Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?

Abstract

Abstract The idea of Artificial intelligence (AI) has a long history in both research and fiction and has been applied in educational settings since the 1970s. However, the topic of AI underwent a huge increase of interest with the release of ChatGPT in late 2022, and more people were talking about generative AI (GenAI or GAI). According to some estimates, the number of publications on generative AI increased with 2269.49% between 2022 and 2023, and the increase was even higher when related to computing education. The aim of this study is to investigate the potential strengths, weaknesses, opportunities, and threats of generative AI in computing education, as highlighted by research published after the release of ChatGPT. The study applied a scoping literature review approach with a three-step process for identifying and including a total of 129 relevant research papers, published in 2023 and 2024, through the Web of Science and Scopus databases. Included papers were then analyzed with a theoretical thematic analysis, supported by the SWOT analysis framework, to identify themes of strengths, weaknesses, opportunities, and threats with generative AI for computing education. A total of 19 themes were identified through the analysis. Findings of the study have both theoretical and practical implications for computing education specifically, and higher education in general. Findings highlights several challenges posed by generative AI, such as potential biases, overreliance, and loss of skills; but also several possibilities, such as increasing motivation, educational transformation, and supporting teaching and learning. The study expands the traditional SWOT analysis, by providing a risk management strategy for handling the strengths, weaknesses, opportunities, and threats of generative AI.

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