Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…

Programming education often imposes a high cognitive burden on novice programmers, requiring them to master syntax, logic, and problem-solving while simultaneously managing debugging tasks. Prior knowledge is a critical factor influencing programming learning performance. A lack of foundational knowledge limits students' self-regulated learning…

Background: As one of the mainstream forms of programming education, educational robotics (ER) have been a crucial way to develop K-12 students' programming ability. Objectives: The purpose of this study is to clarify the content of programming ability, to verify the effectiveness of ER as a teaching method to improve students' programming…

The aim of this study is to investigate the effects of the integration of goal-based scenario (GBS) approach into a block-based coding instruction. Scratch platform was used to find out the effects of GBSs on programming skills of students, who did not have any programming experience. GBSs were used during practice and the development in students'…

The COVID-19 pandemic has forced a significant increase in the utilization of video-based e-learning platforms for programming education. These platforms never considered the essential attributes of student characteristics and learning preferences while designing such a problematic subject having high dropout and failure rates. The traditional…

Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…

Background: In the digital age, fostering young children's computational thinking (CT) and executive functions (EFs) through programming has emerged as a significant research issue. While unplugged programming activities are commonly adopted in preschools, robot programming activities have recently gained attention for the potential to enhance…

In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…

Although programming is often learned through formal instruction or self-paced tutorials, informal learning, for example, through publicly available online documentation, is also a significant resource for skill development among novices. However, many novices struggle to extract useful information from documentation. This work aims to answer two…

Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…

Generalist primary school computer science (CS) teachers are often reluctant to introduce CS activities that go beyond CS unplugged tasks. To address this challenge, we drew from constructive alignment principles to implement a new programming modality for primary school: the handwriting programming language (HPL). HPL brings programming…

During a relatively short period of time, programming has been implemented in the national curriculum of the compulsory school in Sweden. Since 2018, programming is a new content in the technology subject and the research field has discussed some of the challenges teachers and students, who generally have little experiences of programming, face…

Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their…

Background: Artificial intelligence-generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC…

Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…