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Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Chiao Ling Huang; Lianzi Fu; Shih-Chieh Hung; Shu Ching Yang – Journal of Computer Assisted Learning, 2025
Background: Many studies have highlighted the positive effects of visual programming instruction (VPI) on students' learning experiences, programming self-efficacy and flow experience. However, there is a notable gap in the research on how these factors specifically impact programming achievement and learning intentions. Our study addresses this…
Descriptors: Attention, Self Efficacy, Visual Aids, Instructional Effectiveness
Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
Araos, Andrés; Damsa, Crina; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives: This study explores computer and software engineering students' learning…
Descriptors: Computer Science Education, Computer Software, Learning Activities, Undergraduate Students
Esmaeil Jafari – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence (AI) has created new opportunities, challenges, and potentials in teaching; however, issues related to the philosophy of using AI technology in learners' learning have not been addressed and have caused some issues and concerns. This issue is due to the research gap in addressing issues related to ethical and…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, College Faculty
Merve Aydin; Ünal Çakiroglu – Journal of Computer Assisted Learning, 2025
Background: Students experience higher-order thinking skills by finding ways to solve the problem, debugging errors while applying the solution, and testing the solution in programming. However, the inability to create schemas that will characterise programming structures is one of the difficulties during this process. Objectives: This study aimed…
Descriptors: Programming, Computer Science Education, Thinking Skills, Problem Solving
Amy Hutchison; Qi Si; Jamie Colwell; Erdogan Kaya; Eileen Jakeway; Brittany Miller; Kristie Gutierrez; Kelly Regan; Anna Evmenova – Journal of Computer Assisted Learning, 2025
Background: In recent years, computer science education has emerged as a necessary part of school curricula for students of all ages. With such momentum in this direction, it is essential that program designers, educators, and researchers ensure that computer science education is designed to be inclusive, effective, and engaging for all students.…
Descriptors: Coding, Instruction, Scaffolding (Teaching Technique), Literacy