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Creating Personalized Learning Using Aggregated Data from Students’ Online Conversational Interactions in Customized Groups
| Content Provider | Scilit |
|---|---|
| Author | Martin, Scott M. Trang, Matthew L. |
| Copyright Year | 2018 |
| Description | This chapter describes several platforms that move beyond the limitations of conventional online teaching by using live and archived streaming instruction coupled with interactive communication chat channels. In addition to providing knowledge from instructors and peers, these platforms are configured to generate teaching and learning assessment datasets. Deep machine-learning using unique datasets derived from each learner's communication tendencies and social interactivity may help optimize the learning environment for that individual, provide guidance and support, and enable the use of cognitive memory maps to store and retrieve a student's academic journey. Book Name: Learning Engineering for Online Education |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.4324/9781351186193-8&type=chapterpdf |
| Ending Page | 165 |
| Page Count | 22 |
| Starting Page | 144 |
| DOI | 10.4324/9781351186193-8 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2018-10-12 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Learning Engineering for Online Education Education Research Teaching Platforms Learning Using Help Optimize Online Conversational Streaming Instruction Provide Guidance |
| Content Type | Text |
| Resource Type | Chapter |
