Shaping Programming and Data Science Education: Insights from GenAI Technical Book Trends

As GenAI technologies, particularly Large Language Models (LLMs), continue to revolutionize programming and data science, it is increasingly vital for educators to adapt computer science curricula. This paper presents a review of recent technical books on AI-Assisted programming and utilizes the fin...

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Bibliographic Details
Main Authors: Bakharia, Aneesha, Abdi, Solmaz
Format: Conference Proceeding
Language:English
Subjects:
AI-assisted programming
Data science
Data science education
Debugging
Education
Encoding
Ethics
Programming curriculum development
Programming education
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Summary:As GenAI technologies, particularly Large Language Models (LLMs), continue to revolutionize programming and data science, it is increasingly vital for educators to adapt computer science curricula. This paper presents a review of recent technical books on AI-Assisted programming and utilizes the findings to guide curriculum changes in higher education. Our analysis underscores the necessity for novel teaching strategies, emphasizing skills like problem decomposition, top-down design, and advanced debugging. Furthermore, it emphasizes the crucial expansion of curricula to encompass courses on developing applications based on LLMs, utilizing libraries such as LangChain and incorporating Retrieval Augmented Generation functionality. Our analysis reveals a significant gap in technical literature regarding the ethical and societal impacts of GenAI, highlighting the urgent need for programming curricula to evolve and equip students with the skills required to ethically develop AI-enhanced software products. This paper advocates for curriculum development that not only aligns with the latest industry trends but also contributes to research on AI-assisted coding and its future impact.
ISSN:2161-377X
DOI:10.1109/ICALT61570.2024.00040