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

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...

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Main Author: Niklas Humble
Format: Article
Language:English
Published: SpringerOpen 2024-12-01
Series:International Journal of Educational Technology in Higher Education
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Online Access:https://doi.org/10.1186/s41239-024-00494-x
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author Niklas Humble
author_facet Niklas Humble
author_sort Niklas Humble
collection DOAJ
description 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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spelling doaj-art-2c34196acae849f4bc6de2de9deb655c2024-12-15T12:11:30ZengSpringerOpenInternational Journal of Educational Technology in Higher Education2365-94402024-12-0121113510.1186/s41239-024-00494-xRisk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?Niklas Humble0Department of Information Technology, Uppsala UniversityAbstract 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.https://doi.org/10.1186/s41239-024-00494-xGenerative AIComputing educationRisk management strategyLiterature reviewSWOT analysis
spellingShingle Niklas Humble
Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
International Journal of Educational Technology in Higher Education
Generative AI
Computing education
Risk management strategy
Literature review
SWOT analysis
title Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
title_full Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
title_fullStr Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
title_full_unstemmed Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
title_short Risk management strategy for generative AI in computing education: how to handle the strengths, weaknesses, opportunities, and threats?
title_sort risk management strategy for generative ai in computing education how to handle the strengths weaknesses opportunities and threats
topic Generative AI
Computing education
Risk management strategy
Literature review
SWOT analysis
url https://doi.org/10.1186/s41239-024-00494-x
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