Educational researchers continue to polarize into 'qualitative' and 'quantitative' camps, with these terms often functioning as global identity markers, rather than as styles of research that are available to anyone. Many scholars have lamented the drawbacks of researchers being siloed into opposing, apparently incommensurable research paradigms,…

This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…

Queering' questions, unlearns, disrupts, and transforms approaches, expectations, and realities. Futures are time and change. The approach I have designed to operationalize Queering and futures, or Queering futures, is the Queering Futures Framework (QFF). The Queering Futures Framework (QFF) is a brand-new transdisciplinary research framework…

In the past two decades, the interdisciplinary push to denaturalise the concept of society has historicised the very object of social history. In this paper, I propose a way of studying the social history of education that eludes the presupposition of the social as a transcendental or pre-discursive object. My central claim is that it is possible…

This article demonstrates how a technique called Agent-Based Modelling can address a significant challenge for effective interdisciplinarity. Different disciplines and research methods make divergent assertions about what a satisfactory explanation requires. However, without a unified framework analysing the implications of these differences…

Design literacy is an emerging research field that is gaining attention among scholars today. Credit goes to the growing acceptance of design thinking in various disciplines beyond design. Design literacy develops natural abilities in everyone to solve real-world, wicked problems by supporting the cognitive development of concrete (making things)…

Increasing representation of first-generation, low-income, and students of color has been considered critical in developing an inclusive and competitive future workforce. However, research has noted significant difficulties with continued engagement and persistence for those engaged in STEM-based activities, with literature showing at-promise…

We propose cross-disciplinary learning as a construct that can guide instruction and assessment in programs that feature sequential learning across multiple science disciplines. Crossdisciplinary learning combines insights from interdisciplinary learning, transfer, and resources frameworks and highlights the processes of resource activation,…

Purpose: The purpose of this paper is to develop an analytical framework toward facilitating the quantitative measurement of interdisciplinary understanding regarding sustainable energy systems with an application in the area of capacity-building projects in higher education. Design/methodology/approach: The analytical framework is developed using…

Despite growing calls to develop data science students' ethical awareness and expand human-centered approaches to data science education, introductory courses in the field remain largely technical. A new interdisciplinary data science program aims to merge STEM and humanities perspectives starting at the very beginning of the data science…

'QuantCrit' (Quantitative Critical Race Theory) is a rapidly developing approach that seeks to challenge and improve the use of statistical data in social research by applying the insights of Critical Race Theory. As originally formulated, QuantCrit rests on five principles; 1) the centrality of racism; 2) numbers are not neutral; 3) categories…

This paper presents a novel design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using the data science competition platform Kaggle. Peer learning is…

The current COVID-19 situation has seen a plethora of data, statistics and predictions presented to society--some making incredible claims. The authors are concerned that statistics and probability still receive inadequate attention in the classroom, leaving students without the statistical literacy needed to make sense of the claims being made.…

Teaching economic history requires the study of how to combine the economists' modeling and statistical methods with the methods used by historians and the other social sciences. It often involves learning how to search for quantitative data from a variety of sources and then building panel datasets that match the data found with existing…

This article analyses the use of peer evaluation as a tool for evaluating teamwork and students' perceptions of this type of evaluation. A study was conducted of six subjects included on five degree courses at the University of Girona. In all of these subjects, students carried out a team activity, evaluated the performance of the team and the…