High-volume, high-quality and diverse datasets are crucial for advancing research in the education field. However, such datasets often contain sensitive information that poses significant privacy challenges. Traditional anonymisation techniques fail to meet the privacy standards required by regulations like GDPR, prompting the need for more robust…

The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent…

Preparing data-literate citizens and supporting future generations to effectively work with data is challenging. Engaging students in Knowledge Building (KB) may be a promising way to respond to this challenge because it requires students to reflect on and direct their inquiry with the support of data. Informed by previous studies, this research…

With improving technology and monitoring efforts, the availability of scientific data is rapidly expanding. The tools that scientists and engineers use to analyse data are changing in response. At the same time, science education standards have shifted to emphasize the importance of students making sense of data in science classrooms. However, it…

In today's information age, developing data science competencies has become vital to fostering responsible citizenry. However, the actual techniques learners need to become proficient in are still somewhat "in-construction", as the relatively new field of data science is constantly expanding to meet new data-related demands. Data science…

The field of learning analytics has advanced from infancy stages into a more practical domain, where tangible solutions are being implemented. Nevertheless, the field has encountered numerous privacy and data protection issues that have garnered significant and growing attention. In this systematic review, four databases were searched concerning…

How do people reason with data to make sense of the world? What implications might everyday practices hold for data literacy education? We leverage the unique context of the COVID-19 pandemic to shed light on these questions. COVID-19 has engendered a complex, multimodal ecology of information resources, with which people engage in high-stakes…

Learning analytics research presents challenges for researchers embracing the principles of open science. Protecting student privacy is paramount, but progress in increasing scientific understanding and improving educational outcomes depends upon open, scalable and replicable research. Findings have repeatedly been shown to be contextually…

With Big Data revolution, the education sector is being reshaped. The current data-driven education system provides many opportunities to utilize the enormous amount of collected data about students' activities and performance for personalized education, adapting teaching methods, and decision making. On the other hand, such benefits come at a…

Data literacy has been suggested as an important competence that individuals need to succeed in a data-intensive society. However, there is no common understanding as to what data literacy entails and how it could be developed. Instructional emphasis on developing competence of individuals fails to capture learners' relationship to data in…

Whilst learning analytics is still nascent in most African higher education institutions, many African higher education institutions use learning platforms and analytic services from providers "outside" of the African continent. A critical consideration of the protection of data privacy on the African continent and its implications for…

In this study, support for teaching data literacy in social studies is provided through the design of a pedagogical support system informed by participatory design sessions with both pre-service and in-service social studies teachers. It provides instruction on teaching and learning data literacy in social studies, examples of standards-based…

Evidence shows that appropriate use of technology in education has the potential to increase the effectiveness of, eg, teaching, learning and student support. There is also evidence that technology can introduce new problems and ethical issues, e.g., student privacy. This article maps some limitations of technological approaches that ensure…

To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K-12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created,…

Data-art inquiry is an arts-integrated approach to data literacy learning that reflects the multidisciplinary nature of data literacy not often taught in school contexts. By layering critical reflection over conventional data inquiry processes, and by supporting creative expression about data, data-art inquiry can support students' informal…