Foundations of statistical natural language processing
Foundations of statistical natural language processing
The New Division of Labor: How Computers Are Creating the Next Job Market
The New Division of Labor: How Computers Are Creating the Next Job Market
Off-task behavior in the cognitive tutor classroom: when students "game the system"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatic detection of learner's affect from conversational cues
User Modeling and User-Adapted Interaction
Using Knowledge Tracing in a Noisy Environment to Measure Student Reading Proficiencies
International Journal of Artificial Intelligence in Education
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Using learning analytics to assess students' behavior in open-ended programming tasks
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Modeling how students learn to program
Proceedings of the 43rd ACM technical symposium on Computer Science Education
Towards the development of multimodal action based assessment
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Towards the development of multimodal action based assessment
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Expertise estimation based on simple multimodal features
Proceedings of the 15th ACM on International conference on multimodal interaction
Proceedings of the 15th ACM on International conference on multimodal interaction
| Hi-index | 0.00 |
New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics and educational data mining has focused on online courses or cognitive tutors, in which the tasks are more structured and the entirety of interaction happens in front of a computer. In this paper, I argue that multimodal learning analytics could offer new insights into students' learning trajectories, and present several examples of this work and its educational application.