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…

Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…

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 field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA's main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated…

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…

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…

Amid the increasing reliance on digital tools and services in education, this article examines the datafication and commodification of student life in Denmark. We analyse the web and app (iOS and Android) versions of 45 tools and services that teachers in Danish public primary schools use as part of their teaching, the types of data generated by…

In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

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…

The last decade has seen a rise in big data approaches, including in the humanities, whereby large quantities of data are collected and analysed. In this paper, we discuss long-form audio recordings that result from individuals wearing a recording device for many hours. Linguists, psychologists and anthropologists can use them, for example, to…

School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel…

Whilst there is plenty of debate on the nature and role of data in social science research, data in schools tend to be understood in terms of numbers and used in limited ways linked primarily to attainment. The 'datafication' of schooling has been strongly critiqued for its powerful impacts on policy and practice, pupils' experience, the…

The purpose of this paper is to analyze the use of the exemplar methodology (ExM) as a method for selecting exemplars in education research. ExM is a systematic approach to selecting outliers that can be used to education researchers who investigate outliers to better understand phenomena among students, teachers, schools, and communities. While…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…