-driven instruction is still a huge scope and has many shades. One promising way of adding learning analytics to traditional teaching is to offer teachers accessible, data-driven information, either in a dashboard style or with a UI with which they could perform their own analysis on student data (e.g., Ben-Naim, Bain, & Marcus, 2009;…
Descriptors: Data Use, Learning Analytics, Computer Interfaces, Reflection
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Hershkovitz, Arnon – Technology, Instruction, Cognition and Learning, 2015
Still lacking in the mainstream data-driven approaches to studying educational settings is the very basic, most popular educational setting -- that is, the classroom. Capturing data that describes learning in the classroom is the focus of the current issue. The articles in this issue present a large variety of data sources, data collection tools…
Descriptors: Data, Data Use, Instructional Improvement, Data Collection