With growing social science interest in new materialist and posthuman ontologies, it is timely to explore how these may translate practically into social research methodologies. This task is complicated by differing interpretations of how new materialist precepts should shape research. This paper aims to fill a gap in the literature by setting out…

Teacher agency is a set of actions that a teacher takes beyond what is generally expected of them. The concept merits examination, as agency can bolster teachers' ability to set and achieve professional development goals. To better understand how to study, and use, this relatively new concept in the academic literature, a systematic review of 164…

A version of the classic rotationally resolved infrared (IR) spectrum of a diatomic molecule experiment has been developed using the POGIL framework to more fully engage students in the collection, modeling, analysis, and interpretation of the data. An analysis of the experimental protocol reveals that the POGIL approach actively engages students…

Despite vital professional development support through the National Art Education Association's Data Visualization Working Group and other scholars' engagement with the topic in the literature, pedagogical literature that connects contemporary data visualization methods to art teaching practices is limited. While acknowledging that many of us have…

Facebook is widely used and researched. However, though the data generated by educational technology tools and social media platforms other than Facebook have been used for research purposes, very little research has used Facebook posts as a data source--with most studies relying on self-report studies. While it has historically been impractical…

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,…

This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…

Consultee-Centered Consultation (CCC) is built upon the use of a constructivist, interactive approach to support conceptual change in consultees. Constructivism is foundational in ethnographic traditions as well and it focuses on understanding socially constructed meaning-making in cultural groups. Given the importance of constructivism in both…

Technology and data analysis have evolved into a resource-rich tool for collecting, researching and comparing student achievement levels in the classroom. There are sufficient resources to discover student success through data analysis by routinely collecting extensive data on student behaviour and curriculum structure. Educational Data Mining…

Machine learning-based modeling technology has recently become a powerful technique and tool for developing models for explaining, predicting, and describing system/human behaviors. In developing intelligent education systems or technologies, some research has focused on applying unique machine learning algorithms to build the ad-hoc student…

This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research…

Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…

Businesses and other organizations across the globe are becoming more and more data-driven, using a combination of descriptive, diagnostic, predictive and prescriptive analytics to gain a strategic advantage through understanding the past, what we hope to happen in the future, and the ability to accurately predict future outcomes. These forms of…