Assessing ChatGPT’s Accuracy and Reliability in Asthma General Knowledge: Implications for Artificial Intelligence Use in Public Health Education DOI
Muhammad Thesa Ghozali

Journal of Asthma, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 9

Published: Jan. 8, 2025

Integrating Artificial Intelligence (AI) into public health education represents a pivotal advancement in medical knowledge dissemination, particularly for chronic diseases such as asthma. This study assesses the accuracy and comprehensiveness of ChatGPT, conversational AI model, providing asthma-related information. Employing rigorous mixed-methods approach, healthcare professionals evaluated ChatGPT's responses to Asthma General Knowledge Questionnaire Adults (AGKQA), standardized instrument covering various topics. Responses were graded completeness analyzed using statistical tests assess reproducibility consistency. ChatGPT showed notable proficiency conveying asthma knowledge, with flawless success etiology pathophysiology categories substantial medication information (70%). However, limitations noted medication-related responses, where mixed (30%) highlights need further refinement capabilities ensure reliability critical areas education. Reproducibility analysis demonstrated consistent 100% rate across all categories, affirming delivering uniform Statistical analyses underscored stability reliability. These findings underscore promise valuable educational tool while emphasizing necessity ongoing improvements address observed limitations, regarding

Language: Английский

Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice DOI Creative Commons
Tom Farrelly,

Nick Baker

Education Sciences, Journal Year: 2023, Volume and Issue: 13(11), P. 1109 - 1109

Published: Nov. 4, 2023

Generative Artificial Intelligence (GAI) has emerged as a transformative force in higher education, offering both challenges and opportunities. This paper explores the multifaceted impact of GAI on academic work, with focus student life and, particular, implications for international students. While GAI, exemplified by models like ChatGPT, potential to revolutionize concerns about integrity have arisen, leading debates use AI detection tools. essay highlights difficulties reliably detecting AI-generated content, raising false accusations against It also discusses biases within models, emphasizing need fairness equity AI-based assessments particular emphasis disproportionate students, who already face discrimination. mitigate some these providing language support accessibility features. Finally, this acknowledges disruptive education calls balanced approach that addresses opportunities it presents importance literacy ethical considerations adopting technologies ensure equitable access positive outcomes all We offer coda Ng et al.’s competency framework, mapped Revised Bloom’s Taxonomy, through lens cultural competence means supporting educators tools equitably their teaching.

Language: Английский

Citations

135

Testing of detection tools for AI-generated text DOI Creative Commons
Debora Weber-Wulff, Alla Anohina-Naumeca, Sonja Bjelobaba

et al.

International Journal for Educational Integrity, Journal Year: 2023, Volume and Issue: 19(1)

Published: Dec. 25, 2023

Abstract Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use artificial intelligence (AI) generated content an academic environment and intensified efforts searching for solutions to detect such content. The paper examines general functionality detection tools AI-generated text evaluates them based on accuracy error type analysis. Specifically, study seeks answer research questions about whether existing can reliably differentiate between human-written ChatGPT-generated text, machine translation obfuscation techniques affect text. covers 12 publicly available two commercial systems (Turnitin PlagiarismCheck) that are widely used setting. researchers conclude neither accurate nor reliable a main bias towards classifying output as rather than detecting Furthermore, significantly worsen performance tools. makes several significant contributions. First, it summarises up-to-date similar scientific non-scientific field. Second, presents result one most comprehensive tests conducted so far, rigorous methodology, original document set, broad coverage Third, discusses implications drawbacks using settings.

Language: Английский

Citations

135

Detection of GPT-4 Generated Text in Higher Education: Combining Academic Judgement and Software to Identify Generative AI Tool Misuse DOI
Mike Perkins, Jasper Roe, Darius Postma

et al.

Journal of Academic Ethics, Journal Year: 2023, Volume and Issue: 22(1), P. 89 - 113

Published: Oct. 31, 2023

Language: Английский

Citations

55

The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment DOI Open Access
Mike Perkins, Leon Furze, Jasper Roe

et al.

Journal of University Teaching and Learning Practice, Journal Year: 2024, Volume and Issue: 21(06)

Published: April 19, 2024

Recent developments in Generative Artificial Intelligence (GenAI) have created a paradigm shift multiple areas of society, and the use these technologies is likely to become defining feature education coming decades. GenAI offers transformative pedagogical opportunities, while simultaneously posing ethical academic challenges. Against this backdrop, we outline practical, simple, sufficiently comprehensive tool allow for integration tools into educational assessment: AI Assessment Scale (AIAS). The AIAS empowers educators select appropriate level usage assessments based on learning outcomes they seek address. greater clarity transparency students educators, provides fair equitable policy institutions work with, nuanced approach which embraces opportunities recognising that there are instances where such may not be pedagogically or necessary. By adopting flexible can implemented quickly, form much-needed starting point address current uncertainty anxiety regarding education. As secondary objective, engage with literature advocate refocused discourse education, one foregrounds how help support enhance teaching learning, contrasts focus as facilitator misconduct.

Language: Английский

Citations

28

Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework DOI Creative Commons
Oluwaseun Kolade, Adebowale Owoseni, Abiodun Egbetokun

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(4), P. e25953 - e25953

Published: Feb. 1, 2024

Language: Английский

Citations

20

Good models borrow, great models steal: intellectual property rights and generative AI DOI Creative Commons
Simon Chesterman

Policy and Society, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 12, 2024

Abstract Two critical policy questions will determine the impact of generative artificial intelligence (AI) on knowledge economy and creative sector. The first concerns how we think about training such models—in particular, whether creators or owners data that are “scraped” (lawfully unlawfully, with without permission) should be compensated for use. second question revolves around ownership output generated by AI, which is continually improving in quality scale. These topics fall realm intellectual property, a legal framework designed to incentivize reward only human creativity innovation. For some years, however, Britain has maintained distinct category “computer-generated” outputs; input issue, EU Singapore have recently introduced exceptions allowing text mining computational analysis existing works. This article explores broader implications these choices, weighing advantages reducing cost content creation value expertise against potential risk various careers sectors economy, might rendered unsustainable. Lessons may found music industry, also went through period unrestrained piracy early digital era, epitomized rise file-sharing service Napster. Similar litigation legislation help navigate present uncertainty, along an emerging market “legitimate” models respect copyright humans clear provenance their own creations.

Language: Английский

Citations

20

Safeguarding Authenticity in Text with BERT-Powered Detection of AI-Generated Content DOI

Utsho Chakraborty,

Jaydeep Gheewala,

Sheshang Degadwala

et al.

2022 International Conference on Inventive Computation Technologies (ICICT), Journal Year: 2024, Volume and Issue: unknown

Published: April 24, 2024

This research study explores the crucial domain of upholding textual authenticity by introducing a comprehensive method for identifying AI-generated content, employing BERT (Bidirectional Encoder Representations from Transformers). In time when Artificial Intelligence (AI) significantly shapes written communication, it becomes imperative to differentiate between text produced humans and that generated machines. The proposed approach utilizes capabilities delving into contextual embedding, revealing complex patterns serve as indicators AI origin. Through meticulous experimentation evaluation, we substantiate effectiveness our in precisely discerning text. contribution adds ongoing endeavors safeguard integrity human-authored content ever-evolving digital landscape.

Language: Английский

Citations

20

ChatGPT in Teaching and Learning: A Systematic Review DOI Creative Commons
Duha Ali, Yasin Fatemi,

Elahe Boskabadi

et al.

Education Sciences, Journal Year: 2024, Volume and Issue: 14(6), P. 643 - 643

Published: June 14, 2024

The increasing use of artificial intelligence (AI) in education has raised questions about the implications ChatGPT for teaching and learning. A systematic literature review was conducted to answer these questions, analyzing 112 scholarly articles identify potential benefits challenges related educational settings. selection process thorough ensure a comprehensive analysis current academic discourse on AI tools education. Our research sheds light significant impact improving student engagement accessibility critical issues that need be considered, including concerns quality bias generated responses, risk plagiarism, authenticity content. study aims summarize utilizations learning by addressing identified through targeted strategies. authors outlined some recommendations will integration into frameworks enhances outcomes while safeguarding standards.

Language: Английский

Citations

20

Beyond Discrimination: Generative AI Applications and Ethical Challenges in Forensic Psychiatry DOI Creative Commons
Leda Tortora

Frontiers in Psychiatry, Journal Year: 2024, Volume and Issue: 15

Published: March 8, 2024

The advent and growing popularity of generative artificial intelligence (GenAI) holds the potential to revolutionise AI applications in forensic psychiatry criminal justice, which traditionally relied on discriminative algorithms. Generative models mark a significant shift from previously prevailing paradigm through their ability generate seemingly new realistic data analyse integrate vast amount unstructured content different formats. This extends beyond reshaping conventional practices, like risk assessment, diagnostic support, treatment rehabilitation plans, creating opportunities underexplored areas, such as training education. paper examines transformative impact justice. First, it introduces its prevalent models. Following this, reviews current psychiatry. Subsequently, presents thorough exploration transform established practices introduce novel multimodal models, generation augmentation. Finally, provides comprehensive overview ethical legal issues associated with deploying focusing individuals well broader societal implications. In conclusion, this aims contribute ongoing discourse concerning dynamic challenges contexts, highlighting opportunities, risks, challenges. It advocates for interdisciplinary collaboration emphasises necessity thorough, responsible evaluations before widespread adoption into domains where decisions substantial life-altering consequences are routinely made.

Language: Английский

Citations

19

Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines DOI Creative Commons

Hui Wang,

Anh Kim Dang, Zihao Wu

et al.

Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 100326 - 100326

Published: Oct. 1, 2024

Language: Английский

Citations

19