The aim of this qualitative research is to describe the thinking process as a profile of students' mathematical computational thinking (CT) skills in terms of CT attitudes. The subjects in this study were 66 junior high school students in grade IX. There were three students taken by purposive sampling based on high, medium, and low CT attitude.…

Computational thinking (CT) is widely recognized as a fundamental skill in the information age. However, within the context of Chinese early childhood education (ECE), CT remains underrepresented, with a notable gap in the availability of developmentally appropriate and rigorously validated assessment tools designed specifically for…

Purpose: This study focuses on examining how individual differences, including biological, linguistic, and cognitive traits, and prosodic focus affect the computation biases and reaction time (RT) associated with quantity scalar terms in Mandarin-speaking children aged 3-8 years. Method: The participants of this study were 27 Mandarin-speaking…

Blended learning in higher education is evolving to be more personalized, diverse, innovative, student-centered, and high-quality. It presents an opportunity to redesign and enhance curricula. Higher education institutions are adopting a blended approach to complement traditional courses and enrich student learning experiences. However, research…

Many education tests and psychological surveys elicit respondent views of similar constructs across scenarios (e.g., story followed by multiple choice questions) by repeating common statements across scales (one-statement-multiple-scale, OSMS). However, a respondent's earlier responses to the common statement can affect later responses to it…

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…