Semantic Scholar
Open Access
2014
700 sitasi
The Cambridge Handbook of the Learning Sciences: Educational Data Mining and Learning Analytics
R. Baker
P. Inventado
Abstrak
In recent years, two communities have grown around a joint interest on how big data can be exploited to benefit education and the science of learning: Educational Data Mining and Learning Analytics. This article discusses the relationship between these two communities, and the key methods and approaches of educational data mining. The article discusses how these methods emerged in the early days of research in this area, which methods have seen particular interest in the EDM and learning analytics communities, and how this has changed as the field matures and has moved to making significant contributions to both educational research and practice.
Topik & Kata Kunci
Penulis (2)
R
R. Baker
P
P. Inventado
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2014
- Bahasa
- en
- Total Sitasi
- 700×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1017/CBO9781139519526.016
- Akses
- Open Access ✓