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In this course, you will learn about multimodal learning analytics, a different way to do learning analytics. You will learn how to conduct learning analytics in face-to-face, hands-on, unbounded, and analog learning settings such as classrooms and labs. You will learn to capture, process, and fuse natural rich modalities of communication, such as speech, writing, and nonverbal interaction (e.g., movements, gestures, facial expressions, gaze, biometrics, etc.) during real learning activities.
Multimodal learning analytics enable you to understand and optimize learning in real-world environments that do not necessarily use computers during the learning process.
The course content is a gentle introduction to this new approach to learning analytics: its promises, its challenges, its tools and methodologies. To follow the same spirit of multimodal learning analytics, this course will include hands-on learning experiences analyzing different types of signals captured from real environments.
Overview
Syllabus
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Week 1: Why MMLA?
This week we will cover the basics of multimodal learning analytics: why, when and how to apply it. We will cover basic concepts such as data capture, synchronization and fusion.Week 2: Tools of the trade
Multimodal leads to "Multi-tool." We will review the main hardware and software solutions to capture and analyze the main modes related to learning: audio, video, writing and biosignals.Week 3: Bringing it all together
The last week we will conduct a real multimodal learning analytics study, applying the skills acquired in the previous weeks.
