Modelling roles of mathematics in physics has proved to be a difficult task, with previous models of the interplay between the two disciplines mainly focusing on mathematical modelling and problem solving. However, to convey a realistic view of physics as a field of science to our students, we need to do more than train them to become fluent in…

Human one-on-one coaching involves complex multimodal interactions. Successful coaching requires teachers to closely monitor students' cognitive-affective states and provide support of optimal type, timing, and amount. However, most of the existing human tutoring studies focus primarily on verbal interactions and have yet to incorporate the rich…

In real-world situations, multidimensional data may appear on large-scale tests or attitudinal surveys. A simple structure, multidimensional model may be used to evaluate the items, ignoring the cross-loading of some items on the secondary dimension. The purpose of this study was to investigate the influence of structure complexity magnitude of…

Young children can quickly and intuitively represent the number of objects in a visual scene through the Approximate Number System (ANS). The precision of the ANS--indexed as the most difficult ratio of two numbers that children can reliably discriminate--is well known to improve with development: whereas infants require relatively large ratios to…

A relevant aim of research in education is to find and study the reasoning lines that students deploy when dealing with problematic situations. This can be done through an analysis of the answers students give to a questionnaire. In this paper, we discuss some methodological aspects involved in the quantitative analysis of a questionnaire by means…

Personalized education systems recommend learning contents to students based on their capacity to accelerate their learning. This paper proposes a personalized exercise recommendation system for online self-directed learning. We first improve the performance of knowledge tracing models. Existing deep knowledge tracing models, such as Dynamic…

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary…

This study tested a proposed model consisting of mathematics anxiety, mathematics self-efficacy, and implicit theories of intelligence in predicting mathematics and science career interest in middle school students, while controlling for student math level. One hundred fifty-two seventh-grade students in a middle school in the USA participated in…

The purpose of this study is to investigate relationships between elementary-level educators' perceptions of their school's implementation of Green's four-dimensional model of educational leadership and the percentage of students proficient in Language Arts and in Mathematics, averaged over three years. Represented by responses to twenty items…

The study explores the influences of critical thinking and interests on students' performance at school. The tested students attended German grammar schools ("Gymnasien"). Separate regression analyses showed the expected moderate positive influences of critical thinking and interests on school performance. But analyzed simultaneously,…

Using two states' grades 3 through 8 state assessment databases, this study documents the extent to which students were assigned testing accommodations for ELA or mathematics in only one of two consecutive years. The percentage of students with disabilities who were assigned accommodations in the current year only or in the prior year only in a…

General diagnostic models (GDMs) and Bayesian networks are mathematical frameworks that cover a wide variety of psychometric models. Both extend latent class models, and while GDMs also extend item response theory (IRT) models, Bayesian networks can be parameterized using discretized IRT. The purpose of this study is to examine similarities and…

This study uses multilayer minimum spanning tree analysis to develop a model for student retention from a complex system perspective, using data obtained from first-year engineering students at a large well-regarded institution in the European Union. The results show that the elements of the system of student retention are related to one another…

One goal among many in early childhood education and care (ECEC) is that children develop positive attitudes towards mathematics. In order to support this development, teachers need professional competence in both cognitive and affective-motivational facets. Teacher students need to develop this professional competence during their initial teacher…

Student modeling can help guide the behavior of a cognitive tutor system and provide insight to researchers on understanding how students learn. In this context, Bayesian Knowledge Tracing (BKT) is one of the most popular knowledge inference models due to its predictive accuracy, interpretability and ability to infer student knowledge. However,…