Hybrid learning implementation is closely related with technology. In designing hybrid lessons, lecturers need to have both the pedagogical and content-related skills that make the best use of technology so that it also improves the students' skills, including their computational thinking skills. The purpose of this research is to examine whether…

Purpose: Dyslexia is characterized by its diverse causes and heterogeneous manifestations. Chinese children with dyslexia exhibit orthographic, phonological, and semantic deficits across character and radical levels when writing. However, whether character dictation can be used to distinguish children with dyslexia from their typically developing…

Most mathematicians state mathematics is a field of beauty, creativity, and innovation, yet what is echoed by students is not how mathematics allows students to explore, but rather the ways in which it constrains and does not necessitate creativity. In comparison, many students associate coding with freedom, and the ability to create and express…

The Federal STEM Education Strategic plan recognizes the importance of building computational literacy today. This document is aligned to the Computational Literacy Interagency Working Group (IWGCL) objectives to: (1) develop a common operational definition; (2) identify existing research on computational literacy; and (3) identify existing…

Computational thinking (CT) is a fundamental ability for learners in today's society. Although CT assessments and interventions have been studied widely, little is known about CT predictions. This study predicted students' CT achievement in the ICILS 2018 using five machine learning models. These models were trained on the data from five European…

In this article, we propose a variational Bayes (VB) inference method for the deterministic input noisy AND gate model of cognitive diagnostic assessment. The proposed method, which applies the iterative algorithm for optimization, is derived based on the optimal variational posteriors of the model parameters. The proposed VB inference enables…

Learning curves are an important tool in cognitive diagnostics modeling to help assess how well students acquire new skills, and to refine and improve knowledge component models. Learning curves are typically obtained from a model estimated on real data obtained from a finite, and usually limited, sample of students. As a consequence, there is…

Background: This study posits that scaffolded team-based computational modeling and simulation projects can support model-based learning that can result in evidence of representational competence and regulatory skills. The study involved 116 students from a second-year thermodynamics undergraduate course organized into 24 teams, who worked on…

Computational thinking (CT) is a set of cognitive skills that every child should acquire. K-12 classrooms are expected to provide students opportunities (tasks) to think computationally. We introduce a CT competency assessment for middle school students. The assessment design process started by establishing a cognitive model of CT domain mastery,…

This article reports on a study investigating how computational essays can be used to help students in higher education STEM take up disciplinary epistemic agency--cognitive control and responsibility over one's own learning within the scientific disciplines. Computational essays are a genre of scientific writing that combine live, executable…

This review describes a computational approach for modeling the development of speech motor control in infants. We address the development of two levels of control: articulation of individual speech sounds (defined here as phonemes, syllables, or words for which there is an optimized motor program) and production of sound sequences such as phrases…

Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model--a situation in which…

Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model--a situation in which…

Psychology research often focuses on interactions, and this has deep implications for inference from non-representative samples. For the goal of estimating average treatment effects, we propose to fit a model allowing treatment to interact with background variables and then average over the distribution of these variables in the population. This…

Response time data from educational and psychological assessments have become more widely available in recent years. Although much research has been done on response time models, there is large variability between assessments and the factors that may affect response times. On the person's side, familiarity with online environments may largely…