This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…

Today, the use of software in qualitative research analysis is rapidly becoming widespread among researchers. Researchers manage large data sets using features such as editing data, transcribing, creating codes, and searching within data. However, while the data analysis uses software in a format, the analysis of the essence of the data is done by…

A technology-based problem-solving test can automatically capture all the actions of students when they complete tasks and save them as process data. Response sequences are the external manifestations of the latent intellectual activities of the students, and it contains rich information about students' abilities and different problem-solving…

The ongoing 'datafication' of contemporary society has a number of implications for schools and schooling. One is the increasing calls for schools to help develop young people's understandings about the role that digital data now plays in their everyday lives -- especially in terms of the 'data economy' and 'surveillance capitalism'. Reporting on…

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose…

Background: Over the last 20 years, educational large-scale assessments have undergone dramatic changes moving away from simple paper-pencil assessments to innovative, technology-based assessments. This comprehensive switch has led to some rather technical improvements such as identifying early guessing or improving standardization. Objectives: At…

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

Billions in federal COVID-19 relief funds poured into Louisiana schools between 2021 and 2024. But how were systems using the funds? Beginning in 2022, the Louisiana Department of Education partnered with the Region 14 Comprehensive Center to design a groundbreaking fiscal data visualization solution--EPIC (Education Progress and Investment…

Multimedia information fusion technology is currently a popular technology for data processing. The advanced productivity it brings is dozens of times that of traditional data information processing. The collected and processed information is not only efficient and accurate, but also has strong scalability. With the continuous development of…

With the rapid development of information technology, various online education platforms support the sharing of digital educational resources. Because digital educational resources are simple to duplicate and disseminate quickly, there exists copyright infringement, which threatens the interests of copyright owners. In addition, the existing…

Digital technologies have the potential to revolutionize education by enhancing quality, fairness, and efficiency. However, equitable access to these technologies remains a challenge. ILSAs (international large-scale assessments) have shown that the relationship between digital use and performance varies across countries and over time. To fully…

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…

This article presents Python codes that can be used to extract data from Securities and Exchange Commission (SEC) filings. The Python program web crawls to obtain URL paths for company filings of required reports, such as Form 10-K. The program then performs a textual analysis and counts the number of occurrences of words in the filing that…

In a wide range of fields, professional practice is being transformed by the increasing influence of digital analytics: the massive volumes of big data, and software algorithms that are collecting, comparing and calculating that data to make predictions and even decisions. Researchers in a number of social sciences have been calling attention to…