While increasing emphasis has been placed on computer science (CS) and computational thinking (CT) little is known about these topics in elementary classrooms. Significant equity gaps exist within CS/CT at the elementary level, with a major contributor being the lack of highly qualified CS/CT elementary teachers. Professional development (PD) for…

Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…

The College Cost Reduction Act would overhaul the Higher Education Act, making changes to student borrowing and repayment, borrower protections, college oversight, postsecondary data, and more. The bill includes a new proposed risk-sharing model that would require colleges to repay the federal government for a calculated proportion of their…

Previous research has not adequately explored students' behavioral processes when addressing computational thinking (CT) problems of varying difficulty, limiting insights into students' detailed CT development characteristics. This study seeks to fill this gap by employing gamified CT items across multiple difficulty levels to calculate…

Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…

Fostering young learners' computational thinking in AI-based robots is a crucial issue in educational settings. However, there was the complexity of technology in supporting learning activities and the gender gap issue, so an appropriate strategy is needed to guide students to achieve the learning goals. In this study, an AI (Artificial…

Children with mathematical difficulties need to spend more time than typically achieving children on solving even simple equations. Since these tasks already require a larger share of their cognitive resources, additional demands imposed by the need to switch between tasks may lead to a greater decline of performance in children with mathematical…

The ability of TPE participants in arranging lesson plans is essential to be mastered as an indicator of pedagogical competence which should be possessed before conducting a teaching process in the class. This research aimed to analyze the estimation of TPE participants' ability in composing a lesson plan which uses the assessment with partial…

This paper addresses a common challenge with computational cognitive models: identifying parameter values that are both theoretically plausible and generate predictions that match well with empirical data. While computational models can offer deep explanations of cognition, they are computationally complex and often out of reach of traditional…

Research Findings: In this research, 487 Chinese children age 3 to 5 years took part in a number line estimation task. This task was used to assess children's estimation accuracy and their estimation patterns along a number line in two different estimation circumstances. Situation A had the same line lengths for different numeric ranges, whereas…

The need to integrate computation into the physics curriculum has long been established: using simulations and computational modeling can enhance students' conceptual understanding, and the computational skills students acquire are both useful and necessary in their careers. However, making changes to an established physics course is a challenge…

As the use of diagnostic assessment systems transitions from research applications to large-scale assessments for accountability purposes, reliability methods that provide evidence at each level of reporting are needed. The purpose of this paper is to summarize one simulation-based method for estimating and reporting reliability for an…

Recent years have seen increasing interest in incorporating resampling methods into introductory statistics courses and the high school mathematics curriculum. While the use of permutation tests for data from experiments is a step forward, the use of simple bootstrap methods for sampling situations is more problematical. This article demonstrates…

A maximum marginal likelihood estimation with an expectation-maximization algorithm has been developed for estimating multigroup or mixture multidimensional item response theory models using the generalized partial credit function, graded response function, and 3-parameter logistic function. The procedure includes the estimation of item…

Exploratory cognitive diagnosis models (CDMs) estimate the Q matrix, which is a binary matrix that indicates the attributes needed for affirmative responses to each item. Estimation of Q is an important next step for improving classifications and broadening application of CDMs. Prior research primarily focused on an exploratory version of the…