This study aimed to identify the levels of computational thinking skills, computational self-efficacy, and academic well-being among students, identify the potential relationships among them, and determine the predictive effects of computational thinking skills and computational self-efficacy on academic wellbeing. The study used the following…

The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation.…

This article reports research into calculative and optionalized forms of online/blended course design in higher education. This was investigated through a critical case study, centered on two faculty members and one instructional designer at a university in the United States, and using an interpretive framework that highlighted the effects of…

This study demonstrates how to evaluate a university-wide online course designed to support student transition into university by using Propensity Score Matching (PSM) and Doubly Robust Estimation (DRE). Using data from seven academic years, from 2016/17 to 2022/23, with more than 28,000 students, we examine whether enrolment in this optional…

Computational thinking (CT) is becoming increasingly important for K-12 science education, thus warranting new integrations of CT and science content. This intervention study integrated CT through unplugged, or handwritten, algorithmic explanations of natural selection. As students investigated natural selection in varying contexts (specific and…

As adults, we represent and think about number, space, and time in at least two ways: our intuitive--but imprecise--perceptual representations, and the slowly learned--but precise--number words. With development, these representational formats interface, allowing us to use precise number words to estimate imprecise perceptual experiences. We test…

Background and Aims: Epidemiological studies have provided invaluable insight into the origin and impact of low language skills in childhood and adolescence. However, changing terminology and diagnostic guidelines have contributed to variable estimations of the prevalence of developmental language difficulties. The aim of this review was to…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

Impaired numerosity perception in developmental dyscalculia (low "number acuity") has been interpreted as evidence of reduced representational precision in the neurocognitive system supporting non-symbolic number sense. However, recent studies suggest that poor numerosity judgments might stem from stronger interference from non-numerical…

We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…

Multidimensional Item Response Theory (MIRT) has been widely used in educational and psychological assessments. It estimates multiple constructs simultaneously and models the correlations among latent constructs. While it provides more accurate results, the unidimensional IRT model is still dominant in real applications. One major reason is that…

One of the most prominent social influences on human decision making is conformity, which is even more prominent when the perceptual information is ambiguous. The Bayes optimal solution to this problem entails weighting the relative reliability of cognitive information and perceptual signals in constructing the percept from self-sourced/endogenous…

Cognitive diagnosis models (CDMs) are the assessment tools that provide valuable formative feedback about skill mastery at both the individual and population level. Recent work has explored the performance of CDMs with small sample sizes but has focused solely on the estimates of individual profiles. The current research focuses on obtaining…

The development of young children's counting has been extensively researched, yet detailed studies that examine development over multiple years are curiously absent from the literature. This research examined 15 preschoolers' (ages 3-4) use of number words as they engaged in two counting tasks, an oral counting task and counting a collection of 31…

Background and Context: Computational thinking (CT) is a fundamental skill and a new form of literacy that everyone should develop to participate in civic society. Sequencing and algorithmic thinking are at the core of CT. This study looked into how young children enrolled in a kindergarten in Colombia develop CT skills. Objective: This paper aims…