Bibliographic Details
| Title: |
CoRemix: Supporting Online Learning in Scratch Community with Visual Flowchart and Generative AI. |
| Authors: |
Chen, Yunnong (AUTHOR), Yu, Xinyu (AUTHOR), Shen, Yishu (AUTHOR), Liu, Ruiyi (AUTHOR), Sun, Lingyun (AUTHOR), Chen, Liuqing (AUTHOR) |
| Source: |
International Journal of Human-Computer Interaction. May2026, Vol. 42 Issue 10, p7475-7500. 26p. |
| Subjects: |
Flow charts, Generative artificial intelligence, Student projects, Online education, Computer programming education, Computer software development, Visual programming languages (Computer science) |
| Abstract: |
Online programming communities give novices places to explore computing through user-generated projects, but limited structure can hinder a steadily challenging learning path. Beginners often struggle to interpret key events and relationships in projects, connect them to core concepts, and remix practices. We present CoRemix, a generative-AI community support system that uses visual flowcharts to clarify project logic. CoRemix introduces a prompting pipeline paired with a visual-textual scaffold that guides learners in constructing flowcharts. We further incorporate static project analysis and retrieval-augmented generation (RAG) to raise the precision of large-language-model outputs. In technical evaluations, static analysis and RAG improved response quality. In a user study, CoRemix outperformed a baseline in helping learners understand complex projects, strengthen computing-concept skills, and report better learning experiences within online communities. These gains include clearer event sequencing, improved identification of relationships across sprites and scripts, stronger remix strategies, and higher perceived scaffolding for progressive challenge. [ABSTRACT FROM AUTHOR] |
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| Database: |
Psychology and Behavioral Sciences Collection |
