Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.
Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.
Software Data Engineering for Network eLearning Environments: Analytics and Awareness Learning Services
228
Software Data Engineering for Network eLearning Environments: Analytics and Awareness Learning Services
228Paperback(1st ed. 2018)
Product Details
| ISBN-13: | 9783319683171 |
|---|---|
| Publisher: | Springer International Publishing |
| Publication date: | 03/10/2018 |
| Series: | Lecture Notes on Data Engineering and Communications Technologies , #11 |
| Edition description: | 1st ed. 2018 |
| Pages: | 228 |
| Product dimensions: | 6.10(w) x 9.25(h) x (d) |