Background: Based on the embodied cognition perspective, interdisciplinary hands-on learning combines several disciplines, such as science, technology, engineering and mathematics (STEM), to improve students' capacity to solve real-world problems. Despite the popularity of interdisciplinary hands-on learning, particularly the six-phase 6E model,…

Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…

Background: ChatGPT, an AI-based chatbot, supports learning by accurately interpreting and responding to user inputs. Despite its potential, few empirical studies have examined its influence on college students' mathematical problem-solving processes. Objectives: This study aimed to introduce a ChatGPT-facilitated scaffolding to investigate its…

Background: Computational thinking (CT) is a fundamental ability required of individuals in the 21st-century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think…

Background: Numerous higher education institutions worldwide have adopted English-language-medium computer science courses and integrated online problem-solving competitions to bridge gaps in theory and practice (Alhamami "Education and Information Technologies," 2021; 26: 6549-6562). Objectives: This study aimed to investigate the…

Background: Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking. Objectives: This study introduces PA-GPT,…

Background: Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology-enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory-driven measurements that are usually carried out…

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…

Motivation: This research investigates the transformative impact of integrating AI into mathematics education, aiming to enhance students' conceptual understanding and self-efficacy. It addresses the crucial need for innovative teaching methods in response to contemporary challenges in education and aims to fill gaps in understanding the potential…

Background: Group size is one of the important factors that affect collaborative learning, however, there is no consensus in the literature on how many students should the groups be composed of during the problem-solving process. Objectives: This study investigated the effect of group size in a K-12 introductory Artificial Intelligence course by…