Name
Abstract | ||
|---|---|---|
Learning analytics (LA) as a field remains in its infancy. Many of the techniques now prominent from practitioners have been drawn from various fields, including HCI, statistics, computer science, and learning sciences. In order for LA to grow and advance as a discipline, two significant challenges must be met: 1) development of analytics methods and techniques that are native to the LA discipline, and 2) practitioners in LA to develop algorithms and models that reflect the social and computational dimensions of analytics. This workshop introduces researchers in learning analytics to machine learning (ML) and the opportunities that ML can provide in building next generation analysis models. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2567574.2567633 | LAK |
Keywords | Field | DocType |
various field,next generation analysis model,analytics method,la discipline,computational dimension,computer science,machine learning,significant challenge,collaboration,theory | Data science,Learning sciences,Software analytics,Learning analytics,Computer science,Cultural analytics,Artificial intelligence,Analytics,World Wide Web,Business analytics,Semantic analytics,Analysis models,Machine learning | Conference |
Citations | PageRank | References |
3 | 0.45 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dragan Gasevic | 1 | 1569 | 150.79 |
| Rosé Carolyn | 2 | 2126 | 222.80 |
| George Siemens | 3 | 334 | 24.07 |
| Annika Wolff | 4 | 112 | 21.67 |
| Zdenek Zdráhal | 5 | 197 | 25.71 |