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,…

The strategy choice model (SCM) is a highly influential theory of human problem-solving. One strength of this theory is the allowance for both item and person variance to contribute to problem-solving outcomes, but this central tenet of the model has not been empirically tested. Explanatory item response theory (EIRT) provides an ideal approach to…

For meta-analysis of studies that report outcomes as binomial proportions, the most popular measure of effect is the odds ratio (OR), usually analyzed as log(OR). Many meta-analyses use the risk ratio (RR) and its logarithm because of its simpler interpretation. Although log(OR) and log(RR) are both unbounded, use of log(RR) must ensure that…

Purpose: The purpose of this paper is the presentation of a learning model for a manager and employee working collaboratively to make advances in knowledge, skills, work performance and in the quality of their relationship. The model is called reciprocal action learning. Design/methodology/approach: The approach was to examine concepts and…

Use of modeling as a learning strategy in introductory science courses could serve to support the persistence of all students, including those who identify with a traditionally underrepresented ethnic minority (URM). If students find inherent value in working on modeling-type problems then this authentic practice would aid in transforming personal…

Drawing on various disciplinary and scholarly approaches to the multiple roles of higher education in society, this paper offers a new conceptualisation of the non-economic contributions of higher education. The conceptual model identifies two basic dimensions in higher education's contributions to society. The first, axiological dimension…

Traditionally, students' various educational characteristics are evaluated according to the grades they get or the results of their answers to the scales. There are some limitations in making an evaluation based on the results. The fuzzy logic approach, which tries to eliminate these limitations, has recently been used in the field of education.…

A neurological disorder, along with several behavioral issues, may be to blame for a child's subpar performance in the academic journey (such as anxiety, depression, learning disorders, and irritability). These symptoms can be used to diagnose children with ASD, and supervised machine learning models can help differentiate between ASD traits and…

The results of online learning were not optimal, as evidenced by the unsatisfactory learning outcomes. These issues influenced students who had a poor understanding of concepts and those who were quick to learn. It was the reason for the study that aims to analyze the effectiveness of study, explore, implement, evaluate (SEIE) model e-learning…

On the one hand, mathematical software is ubiquitous in mathematics education. On the other hand, word problems are an important part of the curriculum, and they often require modelling skills. This is especially true with optimisation and extrema problems proposed to high school and undergraduate students. We propose two activities around extrema…

Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…

Holistic and ecological approaches to mental health support have been identified by many as best-practice approaches for creating and sustaining well-being. Those who experience mental health challenges including, for example, Borderline Personality Disorder (BPD), often struggle to find adequate, sustainable and ongoing care from clinical…

In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

This study delves into the integration of Project-Based Learning (PBL) and Computational Thinking (CT) to enhance 21st century learning. Through a Narrative Literature Review (NLR), pivotal strategies for effective implementation are identified. These include fostering collaborative pedagogy, employing visualization tools, embracing diverse…

Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…