Science, technology engineering, and mathematics (STEM) professions offer competitive earnings, tend to be compatible with technological advances, and are predicted to remain in high demand in the future. Many countries, including Greece, have prioritised STEM education on their educational agendas, aiming to prepare students for careers in these…

As education systems adapt to evolving societal and technological demands, mathematics curricula must also evolve. Recent trends highlight challenges such as declines in student performance and gaps between intended learning goals and real-world applications. Integrating competencies like data literacy, computational thinking, and problem-solving…

In Singapore, where primary and secondary students routinely top standardized worldwide mathematics examinations, a paradox emerges: when reaching university, many struggle to apply their skills critically in real-world contexts. This commentary examines the challenges and strategies involved in teaching quantitative reasoning (QR) to…

School leadership in education is thinking, communicating, and modeling to maximize student growth and achievement. This quantitative research study explored how school leadership can strengthen the academic progress of students within Multi-Tiered Systems of Support (MTSS). When implementation of MTSS is guided by adaptive school leadership,…

Many aspects of noticing in the classroom are tacitly understood by experienced educators. In this case study, we pair ecological and cognitive psychology with computer-augmented analysis of video data to try to better understand some of the tacit elements of educator noticing and decision-making. The ecological model of noticing views noticing as…

We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…

Student success is becoming a shared vision for quality in higher education. Majority data in higher education have not been transformed into actionable insights for quality enhancement. Data are dispersed among stakeholders, and stakeholders' data literacy influences the effectiveness of using data for student success. However, existing studies…

The Stanford Education Data Archive (SEDA) launched in 2016 to provide nationally comparable, publicly available test score data for U.S. public school districts. I introduce a special collection of six articles that each use SEDA to lend their questions and findings a national scope. Together, these articles demonstrate a range of uses of SEDA…

Most research on learning technology uses clickstreams and questionnaires as their primary source of quantitative data. This study presents the outcomes of a systematic literature review of empirical evidence on the capabilities of multimodal data (MMD) for human learning. This paper provides an overview of what and how MMD have been used to…

Big data is a unique field of study which requires specialized analytics. The field of education has a lot of data: individual student test scores, attendance, behavior, and demographic data are just some of the regularly collected information year after year. Individual student data across an entire state over several years quickly becomes big…

Conceptual stances provide guidance to the mixed methods researcher as he or she makes decisions throughout the research process, including determining the dimensions of integration or levels at which mixing occurs. Only the dialectic conceptual stance specifically encourages mixing at the abstract paradigmatic level. This article outlines four…

Many ethical concerns in online big data research stem from a pervasive assumption that data are disembodied and place-less. While some scholars have begun addressing the ethical dilemmas of big data, few offer approaches or tools that fully grapple with the situatedness of online data and its ethical implications. We draw on feminist new…

Social media data (SMD) is driven by statistical and analytical technologies to obtain information for various decisions. SMD is vast and evolutionary in nature which makes traditional data warehouses ill suited. The research aims to propose and implement novel framework that analyze tweets data from online social networking site (OSN; i.e.,…

A mixture extension of Samejima's continuous response model for continuous measurement outcomes and its estimation through a heuristic approach based on limited-information factor analysis is introduced. Using an empirical data set, it is shown that two groups of respondents that differ both qualitatively and quantitatively in their response…

In regression analysis courses, there are many settings in which the response variable under study is continuous, strictly positive, and right skew. This type of response variable does not adhere to the normality assumptions underlying the traditional linear regression model, and accordingly may be analyzed using a generalized linear model…