Multimodal Learning Analytics (MLA)

Xavier Ochoa, Escuela Superior Politécnica del Litoral, Ecuador

Marcelo Worsley, Stanford University, CA, USA

Overview

Learning does not only occur over Learning Management Systems or digital tools. It tends to happen in several face-to-face, hands-on, unbounded and analog learning settings such as classrooms and labs. Multimodal Learning Analytics (MLA) emphasizes the analysis of natural rich modalities of communication during situated learning activities. This includes students’ speech, writing, and nonverbal interaction (e.g., movements, gestures, facial expressions, gaze, biometrics, etc.). A primary objective of multimodal learning analytics is to analyze coherent signal, activity, and lexical patterns to understand the learning process and provide feedback to its participants in order to improve the learning experience. This workshop is posed as a gentle introduction to this new approach to Learning Analytics: its promises, its challenges, its tools and methodologies.  To follow the same spirit of MLA, this workshop will include a hands-on learning experience analyzing different types of signals captured from real environments.

Objectives

• Define multimodal analysis and motivated its affordances
• Explore the vast untapped sources of information about the learning process potentially available through multimodal capture and analysis
• Introduce participants to MLA techniques and tools
• Discuss challenges and opportunities in MLA
• Provide hands-on opportunities to explore MLA
• Grow a Special Interest Group in MLA

Activities

• Participant introduction: 10 minutes
• Introducing Multimodal Learning Analytics: 20 minutes
• Live examples of MLA research: 30 minutes
• MLA datasets: 15 minutes
• Introduction to hands-on activity on MLA datasets: 15 minutes
• Break (informal discussion): 30 minutes
• Hands on activity on MLA datasets: 45 minutes
• Demonstration Session: 30 minutes
• Final Discussions: 15 minutes

Requirements

• A laptop with connection to Internet
• Basic programming skills
• Large amounts of curiosity

Organizers

Xavier Ochoa is a principal professor at the Faculty of Electrical and Computer Engineering at Escuela Superior Politécnica del Litoral (ESPOL) in Guayaquil, Ecuador. He coordinates the research group on Teaching and Learning Technologies at ESPOL. He is also involved in the coordination of the Society for Learning Analytics Research (SoLAR), the Latin American Community on Learning Technologies (LACLO), the ARIADNE Foundation and several regional projects on Personalized and Open Education. His main research interests revolve around Learning Analytics, Multimodal Interaction, Informetrics and Learning Technologies in general. More information at http://ariadne.cti.espol.edu.ec/xavier

Marcelo Worsley is a PhD candidate in the Learning Sciences and Technology Design program where his research centers around identifying ways to leverage artificial intelligence to characterize learning in constructionist learning environments. Beyond this, he is interested in improving STEM education and making it more accessible to a larger population of students. To this end, he has extensive experience developing both after-school programs and summer programs that help students recognize that they can successfully pursue STEM fields by having them engage in constructionist learning activities. He also has experience teaching high school engineering classes and one-on-one tutoring. In addition to his education experience, Marcelo has industrial experience in pharmaceuticals, non-profits, chemicals, technology consulting, and a number of industrial research labs: AT&T, IBM and Accenture.  He holds a BS in Chemical Engineering, a BS in Spanish, and is pursuing an MS in Computer Science, in addition to the PhD in Education.  Marcelo is funded through the AT&T Labs Fellowship Program and the Stanford Diversifying Academia, Recruiting Excellence Fellowship.