Next deadline: Chapter manuscript proposals due (2-page abstract): March 01, 2025
Submission server: https://www.conftool.
Edited volume to be published by Springer
Volume Editors:
Stavros A. Nikou, Institute of Education, University of Strathclyde, stavros.nikou@strath.ac.uk
Michael E. Auer, CTI Frankfurt, Germany, auer@cti-online.net
As Generative AI (Gen AI) technologies evolve, the education sector is seeking to explore their potential to enhance teaching and learning. From AI-powered teaching assistants that help students with homework, to algorithms that can analyze student performance and offer personalized recommendations, Generative AI seems to have a transformative educational potential. However, the use of Generative AI in the context of primary and secondary schools, while it brings both opportunities and challenges, it is an area that it is underexplored and therefore requires deeper examination.
The book, “Generative AI in Novel Educational Applications: Practices of Integrating GenAI in the Primary and Secondary Classroom” seeks to serve as a comprehensive resource for researchers and practitioners to share insights, research, and practical applications of generative artificial intelligence in primary and secondary education.
The book will gather contributions from leading academics, educators, and educational technologists who are at the forefront of AI integration in education and will provide evidence-based solutions and best practices across multiple aspects of the educational experience. From enhancing personalized learning to reimagining the organization and administration of primary and secondary schools, this resource explores how Gen AI can be harnessed to build the classrooms of the future. With insights on fostering collaboration among educators, engaging students, and supporting research-backed teaching methods, this book aims to serve as an essential guide for educators, administrators, and policymakers looking to thoughtfully integrate Gen AI into primary and secondary education.
The book will explore a wide range of topics, including but not limited to:
· Case studies and practical examples: Real-world applications of Gen AI in different educational settings, showcasing successful implementations and lessons learned from both primary and secondary school contexts.
· Pedagogical implications: How Gen AI affects traditional teaching methods, teacher-student interactions, assessments and the development of critical thinking and creativity in students.
· Benefits of Gen AI in the primary and secondary classroom: How Gen AI can support personalized learning, improve student engagement, and automate administrative tasks to reduce teacher workload.
· Challenges and drawbacks: Issues such as student data privacy, algorithmic bias, over-reliance on automation, the digital divide, and ethical concerns in the use of Gen AI in primary and secondary education.
· Policy and professional development: Strategies for developing policies and training programs to prepare educators for the responsible use of Gen AI tools in their classrooms.
By presenting a broad range of perspectives, this book will serve as an essential guide for anyone interested in the responsible, effective, and equitable integration of Gen AI in primary and secondary education.
The editors welcome submissions from academics and researchers, teachers, postgraduate students, education technologists, policy makers, and other practitioners interested in the innovative uses of Gen AI in primary and secondary education to share their experiences and views on applying GenAI to teaching and learning with special focus on primary and secondary education, to discuss, explore trends and challenges and critically expose possibilities and ways to re-think the education of the future.
Call Details and Timeline:
This book project will follow a 2-step review process. Prospective authors are invited to submit a chapter proposal to one of the sections first, no later than March 01, 2025. On the basis of the 2-page proposal, the editorial team may invite the authors to submit a full manuscript or reject the submission. The chapter proposals should include a title, authors, affiliations, chapter abstract describing the content of the chapter (max. 2 pages), keywords, key references, and a 2-3 sentence describing how the chapter fits the theme of the respective section (see template for further details).
The proposed chapter should be a previously unpublished work. Upon acceptance of the chapter proposal, the full manuscript should be completed no later than June 01, 2025. Guidelines for preparing chapters will be sent to authors upon acceptance of the chapter proposal. Contributions will undergo a peer-review process where the authors identity will be concealed. Authors are expected to peer-review one or two chapters for other book sections (review-to-publish policy). Comments to authors will be returned by June 30, 2025. Finalized full chapter manuscripts are due no later than August 30, 2025.
All manuscripts should be submitted online on : https://www.conftool.net/genai-in-novel-educational-applications/
Authors are requested to choose one of the below-described sections for abstract submission.
Abstract submissions are strictly requested to use the abstract template and should not exceed 2 pages of length.
Abstract template: https://cti-online.net/dl/book-GenAI/structured_abstract.docx
We plan to publish this book in the second half of 2025 in Springer publishing house (Cham) in the book series Lecture Notes in Networks and Systems
Indexed in: SCOPUS, DBLP, INSPEC, EI Compendex, SCImago, …
Call for Paper publication: January 15, 2025
Chapter manuscript proposals due (2-page abstract): March 01, 2025
Feedback and manuscript invitation (pending publisher decision): March 20, 2025
Full chapter manuscripts due: June 01, 2025
Notification of reviewers’ feedback: June 30, 2025
Final chapter manuscript submission: August 30, 2025
Notification of final decision: September 20, 2025
Expected publication date: December 2025
Please note that there is a publishing fee of 500 EUR per chapter for inclusion in this upcoming book.
The text is divided in four different sections that compile and group main curriculum subjects:
Section 1: Generative AI in STEM
This section aims to discuss how Generative AI can help students to more effectively understand topics from mathematics, physics, chemistry, biology, technology and engineering by enhancing scientific inquiry, supporting hypothesis generation, and offering personalized learning paths. In addition, the section will discuss how Generative AI enables teachers to automate assessments, create custom exercises, and track student progress. Ethical considerations around AI in scientific data analysis and student experimentation will also be examined.
Section 2: Gen AI in Language Learning and Literature
This section will discuss how Gen AI transforms language learning and literature. The section aims to investigate how Gen AI can enhance language acquisition in areas like vocabulary development, reading comprehension, and speaking fluency through conversation simulations. Contextual language practice, customized reading materials and feedback on writing are alos cases cases for investigation. The section will explore how Gen AI can assist in analyzing written works, such as novels, poems, plays, and essays. Additionally, it will address the impact of AI-generated content on students’ critical thinking, creativity, writing and analytical abilities while considering ethical concerns, including data privacy, cultural understanding.
Section 3: Generative AI in Social Studies
Gen AI can enhance social studies education by creating interactive learning experiences that bring historical events, cultural studies, and geography to life. AI tools can generate historical simulations, craft personalized quizzes, and provide real-time feedback, making abstract concepts more accessible. The section will explore how Gen AI can support inquiry-based learning, foster critical thinking, and help students explore diverse perspectives on social issues. Additionally, it addresses the potential drawbacks of AI-generated content, such as ensuring historical accuracy and avoiding bias in presenting social and political contexts.
Section 4: Generative AI in Art and Design
This section will explore how Gen AI offers innovative tools for fostering creativity and experimentation in art and design education by generating visuals and creating digital art, sketching, painting, and graphic design. This section examines how Gen AI enhances creative expression by supporting students in developing their artistic skills and offering new ways to experiment. It also discusses challenges such as balancing human creativity with machine-generated content in art education.
