Year: 2022
Type: book-chapter
Abstract: This chapter is an introduction to the use of multiple modalities of learning trace data to better understand and feedback learning processes that occur both in digital and face-to-face contexts. First, it will explain the rationale behind the emergence of this type of study, followed by a brief explanation of what Multimodal Learning Analytics (MmLA) is based on current conceptual understandings and current state-of-the-art implementations. The majority of this chapter is dedicated to describing the general process of MmLA from the mapping of learning constructs to low-level multimodal learning traces to the reciprocal implementation of multimedia recording, multimodal feature extraction, analysis, and fusion to detect behavioral markers and estimate the studied constructs. This process is illustrated by the detailed dissection of a real-world example. This chapter concludes with a discussion of the current challenges facing the field and the directions in which the field is moving to address them.
Source: Solar eBooks
DOI: 10.18608/hla22.006
Author: Xavier Ochoa
Institution: New York University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4381145042