Practicable Learning Analytics

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Practicable Learning Analytics

This book is about practicable learning analytics, that is able to become a successful part of practice, ultimately leading to improved learning and teaching. The aim of the book is to shift our perspective on learning analytics creation and implementation from that of “designing of” technology to that of “designing for” a system of practice. That is, any successful implementation of learning analytics requires a systematic approach, which the book explains through the lens of the Information Systems Artefact, constituting of the three interdependent artefacts: “technical”, “information” and “social”. The contributions of this book go beyond a consideration of particular humans such as teachers and students, and their individual activities to consider the larger systems of activity of which analytics become part of. The chapters included in this book present different cases of learning analytics implementation across countries, and the related opportunities and challenges related to generalizability of the results. The book is written for designers, students and educators of learning analytics who aim to improve learning and teaching through learning analytics.
Emergent Practices of Learning Analytics in K-12 Classrooms

In the world of education, technology has revolutionized teaching and learning practices globally. However, the widespread adoption of technology, especially in response to Covid-19, has led to a deluge of data from students' digital footprints. The challenge lies in effectively using this data through learning analytics (LA) to optimize K-12 classroom practices. Emergent Practices of Learning Analytics in K-12 Classrooms, edited by Dr. Nurdan Kavaklı Ulutaş and Dr. Devrim Höl offers a comprehensive solution to these challenges. This book gathers academic scholars to explore practical perspectives on applying learning analytics in K-12 classrooms, combining qualitative and quantitative methodologies. Addressing topics such as predictive analytics, ethical considerations, and future directions, it empowers educators to make data-driven decisions, creating engaging learning experiences for improved student outcomes. By embracing the insights and recommendations presented in this book, academic scholars can confidently navigate the realm of learning analytics and shape the future of K-12 education.
Generative Intelligence and Intelligent Tutoring Systems

This book constitutes the refereed proceedings of the 20th International Conference on Generative Intelligence and Intelligent Tutoring Systems, ITS 2024, held in Thessaloniki, Greece, during June 10–13, 2024. The 35 full papers and 28 short papers included in this book were carefully reviewed and selected from 88 submissions. This book also contains 2 invited talks. They were organized in topical sections as follows: Generative Intelligence and Tutoring Systems; Generative Intelligence and Healthcare Informatics; Human Interaction, Games and Virtual Reality; Neural Networks and Data Mining; Generative Intelligence and Metaverse; Security, Privacy and Ethics in Generative Intelligence; and Generative Intelligence for Applied Natural Language Processing.