RIMES: Embedding Interactive Multimedia Exercises in Lecture Videos
July 06, 2015 Β· Declared Dead Β· π International Conference on Human Factors in Computing Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Juho Kim, Elena L. Glassman, AndrΓ©s Monroy-HernΓ‘ndez, Meredith Ringel Morris
arXiv ID
1507.01318
Category
cs.CY: Computers & Society
Cross-listed
cs.HC
Citations
56
Venue
International Conference on Human Factors in Computing Systems
Last Checked
3 months ago
Abstract
Teachers in conventional classrooms often ask learners to express themselves and show their thought processes by speaking out loud, drawing on a whiteboard, or even using physical objects. Despite the pedagogical value of such activities, interactive exercises available in most online learning platforms are constrained to multiple-choice and short answer questions. We introduce RIMES, a system for easily authoring, recording, and reviewing interactive multimedia exercises embedded in lecture videos. With RIMES, teachers can prompt learners to record their responses to an activity using video, audio, and inking while watching lecture videos. Teachers can then review and interact with all the learners' responses in an aggregated gallery. We evaluated RIMES with 19 teachers and 25 students. Teachers created a diverse set of activities across multiple subjects that tested deep conceptual and procedural knowledge. Teachers found the exercises useful for capturing students' thought processes, identifying misconceptions, and engaging students with content.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computers & Society
π
π
The Cartographer
R.I.P.
π»
Ghosted
Artificial Intelligence: the global landscape of ethics guidelines
R.I.P.
π»
Ghosted
The role of artificial intelligence in achieving the Sustainable Development Goals
R.I.P.
π»
Ghosted
Green AI
R.I.P.
π»
Ghosted
Principles alone cannot guarantee ethical AI
R.I.P.
π»
Ghosted
Tackling Climate Change with Machine Learning
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted