Name
Abstract | ||
|---|---|---|
While video has become a widely adopted medium for online learning, existing video players provide limited support for navigation and learning. It is difficult to locate parts of the video that are linked to specific concepts. Also, most video players afford passive watching, thus making it difficult for learners with limited metacognitive skills to deeply engage with the content and reflect on their understanding. To support concept-driven navigation and comprehension of lecture videos, we present ConceptScape, a system that generates and presents a concept map for lecture videos. ConceptScape engages crowd workers to collaboratively generate a concept map by prompting them to externalize reflections on the video. We present two studies to show that (1) interactive concept maps can be useful tools for concept-based video navigation and comprehension, and (2) with ConceptScape, novice crowd workers can collaboratively generate complex concept maps that match the quality of those by experts.
|
Year | Venue | Keywords |
|---|---|---|
2018 | CHI | Crowdsourcing, video learning, online education, concept map |
Field | DocType | ISBN |
Online learning,Educational technology,Concept map,Video navigation,Computer science,Crowdsourcing,Metacognition,Human–computer interaction,Multimedia,Comprehension | Conference | 978-1-4503-5620-6 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ching Liu | 1 | 0 | 0.68 |
| Juho Kim | 2 | 632 | 68.72 |
| Hao-Chuan Wang | 3 | 296 | 45.80 |