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Peer reviewedParian Haghighat; Denisa Gandara; Lulu Kang; Hadis Anahideh – Grantee Submission, 2024
Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…
Descriptors: Prediction, Learning Analytics, Multivariate Analysis, Regression (Statistics)
Denisa Gandara; Hadis Anahideh – Society for Research on Educational Effectiveness, 2024
Background/Context: Predictive analytics has emerged as an indispensable tool in the education sector, offering insights that can improve student outcomes and inform more equitable policies (Friedler et al., 2019; Kleinberg et al., 2018). However, the widespread adoption of predictive models is hindered by several challenges, including the lack of…
Descriptors: Prediction, Learning Analytics, Ethics, Statistical Bias
Yang, Li-Ping; Xin, Tao – Educational Measurement: Issues and Practice, 2022
The upgrade educational information technology triggered by COVID-19 has shaped a new educational order and new educational forms. As a result, traditional educational measurement is now facing a systematic transformation, that is, from the Assessment of Learning (AoL) to Assessment for Learning (AfL), and finally to Assessment as Learning (AaL).…
Descriptors: Educational Assessment, Information Technology, Educational Technology, COVID-19

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