Call for Proposals for an Edited Volume to be published by Routledge
International Perspectives on Educational Data Literacy: Frameworks, Contexts, and Practices
Editors: Clara Schumacher1 and Dirk Ifenthaler2,3
1University of Potsdam, Germany, 2University of Mannheim, Germany, 3Curtin University, Australia
Data have always been collected in educational contexts, but with the advent of educational technologies, they are enhanced by data from learners' and teachers' interactions with these systems. With learning analytics, data collection, analysis, and visualizations are realized in near real-time. In addition, data-based decision-making in education has gained increased interest (Mandinach & Schildkamp, 2021). However, to make use of the additional insights to inform teaching or learning processes as well as educational decision-making, the involved stakeholders need to be educational data literate (Schildkamp, 2019). Educational data literacy or data literacy for learning and teaching is often not sufficiently distinguished from other related concepts, such as assessment literacy (Mandinach & Gummer, 2013). Educational data literacy includes statistical literacy, assessment literacy, pedagogical knowledge, and data-driven decision-making (Henderson & Corry, 2021). Mandinach et al. (2015, p. 3) define data literacy for teaching as „the ability to transform information into actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data (assessment, school climate, behavioral, snapshot, longitudinal, moment-to-moment, etc.) to help determine instructional steps. It combines an understanding of data with standards, disciplinary knowledge and practices, curricular knowledge, pedagogical content knowledge, and an understanding of how children learn.“. The Learn2Analyze initiative defined educational data literacy as „The ability to collect, manage, analyze, comprehend, interpret, and apply educational data in an ethical, meaningful, and critical manner.“ (Sampson et al., 2022, p. 32).
This edited book aims to provide a comprehensive overview of the current state of the art of the emerging and current topic of educational data literacy. In addition, it seeks to integrate definitions of the concept and fragmented approaches taking place in different countries or contexts. Furthermore, since learning analytics were established in 2010, some institutions have made use (initial) implementations of learning analytics systems to inform teaching. These advances impact what constitutes teachers' educational data literacy, the need to foster it, and the volume and types of data available.
Therefore, we seek contributions to the following tentative topics and potential key areas of the volume:
1. Introduction to Educational Data Literacy
This section includes an Introduction with key concepts and the current state of research (systematic review). In addition, a chapter on the historical context provides a brief overview of the evolution of data literacy in education and how it has become increasingly important in the digital age. It is of interest to gain an overview of the different perspectives in different countries and educational contexts.
2. Theoretical Frameworks of Educational Data Literacy
This section explores existing theoretical frameworks and models contributing to understanding educational data literacy. This may include psychological, pedagogical, data science, and computer science perspectives. In addition, this may incorporate the distinction of educational data literacy from other concepts, such as data or assessment literacy, and how they relate to or enhance each other. Furthermore, this may encompass assessment measures that are available or under development to investigate educational data literacy.
3. Technology Integration and Tools
This section focuses on developing educational data literacy competence among educators, learners, and other stakeholders. It may include contributions focused on data visualization tools for enhancing educational data literacy and examining how educational organizations implement data management systems to organize and utilize educational data effectively.
4. Case Studies on Educational Data Literacy
This section provides insights into case studies, for instance, with a focus on “Ethical Dilemmas in Educational Data Use,” “Data-Driven Decision Making in Educational Leadership,” “Professional Development for Educators in Data Literacy”, “Implementing Data Literacy Programs in K-12 Education,” “International Perspectives on educational data literacy”, “Comparison of educational data literacy in different educational contexts” or “Integrating Data Literacy into Higher Education Curriculum.”
The volume aims to increase mutual learning on educational data literacy from different contexts. Therefore, we invite, besides researchers, practitioners, and policymakers to contribute to this volume.
Call for Proposals
If you are interested in contributing to the book project, we are asking you to submit a chapter proposal, including title, authors, affiliations, abstract describing the content of the chapter (max. 500 words), five keywords, three key references and a description of how the chapter fits the theme of the book, no later than 31 May 2024.
Please submit the chapter proposal no later than 31 May 2024 as a single PDF document, including all required information via e-mail (clara.schumacheruni-potsdam.de).
All submissions will undergo a rigorous double-masked peer review, recommending full submissions from among the proposals. Accepted chapters shall not exceed 8,000 words and shall be completed no later than 31 December 2024. Specific guidelines will be made available upon notification of acceptance.
Proposed Timeline
31 May 2024: Proposal including title, authors, affiliations, abstract (max. 500 words), keywords, references, and chapter contribution to the edited volume.
30 June 2024: Notification of acceptance and further information to submit full chapters to authors.
31 December 2024: Submission deadline for draft chapters (max. 8,000 words)
15 January 2025: Reviewers' feedback sent to authors
28 February 2025: Final chapters due
31 March 2025: Final book manuscript submitted to the publisher
For any inquiry, please contact clara.schumacheruni-potsdam.de