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Download full textGraf von Malotky, Nikolaj Troels; Martens, Alke – International Association for Development of the Information Society, 2021
ITSs have the requirement to be adaptive to the student with AI. The classical ITS architecture defines three components to split the data and to keep it flexible and thus adaptive. However, there is a lack of abstract descriptions how to put adaptive behavior into practice. This paper defines how you can structure your data for case based systems…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Instructional Development, Instructional Improvement
Direct linkMaya Usher; Arnon Hershkovitz; Alona Forkosh-Baruch – British Journal of Educational Technology, 2021
The outbreak of the COVID-19 pandemic has changed education dramatically, with the sudden shift from face-to-face to emergency remote teaching. Online learning environments may facilitate data-driven instructional process; yet, our understanding regarding data-driven decisions is still limited. This quantitative study examined types of learners'…
Descriptors: College Faculty, COVID-19, Pandemics, Distance Education
Doan, Sy; Eagan, Joshua; Grant, David; Kaufman, Julia H.; Setodji, Claude Messan – RAND Corporation, 2022
This technical report provides detailed information about the sample, survey instruments, and resultant data for the 2022 American Instructional Resources Surveys (AIRS) that were administered to principals and teachers in spring 2022 via the RAND Corporation's American Educator Panels (AEP). The 2022 AIRS focused on the usage of, perceptions of,…
Descriptors: Surveys, Instructional Materials, Language Arts, Mathematics Instruction
