Text Analysis of Chatgpt as a Tool for Academic Progress or Exploitation

Bukar, Umar Ali; Sayeed, Shohel; Razak, Siti Fatimah Abdul; Yogarayan, Sumendra; Amodu, Oluwatosin Ahmed

doi:10.2139/ssrn.4381394

Cited by 6 publications

(5 citation statements)

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“…Secondly, several studies have called for more research on AI ethics and encouraged the development of policies to shape the development and utilization of AI tools in various sectors ( Dwivedi et al, 2023 ; Mhlanga, 2023 ; Gunawan, 2023 ; Carvalho & Ivanov, 2023 ; Halaweh, 2023 ; Bukar et al, 2023 ; Tlili et al, 2023 ). In response to this demand, this study makes diverse and multidisciplinary contributions and holds implications and significance that are tailored to various audiences.…”

Section: Discussionmentioning

confidence: 99%

An integrative decision-making framework to guide policies on regulating ChatGPT usage

Bukar,

Sayeed,

Abdul Razak

et al. 2024

PeerJ Computer Science

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Generative artificial intelligence has created a moment in history where human beings have begin to closely interact with artificial intelligence (AI) tools, putting policymakers in a position to restrict or legislate such tools. One particular example of such a tool is ChatGPT which is the first and world's most popular multipurpose generative AI tool. This study aims to put forward a policy-making framework of generative artificial intelligence based on the risk, reward, and resilience framework. A systematic search was conducted, by using carefully chosen keywords, excluding non-English content, conference articles, book chapters, and editorials. Published research were filtered based on their relevance to ChatGPT ethics, yielding a total of 41 articles. Key elements surrounding ChatGPT concerns and motivations were systematically deduced and classified under the risk, reward, and resilience categories to serve as ingredients for the proposed decision-making framework. The decision-making process and rules were developed as a primer to help policymakers navigate decision-making conundrums. Then, the framework was practically tailored towards some of the concerns surrounding ChatGPT in the context of higher education. In the case of the interconnection between risk and reward, the findings show that providing students with access to ChatGPT presents an opportunity for increased efficiency in tasks such as text summarization and workload reduction. However, this exposes them to risks such as plagiarism and cheating. Similarly, pursuing certain opportunities such as accessing vast amounts of information, can lead to rewards, but it also introduces risks like misinformation and copyright issues. Likewise, focusing on specific capabilities of ChatGPT, such as developing tools to detect plagiarism and misinformation, may enhance resilience in some areas (e.g., academic integrity). However, it may also create vulnerabilities in other domains, such as the digital divide, educational equity, and job losses. Furthermore, the finding indicates second-order effects of legislation regarding ChatGPT which have implications both positively and negatively. One potential effect is a decrease in rewards due to the limitations imposed by the legislation, which may hinder individuals from fully capitalizing on the opportunities provided by ChatGPT. Hence, the risk, reward, and resilience framework provides a comprehensive and flexible decision-making model that allows policymakers and in this use case, higher education institutions to navigate the complexities and trade-offs associated with ChatGPT, which have theoretical and practical implications for the future.

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Section: Discussionmentioning

confidence: 99%

An integrative decision-making framework to guide policies on regulating ChatGPT usage

Bukar,

Sayeed,

Abdul Razak

et al. 2024

PeerJ Computer Science

Self Cite

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“…By utilizing VOSviewer, one can gain a deeper understanding of the prevailing trends, major contributions, and emerging areas within the realm of ChatGPT's application in education. This analytical approach not only reveals the current landscape of research but also guides future studies by highlighting potential areas of exploration and collaboration [4].…”

Section: Methodsmentioning

confidence: 99%

“…Overlay visualization in VOSviewer is a powerful technique for bibliometric analysis that provides insights into various aspects of a dataset, typically comprising scientific publications [4]. Overlay visualizations often display the age of items (like publications or keywords) in a dataset.…”

Section: Fig 2 Overlay Visualization Of Scopus-based Articles On Chat...mentioning

confidence: 99%

“…Density visualization in VOSviewer is a method used to graphically represent the concentration of data points (such as keywords, authors, or publications) within a bibliometric network [4].…”

Section: Fig 3 Density Visualization Of Scopus-based Articles Of Chat...mentioning

confidence: 99%

“…Furthermore, empirical studies have been conducted to explore the impact of AI chatbots, like ChatGPT, on students' learning outcomes. These studies indicate that AI chatbots, when integrated into educational environments, can significantly affect students' learning, especially in higher education settings [3], [4].…”

Section: Introductionmentioning

confidence: 99%

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ChatGPT and Education: A Scopus Bibliometric Analysis

Riyadi,

Syaripudin,

Kurniasih

et al. 2024

Proceedings of the International Conference on Teaching, Learning and Technology (ICTLT 2023)

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The birth of ChatGPT has caused controversy, especially in the world of education. Various studies have been conducted looking at the positive and negative impacts. This research is a Scopus-based bibliometric analysis to examine trends in the relationship between ChatGPT and education. The articles analysed were sourced from the Scopus database totalling 403 from the end of 2023 to the beginning of 2024. After managing the database from Scopus, this study classified and visualized it using VOSviewer software. The research results are classified based on VOSviewer output starting from the network, overlay, density visualization, and specific topics such as "education", and "higher education". The research results describe 54 keyword items in 11 clusters. The most popular keywords include "academic integrity", "machine learning", "plagiarism", and "ethics". The most popular keywords include "academic integrity", "machine learning", "plagiarism", "justice", and "ethics". This review provides an appropriate reference point for further research on "ChatGPT and Education".

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