Recent worldwide epidemiological surveys of autism conducted in 37 countries are reviewed; the median prevalence of autism is 0.97% in 26 high-income countries. Methodological advances and remaining challenges in designing and executing surveys are discussed, including the effects on prevalence of variable case definitions and nosography, of…

As Computer Science has increased in popularity so too have class sizes and demands on faculty to provide support. It is therefore more important than ever for us to identify new ways to triage student questions, identify common problems, target students who need the most help, and better manage instructors' time. By analyzing interaction data…

Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…

We are currently in a century of data where massive amount of data are collected and processed every day, and machine learning plays a critical role in automatically processing the data and mining useful information from it for making decisions. Despite the wide and successful applications of machine learning in different fields, the robustness of…

This manuscript builds on a novel, automatic, freely-available Bayesian approach to extract information in abstracts and titles to classify research topics by quartile. This approach is demonstrated for all N= 149,129 ISI-indexed publications in biological sciences journals during 2017. A Bayesian multinomial inverse regression approach is used to…

We examine how the politics of knowledge production limit research on the relationship between immigration status and social inequality. We centre the practices of methodological nationalism in Canada, a traditional country of permanent immigration in which temporary migration has become a core feature of the immigration system. In this case,…

Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…

This study investigated with the help of in-depth interviews and a think-aloud-approach how 10- to12-year-old children (n = 46) in the Canton of Berne, Switzerland, get to know species, how they identify plants and animals, and for how important they consider species knowledge to be. Own observations and sensual experiences coupled with positive…

In mathematics, the keyword strategy involves identifying a keyword and using that keyword to determine the operation needed to find a word problem's solution. We analyzed 747 high-stakes released items across grades 3, 4, 5, 6, 7, and 8. Of these, 57 items did not involve written text. Of the 690 text-based items, we classified 69% as directive…

In recent times, Educational Data Mining and Learning Analytics have been abundantly used to model decision-making to improve teaching/learning ecosystems. However, the adaptation of student models in different domains/courses needs a balance between the generalization and context specificity to reduce the redundancy in creating domain-specific…

This study examined the distribution of language expansion in parent-child (preschool aged) mealtime conversations in 30 Chinese middle-class families. The conversations were categorised into four types: "contextualised & conflicted," "contextualised & non-conflicted," "decontextualised & conflicted," and…

English Learner-classified (ELC) students are one of the nation's most marginalized student populations. One promising but understudied strategy to strengthen teaching of ELC students is teacher induction. This article examines the role of teacher induction in strengthening novice teachers' EL-specific teaching knowledge and skills. Through a…

Histories of statistics and quantification have demonstrated that systems of statistical knowledge participate in the construction of the objects that are measured. However, the pace, purpose, and scope of quantification in state bureaucracy have expanded greatly over the past decades, fuelled by (neoliberal) societal trends that have given the…

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…

Comparative studies on 'apprenticeships' in Europe increasingly cover a variety of programmes previously not considered under this heading. The paper explores the potential of a new, combined cultural-historical and functional classification of apprenticeships on the basis of their underpinning training logic. Four main logics are discussed which…