Teaching computer programming language remotely presents particular difficulties due to its requirement for abstract and logical thinking. There is a dearth of research specifically examining the potential factors that determine student performance when distance self-learning is conducted for programming language education. This study aims to…

The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…

Computational thinking (CT) competency is essential for K-12 students in the digital societies. Understanding the relationship between students' CT and relevant factors contributes to implementing and improving CT education. Most previous studies investigated the effect of demographic or attitudinal factors on CT performance; whereas few research…

Students in technology majors such as Computer Science and Information Technology need to take a series of computer programming courses to graduate. Yet, not all students will persist in taking programming courses as required, and little is known about the factors influencing their enrollment intentions. Research is needed to better understand…

Background: Integrating programming in K-12 curriculum has become a global consensus. Teachers are central figures in programming instruction. But the majority of current research focuses on teachers' external teaching behaviours and less on teachers' attitudes towards programming. Objectives: The purpose of this study is to validate the K-12…

Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant…

In this study, a predictive model is constructed to analyze learners' performance in programming tasks using data of programming behavioral events and behavioral sequences. First, this study identifies behavioral events from log data and applies lag sequence analysis to extract behavioral sequences that reflect learners' programming strategies.…

Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…

While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs…