Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

Multi-lab projects are large scale collaborations between participating data collection sites that gather empirical evidence and (usually) analyze that evidence using meta-analyses. They are a valuable form of scientific collaboration, produce outstanding data sets and are a great resource for third-party researchers. Their data may be reanalyzed…

This paper scrutinizes the increasing trend of using international large-scale assessment (ILSA) data for causal inferences in educational research, arguing that such inferences are often tenuous. We explore the complexities of causality within ILSAs, highlighting the methodological constraints that challenge the validity of causal claims derived…

This article explores potential uses, misuses, beneficiaries, and tensions of learning analytics in higher education. While those promoting and using learning analytics generally agree that ethical practice is imperative, and student privacy and rights are important, navigating the complex maze of ethical dilemmas can be challenging, particularly…

Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…

This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from…

As a result of the growing commercial marketplace for teachers' digital data, a new organization that includes educational data brokers has evolved. Educational data brokerage is relatively intangible due to the ease of de-identified data being collected and sold via educational technology. There is an urgent need to expose how the brokerage of…

Rapidly developing technological advances have raised new questions about what makes us uniquely human. As data and generative AI become more powerful, what does it mean to learn, teach, create, make meaning, and express ourselves, even as machines are trained to take care of these tasks for us? With youth, and in the context of literacy and media…

In today's digital world, higher education institutions collect and use more data than ever. However, institutional silos create barriers for stakeholders who need data for daily operations and strategy. This article presents a vision of a unified, collaborative future for data governance and actionable steps stakeholders can take.

The Data Must Speak (DMS) Positive Deviance research aims to improve the equity and quality of education through the use of data by studying the practices and behaviours of 'positive deviant' schools -- schools that outperform others despite operating in similar contexts and with equivalent resources. The analysis aims to inform practical…

Whilst technology may have been the 'saviour' of HE from the immediate challenges of the pandemic, the opportunistic dialogue emerging in response is imbued with notions of the pandemic as a catalyst for change. Empowered by the apparent success of technology's deliverance, the door has been opened to unprecedented investment into a pervasive and…

The purpose of this project is to explore the limitations of federal postsecondary data as data as those data relate to Indigenous students and to Tribal Colleges and Universities. After first establishing some of the statistical limitations we commonly find in postsecondary data with Indigenous students, we provide strategies and practices that…

Coaching is a form of professional learning that can contextualize learning and personalize the development of knowledge and skills to improve professional practice and the student experience. Coaching for equity-oriented continuous improvement needs be defined differently than instructional coaching since the schools are focused on changing…

New challenges in education demand effective solutions. Although Learning Analytics (LA), Educational Data Mining (EDM) and the use of Big Data are often presented as a panacea, there is a lot of ground to be covered in order for the EDM to answer the real questions of educators. An important step toward this goal is to implement holistic…

Artificial intelligence (AI) and big data methodologies have provided a vast possibility of applications in different public policy sectors. AI and big data provide essential innovations in school teaching and learning practices, curriculum, and management in education, transforming the entire formulation and implementation of education policy.…