Key research themes
1. How do different teaching and assessment methods influence the acquisition and evaluation of coding skills in K-12 and early childhood education?
This theme investigates effective pedagogical approaches for teaching coding to children and adolescents, emphasizing the design of assessments that capture multiple dimensions of coding competence beyond mere syntax, including problem-solving, algorithmic thinking, and creativity. It addresses challenges faced by educators in formative and summative evaluations, learners’ developmental readiness, and the integration of computational thinking into curricula.
2. What competencies and social dynamics affect developer performance and learning in coding tasks, including code review and pair programming?
This theme explores individual and interpersonal factors shaping coding proficiency and collaboration, focusing on how specific competencies and group compatibility influence coding performance, learning efficacy, and social engagement in pair programming and code review contexts. It examines both technical and socio-emotional competencies required for high-quality code review, as well as the impacts of personality traits, prior knowledge, and friendship relations on flow states and productivity in paired coding.
3. How do emerging technologies like AI-driven code generation tools and debugging environments influence coding education, problem-solving, and error correction?
This theme addresses the opportunities and challenges posed by AI-based coding assistants and interactive debugging tools for novices and educators. It investigates AI’s capacity to solve coding exercises such as Parsons problems, the differential impact of execution environments on correcting tracing errors, and the implications of these tools on students’ conceptual understanding, creativity, and independent problem-solving.






