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Autor/inAguilar, Stephen J.
TitelLearning Analytics: At the Nexus of Big Data, Digital Innovation, and Social Justice in Education
QuelleIn: TechTrends: Linking Research and Practice to Improve Learning, 62 (2018) 1, S.37-45 (9 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN8756-3894
DOI10.1007/s11528-017-0226-9
SchlagwörterInstructional Design; Social Justice; Educational Research; Data Collection; Data Analysis; Learning Experience; Educational Innovation; Class Size; Educational Technology; Student Needs; Individualized Instruction
AbstractWe are still designing educational experiences for the "average" student, and have room to improve. Learning analytics provides a way forward. This commentary describes how learning analytics-based applications are well positioned to meaningfully personalize the learning experience in diverse ways. In so doing, learning analytics has the potential to contribute to more equitable and socially just educational outcomes for students who might otherwise be seen through the lens of the average student. Utilizing big data, good design, and the input of the stakeholders, learning analytics techniques aim to develop applications for the sole purpose of reducing the classroom size to 1. Over time, these digital innovations will enable us to do away with a model of education that teaches toward the non-existent average student, replacing it with one that is more socially just--one that addresses the individual needs of every student. (As Provided).
AnmerkungenSpringer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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