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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
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Deho, Oscar Blessed; Joksimovic, Srecko; Li, Jiuyong; Zhan, Chen; Liu, Jixue; Liu, Lin – IEEE Transactions on Learning Technologies, 2023
Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…
Descriptors: Learning Analytics, Models, Student Records, Prediction
Carlson, Tiffany; Crepeau-Hobson, Franci – Communique, 2021
When the coronavirus pandemic was declared a public health crisis in March 2020, school psychologists were forced into situations where face-to-face interaction with their students was discouraged and in some cases, prohibited. Consequently, the traditional practice of school psychology abruptly ended. Individualized Education Plans (IEP) and…
Descriptors: Cognitive Tests, Ethics, Decision Making, Models
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Olufunke, Ajayi E.; Sunday, Adodo O.; Olusola, Ajayi O. – Journal on School Educational Technology, 2020
Students' academic achievement outcome hinges on many factors such as attendance, behaviour, motivation and parental monitoring of students' performance. Unlike in primary and secondary schools where there are templates for parents to monitor their wards' academic records, the situation is different in tertiary institutions. Consequently, this…
Descriptors: Foreign Countries, Undergraduate Students, Student Records, Parents
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Sclater, Niall – Journal of Learning Analytics, 2016
Ethical and legal objections to learning analytics are barriers to development of the field, thus potentially denying students the benefits of predictive analytics and adaptive learning. Jisc, a charitable organization that champions the use of digital technologies in UK education and research, has attempted to address this with the development of…
Descriptors: Data Analysis, Information Policy, Ethics, Standard Setting
Rogers, Sheryl D. – ProQuest LLC, 2012
The study was a policy analysis of student records policies within Florida public K-12 school districts. The researcher gathered all student records policies for the sixty-seven school districts. In addition, traditional legal research was used involving applicable federal acts, state statutes, case law, as well as legal and educational…
Descriptors: Public Schools, School Policy, Privacy, Policy Analysis
Bartlett, Larry; And Others – 1976
The model policy and rules presented here were based on the final rules concerning education records appearing in the "Federal Register" and are designed to help those developing and implementing local policy and rules. The model policy is a short statement of direction concerning student records. The rules, covering 21 different areas,…
Descriptors: Administrator Responsibility, Confidential Records, Confidentiality, Disclosure