Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 3 |
Descriptor
Source
| IEEE Transactions on Learning… | 3 |
Author
| Brinton, Christopher G. | 1 |
| Chiang, Mung | 1 |
| Conlan, Owen | 1 |
| Ha, Sangtae | 1 |
| Iyer, Sridhar | 1 |
| Ju, William | 1 |
| Murthy, Sahana | 1 |
| Rajendran, Ramkumar | 1 |
| Rill, Ruediger | 1 |
| Smith, Robert | 1 |
| Yousuf, Bilal | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 1 |
| Secondary Education | 1 |
Audience
Location
| India | 1 |
| Ireland (Dublin) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkYousuf, Bilal; Conlan, Owen – IEEE Transactions on Learning Technologies, 2018
This paper introduces VisEN, a novel visual narrative framework that has been shown to facilitate, support, and enhance student engagement in an adaptive Online Learning Environment (OLE). VisEN provides explorable visual narratives personalized to students in order to support them in engaging with course content. The evaluation of VisEN showed…
Descriptors: Learner Engagement, Visual Aids, Electronic Learning, Individualized Instruction
Rajendran, Ramkumar; Iyer, Sridhar; Murthy, Sahana – IEEE Transactions on Learning Technologies, 2019
The importance of affective states in learning has led many Intelligent Tutoring Systems (ITS) to include students' affective states in their learner models. The adaptation and hence the benefits of an ITS can be improved by detecting and responding to students' affective states. In prior work, we have created and validated a theory-driven model…
Descriptors: Feedback (Response), Individualized Instruction, Intelligent Tutoring Systems, Psychological Patterns
Brinton, Christopher G.; Rill, Ruediger; Ha, Sangtae; Chiang, Mung; Smith, Robert; Ju, William – IEEE Transactions on Learning Technologies, 2015
We present the design, implementation, and preliminary evaluation of our Adaptive Educational System (AES): the Mobile Integrated and Individualized Course (MIIC). MIIC is a platform for personalized course delivery which integrates lecture videos, text, assessments, and social learning into a mobile native app, and collects clickstream-level…
Descriptors: Individualized Instruction, Electronic Learning, Online Courses, Student Attitudes
