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…

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly,…

In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…