A Literature Analysis of Programming Education in Information Education Using Text Mining

Objectives This study aims to analyze the previous research on programming education from the perspective of computer education and information education in depth by using text mining techniques on all the texts in the literature, and to derive the main keywords and research trends of research related to programming education in Korea and implications for future research. Methods We systematically collected and preprocessed research results from 2015 to March 2024 to extract a large amount of text, and based on this, we used TF-IDF to derive keywords and analyze research trends. We also visualized Word2Vec results by focusing on the keywords of block, text, and physical computing along with programming education to draw implications. Results The TF-IDF analysis confirmed that programming education from the perspective of promoting computational thinking is emphasized in information education and artificial intelligence education, and the main research targets of ‘toddlers’, ‘students’, and ‘pre-service teachers’ were identified along with keywords such as ‘programming’, ‘blocks’, and ‘physical computing’. In addition, the Word2Vec analysis centered on the main keywords related to programming education revealed the research perspectives of each teaching method. Conclusions This study has academic significance in that it suggests research directions such as diversification of research in terms of teaching and learning methods, the need for research on learning problems, and the need for in-depth educational research centered on the specificity of AI education through text mining to analyze a large amount of text containing the overall context of previous research.