A shift from teaching to learn to learning to think is necessary to promote critical thinkers. Since teachers tend to replicate the educational models they have experienced as students, new references are needed. In order to address these concerns, we present an interdisciplinary intervention in initial teacher education and analyse its impact on…

The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' expectations before and after their laboratory courses and experiences. Although the MLLI has been used in various studies and laboratory environments to investigate students' cognitive and affective laboratory expectations, the authors of the instrument…

Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…

To best prepare students for the real-world research environment, key skills, including experimental design, data analysis, communication of results, and critical thinking, should be key components of undergraduate science courses. Furthermore, the impact of the COVID-19 pandemic on in-person teaching has resulted in a need to develop courses that…

Background: Sexual health includes physical, emotional, mental, and social wellbeing related to sexuality. Given people with mild intellectual disabilities' reliance on relatives and support staff, it is important to explore the latter's understanding of sexual health. Method: Relatives (n = 7) and support staff (n = 15) of people with mild…

This article examines the use of the repertory grid technique as a method to investigate learner perceptions in language education research. An important issue raised in this article concerns how far a researcher's agenda may be unintentionally imposed onto a research study which is investigating learners' perceptions, and how far the ensuing data…

Data literacy, an important goal for social studies education, involves teaching students how to comprehend, analyze, interpret, evaluate, create, and argue with data and data visualizations such as timelines, maps, and graphs. Digital data visualizations support rapid inquiry and explorations that would be difficult on paper - such as adding data…

Entrepreneurship education has evolved to meet the demands of a dynamic business environment, necessitating innovative teaching methods to prepare entrepreneurs for market uncertainties. Large Language Models (LLMs) like the Generative Pre-trained Transformer 4 (GPT-4), recognized for their exceptional performance on public datasets, are examined…

Many students persistently misinterpret histograms. This calls for closer inspection of students' strategies when interpreting histograms and case-value plots (which look similar but are different). Using students' gaze data, we ask: "How and how well do upper secondary pre-university school students estimate and compare arithmetic means of…

The 2021-22 Civil Rights Data Collection (CRDC) is a mandatory survey of all public school districts and schools serving students in preschool through grade 12 in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico and therefore includes data from 17,704 public school districts also known as local education agencies (LEAs) and…

Students develop process skills through repeated practice of data interpretation, problem solving, and critical thinking. The primary literature provides a rich source of data and application problems to engage students in this practice within the context of chemistry content knowledge. However, most existing classroom activities based on the…

Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim…

This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…

U.S. colleges and universities are under increasing pressure to appear racially diverse, but have yet to account systematically for a quickly growing contingent of multiracial-identifying students. Drawing on interviews with multiracial-identifying undergraduates at Western University, I demonstrate how everyday university practices compromise…

As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…