Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o

Is, Enes Efe; Menekseoglu, Ahmet Kivanc

doi:10.1007/s10067-024-07154-5

Clin Rheumatol

2024

DOI: 10.1007/s10067-024-07154-5

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Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o

Enes Efe Is,

Ahmet Kivanc Menekseoglu

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Cited by 4 publications

References 29 publications

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Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Daungsupawong,

Wiwanitkit

2024

Clin Rheumatol

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Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Daungsupawong,

Wiwanitkit

2024

Clin Rheumatol

View full text Add to dashboard Cite

Response to: comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Is,

Menekseoglu

2024

Clin Rheumatol

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Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini

Llerena-Izquierdo,

Mendez-Reyes,

Ayala-Carabajo

et al. 2024

Education Sciences

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This study explores the impact of artificial intelligence on the teaching of programming, focusing on the GenAI Gemini tool in Google Colab. It evaluates how this technology influences the comprehension of fundamental concepts, teaching processes, and effective teaching practices. In this research, students’ motivation, interest, and satisfaction are determined, as well as the fulfillment and surpassing of their learning expectations. With a quantitative approach and a quasi-experimental design, an investigation was carried out in seven programming groups in a polytechnic university in Guayaquil, Ecuador. The results reveal that the use of GenAI significantly increases interest in programming, with 91% of the respondents expressing increased enthusiasm. In addition, 90% feel that the integration of GenAI meets their expectations, and 91% feel that it has exceeded those expectations in terms of educational support. This study evidences the value of integrating advanced technologies into education, suggesting that GenAI can transform the teaching of programming. However, successful implementation depends on timely training of educators, ethics training for students, ongoing interest in the technology, and a curriculum design that maximizes the capabilities of GenAI.

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Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o

Cited by 4 publications

References 29 publications

Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Response to: comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence

Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini

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