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Saqr, Mohammed – British Journal of Educational Technology, 2023
Learning analytics is a fast-growing discipline. Institutions and countries alike are racing to harness the power of using data to support students, teachers and stakeholders. Research in the field has proven that predicting and supporting underachieving students is worthwhile. Nonetheless, challenges remain unresolved, for example, lack of…
Descriptors: Learning Analytics, Generalizability Theory, Models, Grades (Scholastic)
Viberg, Olga; Engström, Linda; Saqr, Mohammed; Hrastinski, Stefan – Education and Information Technologies, 2022
In order to successfully implement learning analytics (LA), we need a better understanding of student expectations of such services. Yet, there is still a limited body of research about students' expectations across countries. Student expectations of LA have been predominantly examined from a view that perceives students as a group of individuals…
Descriptors: Learning Analytics, Student Attitudes, Expectation, College Students
Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation