Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…

This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…

The introduction of real-world, meaningful tasks in mathematics classrooms promises to create opportunities for enhancing students' learning through active engagement with mathematical ideas; however, researchers have given little consideration to the contexts in which urban high-school students live. The case study of three students reported in…

We describe and use an analytical framework to document mathematics discourse in instruction (MDI), and interpret differences in mathematics teaching. MDI is characterised by four interacting components in the teaching of a mathematics lesson: exemplification (occurring through a sequence of examples and related tasks), explanatory talk (talk that…

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

Data-mined models often achieve good predictive power, but sometimes at the cost of interpretability. We investigate here if selecting features to increase a model's construct validity and interpretability also can improve the model's ability to predict the desired constructs. We do this by taking existing models and reducing the feature set to…

A "Framework for K-12 Science Education" identified eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science…

Simulation games can play a critical role in enabling students to navigate the problem spaces of the past while simultaneously critiquing the models designers offer to represent those problem spaces. There is much to be gained through their use. This includes rich opportunities for students to engage the past as independent historians; to consider…

Background: Teacher-related factors such as gender, experience, conceptions related to mathematics, instructional practices have effects with various magnitudes on students' mathematics achievement. Classroom related factors such as class size, class climate and limitations to teaching and their relation to mathematics achievement have also been…