Introduction to Multimodal Learning Analytics

Michail Giannakos; Daniel Spikol; Daniele Di Mitri; Kshitij Sharma; Xavier Ochoa; Rawad Hammad

doi:10.1007/978-3-031-08076-0_1

Introduction to Multimodal Learning Analytics

Michail Giannakos, Daniel Spikol, Daniele Di Mitri, Kshitij Sharma, Xavier Ochoa, Rawad Hammad

Administration, Leadership & Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This chapter provides an introduction and an overview of this edited book on Multimodal Learning Analytics (MMLA). The goal of this book is to introduce the reader to the field of MMLA and provide a comprehensive overview of contemporary MMLA research. The contributions come from diverse contexts to support different objectives and stakeholders (e.g., learning scientists, policymakers, technologists). In this first introductory chapter, we present the history of MMLA and the various ongoing challenges, giving a brief overview of the contributions of the book, and conclude by highlighting the potential emerging technologies and practices connected with MMLA.

Original language	English (US)
Title of host publication	The Multimodal Learning Analytics Handbook
Publisher	Springer International Publishing
Pages	3-28
Number of pages	26
ISBN (Electronic)	9783031080760
ISBN (Print)	9783031080753
DOIs	https://doi.org/10.1007/978-3-031-08076-0_1
State	Published - Jan 1 2022

Keywords

AI in education
Learning analytics
Multimodal learning analytics
Sensor data

ASJC Scopus subject areas

General Social Sciences

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10.1007/978-3-031-08076-0_1

Cite this

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AU - Spikol, Daniel

AU - Mitri, Daniele Di

AU - Sharma, Kshitij

AU - Ochoa, Xavier

AU - Hammad, Rawad

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KW - Sensor data

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Introduction to Multimodal Learning Analytics

Abstract

Keywords

ASJC Scopus subject areas

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