The First International Conference on Multimodal Learning Analytics
represented an initial intellectual gathering of multidisciplinary scientists interested in this new topic.
The Third International Workshop on Multimodal Learning Analytics brings together an international collection of
researchers to further advance research on multimodal learning analytics with a data-driven grand challenge event.
In support of this event, the Math Data Corpus and related coding resources are made publicly available for community use by Incaa Designs. In addition, the ChronoViz multimodal data analysis tool is supported by UCSD for workshop grand challenge participants who wish to use it.
The Math Data Corpus contains high-fidelity time-synchronized multimodal data recordings on collaborating groups of students as they work together to solve mathematics problems varying in difficulty. Data were collected on students' natural multimodal communication and activity patterns, including their speech, digital pen input, facial expressions, gestures, and physical movements.
The dataset includes 12 sessions, with six three-student groups who each met twice. In total, approximately 29 student-hours of recorded multimodal data is available during these collaborative problem solving sessions. This data resource includes initial coding of problem segmentation, problem-solving correctness, and representational content on students' writing. A full description of this dataset on this dataset is provided as part of this document, including detailed appendices. Moreover, this paper on "Problem solving, Domain Expertise and Learning: Ground-truth Performance Results for Math Data Corpus" can be used to better understand the data. The dataset is available to participants in the Third International Workshop on Multimodal Learning Analytics data-driven grand challenge, after signing a collaborator agreement (see below).
Steps for MMLA workshop participants: