Investigating Freshmen Students’ Coding Standards Challenges Using NLP Techniques

This study investigates the potential use of Natural Language Processing (NLP) techniques to analyze coding standards violations within the context of an introductory programming course. In particular, the study evaluates the effectiveness of various advanced text embedding techniques, including Bag of Words (BOW), Doc2Vec, and BERT, in clustering coding standards violations. This study aims to determine which text embedding techniques contribute to the most accurate clustering of errors. Our findings highlight the superiority of Doc2Vec embeddings in effectively clustering related errors compared to the alternative techniques.