Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 2 |
Descriptor
Benchmarking | 2 |
Data Use | 2 |
Dropouts | 1 |
Electronic Learning | 1 |
Ethics | 1 |
Guidelines | 1 |
Learning Analytics | 1 |
MOOCs | 1 |
Models | 1 |
Prediction | 1 |
Predictor Variables | 1 |
More ▼ |
Source
IEEE Transactions on Learning… | 2 |
Author
Abelardo Pardo | 1 |
Chen Zhan | 1 |
De Smedt, Johannes | 1 |
De Weerdt, Jochen | 1 |
Deeva, Galina | 1 |
Djazia Ladjal | 1 |
Ruth Marshall | 1 |
Srecko Joksimovic | 1 |
Thierry Rakotoarivelo | 1 |
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Chen Zhan; Srecko Joksimovic; Djazia Ladjal; Thierry Rakotoarivelo; Ruth Marshall; Abelardo Pardo – IEEE Transactions on Learning Technologies, 2024
Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide,…
Descriptors: Privacy, Learning Analytics, Ethics, Data Use
Deeva, Galina; De Smedt, Johannes; De Weerdt, Jochen – IEEE Transactions on Learning Technologies, 2022
Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…
Descriptors: Electronic Learning, MOOCs, Dropouts, Prediction