Python’s Contribution to Artificial Intelligence in Education: A state-of-the-art review
DOI:
https://doi.org/10.62411/faith.3048-3719-267Keywords:
Adaptive Learning, Artificial Intelligence, Education, Educational Data Mining, Learning Analytics, Artificial Intelligence Python Libraries Education AI Applications, Python, Teaching and Learning ApplicationsAbstract
This paper examines current trends in Artificial Intelligence (AI), with a particular emphasis on the application of the Python programming language in educational settings. The existing literature reveals a gap in reviews regarding Python's role in AI applications within the education sector. This paper highlights and describes the most effective and popular Python libraries, particularly those relevant to AI in educational settings, that have emerged in recent years. Additionally, it presents basic and widely used AI applications in education that utilize Python. The research method employed is a state-of-the-art review, which involves searching the literature using specific keywords and applying inclusion and exclusion criteria for quality and reliability. In the findings, synthesis, and discussion section, results are presented in tables to facilitate use by researchers and practitioners, allowing for easier application. The tables include information on the most well-known and frequently used Python libraries and AI applications, the grouping categories of Python libraries, their tasks and functions, as well as how Python libraries can be applied in education. Moreover, the paper explores AI methods that enhance teaching and learning using Python tools and connects learning theories with these AI methods. During the discussion, the paper provides an analysis to assist new researchers and practitioners, especially those working with AI in education, on how to effectively leverage AI through Python. It also emphasizes the overall benefits that Python brings to the field of AI in education. The paper also offers various suggestions for addressing gaps in the existing literature.
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