Background and Context: Professional development (PD) programs for K-12 computer science teachers use surveys to measure teachers' knowledge and attitudes while recognizing daily sentiment and emotion changes can be crucial for providing timely teacher support. Objective: We investigate approaches to compute sentiment and emotion scores…

In the wake of the present inclusion of programming in mathematics education, which is a feature of curricular revisions in many countries, we have analysed newly inserted programming activities in mathematics textbooks. The aim was to investigate how such activities relate to and potentially affect students' opportunities to learn mathematics.…

Background: Robot programming can simultaneously cultivate learners' computational thinking (CT) and spatial thinking (ST). However, there is a noticeable gap in research focusing on the micro-level development patterns of learners' CT and ST and their interconnections. Objectives: This study aims to uncover the intricate development patterns and…

This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to…

Most existing autograders used for grading programming assignments are based on unit testing, which is tedious to implement for programs with graphical output and does not allow testing for other code aspects, such as programming style or structure. We present a novel autograding approach based on machine learning that can successfully check the…

The paper discusses an alternative method of assessing the difficulty of pupils' programming tasks to determine their age appropriateness. Building a program takes the form of its successive iterations. Thus, it is possible to monitor the number of times such a program was built by the solver. The variance of the number of program builds can be…

As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…

Collaborative programming can develop computational thinking and knowledge of computational programming. However, the researchers pointed out that because students often fail to mobilize metacognition to regulate and control their cognitive activities in a cooperation, this results in poor learning effects. Especially low-achieving students need…

In a previous publication we examined the connections between high-school computer science (CS) and computing higher education. The results were promising -- students who were exposed to computing in high school were more likely to take one of the computing disciplines. However, these correlations were not necessarily causal. Possibly those…

Computational thinking (CT) has attracted global research attention. However, the relationship between CT education and later aspirations in computing careers was less explored, and less attention was paid to understanding the intermediary role of computational identity. Based on social cognitive career theory, this study examined the…

Improving computer science (CS) education in PK-12 continues to be a priority for educators, researchers, and policymakers worldwide. One of the leading problems and mitigating factors of student CS success, however, is the lack of teachers prepared and qualified to teach computer science. Efforts have been made to address this issue through…

Virtual reality (VR) technology is playing a crucial role in the changing paradigm of education. In many cases, however, VR technology is not being taught because of the lack of relevant educational content at middle and high school levels. This study investigates the effect of design education using VR-based coding on students' competence and…

The purpose of this study was to explore the teaching-learning process of informatics education in South Korea, where an informatics education initiative was recently announced for K-12 education. Based on this initiative, this study aimed to investigate the effect of academic self-efficacy, teacher support, and a deep approach to learning…

This study provides the first causal analysis of the impact of expanding Computer Science (CS) education in U.S. K-12 schools on students' choice of college major and early career outcomes. Utilizing rich longitudinal data from Maryland, we exploit variation from the staggered rollout of CS course offerings across high schools. Our findings…

The study's goal was to examine the correlation between the computer programming self-efficacy and computational thinking skills of gifted and talented students. The capacity of the computer programming self-efficacy of gifted and talented students to predict their computational thinking skills were also examined. The relational screening model…