Trends and Issues in STEM plus C Research: A Bibliometric Perspective

The integration of computing education or computational thinking with STEM majors has gained substantial research interests. A number of research papers of the topic were published. This work is to provide a comprehensive overview of literature in the STEM + C field through both bibliometric and content analysis. We conducted a systematic search to identify articles and utilized machine-learning-based techniques to analyze these articles. Common bibliometric indicators were used for bibliometric analysis. Machinelearning-based text mining techniques such as LDA topic modelling and flow analysis were used for content analysis. Our analysis spotted STEM + C publication trends, popular topics and their dynamics over time. This work also pinpointed commonly used methodologies for integration study for both PK, K-12 and higher education. Meanwhile, several future research directions were identified. This work contributes to the literature by systematically examining the existing literature and bringing machine-learning-based data mining techniques to the analysis.