What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education

By Ahmed Tlili, Boulus Shehata, Michael Agyemang Adarkwah, Aras Bozkurt, Daniel Thomas Hickey, Ronghuai Huang, Brighter Agyemang. Smart Learning Environments, 2023

1,551 citations recorded by the source corpus.

Artificial Intelligence (AI) technologies have been progressing constantly and being more visible in different aspects of our lives. One recent phenomenon is ChatGPT, a chatbot with a conversational artificial intelligence interface that was developed by OpenAI. As one of the most advanced artificial intelligence applications, ChatGPT has drawn much public attention across the globe. In this regard, this study examines ChatGPT in education, among early adopters, through a qualitative instrumental case study. Conducted in three stages, the first stage of the study reveals that the public discourse in social media is generally positive and there is enthusiasm regarding its use in educational settings. However, there are also voices who are approaching cautiously using ChatGPT in educational settings. The second stage of the study examines the case of ChatGPT through lenses of educational transformation, response quality, usefulness, personality and emotion, and ethics. In the third and final stage of the study, the investigation of user experiences through ten educational scenarios revealed various issues, including cheating, honesty and truthfulness of ChatGPT, privacy misleading, and manipulation. The findings of this study provide several research directions that should be considered to ensure a safe and responsible adoption of chatbots, specifically ChatGPT, in education.

Subfields: Artificial Intelligence, Health Informatics, Safety Research

View Paper: https://www.semanticscholar.org/paper/f6681d526def3a7a5cd7b960d3e60ac69a10dbd7

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Citations in the corpus

Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots (2023, background): “Increasing students' knowledge of academic honesty guidelines and their comprehension of the penalties for misconduct in academia are also significant [24].”
Exploring students’ perspectives on Generative AI-assisted academic writing (2024, neutral): “Despite its many benefits, there are still challenges and concerns associated with using GenAI for academic writing tasks, including data privacy, intellectual property, students’ over-reliance on automated tools, and plagiarism (Lund & Wang, 2023; Ray, 2023; Tlili et al., 2023).”
Generative artificial intelligence: a systematic review and applications (2024, positive): “For instance, in a recent article [130] highlights the need for a new and creative way of teaching that effectively incorporates the progress brought by AI.”
Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions (2023, background): “Specifically, a study demonstrated that adding 1 word (“amazing”) to an AI-generated text reduced the fake level (ie, generated by AI) detected by a tool from 99% to 24% [48].”
ChatGPT and Open-AI Models: A Preliminary Review (2023, background): “Education/Chatbots ChatGPT is extremely important and valuable for transforming education [48].”
Promises and challenges of generative artificial intelligence for human learning (2024, positive): “Such attacks could facilitate cheating, promote biased views or expose students to offen sive language 92 .”
The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney (2023, positive): “Students should be able to learn how to evaluate the information given by ChatGPT in a critical manner and begin to curate the information (Tlili et al., 2023).”
The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions (2023, neutral): “73 However, generative AI enhances these capabilities by transcending mere pattern recognition to synthesize new data.”
A Documentary Evaluation of Offline AI Integration in Teacher-in-a-Box OER Programmes for Low-Connectivity Schools (2026, unknown): “Recent advances in generative AI suggest a potential contribution to this design space: local-first language models that can operate offline after initial setup (for example, GPT4All class of tools) and can be paired with retrieval methods that ground outputs in a locally stored corpus [24]-[27].”