Computing education

Computing education research focuses on the study and development of effective teaching and learning strategies in computer science and related fields. This discipline explores how computing education programs, majors, and courses can be designed to enhance students’ knowledge and skills, addressing questions like ‘Is computing education the same as computer science education?’ and ‘Is computing a hard degree?’ Situated within human-centred computing, this research area highlights the intersection of technology, pedagogy, and learner experience. JoVE Visualize enriches this knowledge by pairing PubMed research articles with JoVE’s experiment videos, offering a comprehensive view of research methodologies and findings for researchers and students.

Key Methods & Emerging Trends

Established Methods in Computing Education Research

Traditional approaches in computing education research often involve quantitative and qualitative techniques such as controlled classroom experiments, surveys of student learning outcomes, and curriculum assessments. Studies may employ Computer Science Education PDFs and statistical analyses to evaluate the effectiveness of computing education programs and courses. Longitudinal studies tracking major retention rates and pedagogical interventions across diverse student populations also form a core part of this research. These methods help educators and researchers understand how best to teach computing concepts, including initiatives from organizations like the National Centre for Computing Education and Barefoot Computing.

Emerging and Innovative Methods

Recent trends in computing education research include the integration of technology-enhanced learning tools such as Raspberry Pi-based projects promoted by the National Centre for Computing Education Raspberry Pi initiative. Gamification, adaptive learning platforms, and AI-driven analytics are gaining momentum to personalize teaching and assess student engagement. Mixed-methods research combining ethnographic studies with learning data analytics offers deeper insight into how students experience computing education courses. These innovative approaches support ongoing efforts to improve teaching practices and address challenging questions faced by those who teach computing and assess curriculum effectiveness.