Python Script for SDG Classification and Curriculum Analysis

SUPPLEMENTARY MATERIAL Supplementary Material Python Script for SDG Classification and Curriculum Analysis S1. Overview This supplementary material provides the Python script developed to classify course syllabi according to their alignment with the Sustainable Development Goals (SDGs). The script performs automated keyword-based text analysis using a structured dictionary, enabling scalable, transparent, and replicable identification of SDG-related content. The procedure supports the methodological approach described in the main manuscript and allows application across different institutional and disciplinary contexts. S2. Data Requirements The script requires two input files: Keyword dictionary file (Excel format) Each column represents one SDG Each column contains associated keywords Syllabus dataset (Excel format)Must include at least: EMENTA (syllabus text) S3. Processing Logic The script performs the following steps: Loads the SDG keyword dictionary Preprocesses syllabus text (lowercase normalization) Scans each syllabus for keyword occurrences Assigns SDGs based on keyword matching Outputs a dataset with SDG classification results S4. Output The script generates a dataset including a variable (SDG_related) indicating the SDGs identified in each syllabus. This output supports: SDG frequency analysis Curriculum positioning analysis Institutional comparisons S5. Reproducibility Note The script is adaptable to other contexts by modifying the keyword dictionary. Researchers are encouraged to refine keyword lists according to disciplinary and linguistic specificities to improve classification accuracy.