Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini DOI Creative Commons
Joe Llerena-Izquierdo, Johan Méndez Reyes, Raquel Ayala Carabajo

et al.

Education Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 1330 - 1330

Published: Dec. 4, 2024

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

Language: Английский

Comparative analysis of ChatGPT-4o mini, ChatGPT-4o and Gemini Advanced in the treatment of postmenopausal osteoporosis DOI Creative Commons
Rui Liu, Jianjun Liu,

Jia Yang

et al.

BMC Musculoskeletal Disorders, Journal Year: 2025, Volume and Issue: 26(1)

Published: April 16, 2025

Language: Английский

Citations

0
Evaluating the performance of GPT-3.5, GPT-4, and GPT-4o in the Chinese National Medical Licensing Examination DOI Creative Commons

Dingyuan Luo,

Mengke Liu,

Runyuan Yu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 23, 2025

Language: Английский

Citations

0
Response to: comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence DOI
Enes Efe İş, Ahmet Kıvanç Menekşeoğlu

Clinical Rheumatology, Journal Year: 2024, Volume and Issue: 43(12), P. 4023 - 4024

Published: Oct. 22, 2024

Language: Английский

Citations

1
Assessing the accuracy and readability of ChatGPT-4 and Gemini in answering oral cancer queries—an exploratory study DOI Creative Commons
Márcio Diniz Freitas, Rosa María López‐Pintor, Alan Roger Santos‐Silva

et al.

Published: Nov. 19, 2024

Aim: This study aims to evaluate the accuracy and readability of responses generated by two large language models (LLMs) (ChatGPT-4 Gemini) frequently asked questions lay persons (the general public) about signs symptoms, risk factors, screening, diagnosis, treatment, prevention, survival in relation oral cancer. Methods: The each response given LLMs was rated four cancer experts, blinded source responses. as 1: complete, 2: correct but insufficient, 3: includes incorrect/outdated information, 4: completely incorrect. Frequency, mean scores for question, overall were calculated. Readability analyzed using Flesch Reading Ease Flesch-Kincaid Grade Level (FKGL) tests. Results: ChatGPT-4 ranged from 1.00 2.00, with an score 1.50 (SD 0.36), indicating that usually sometimes insufficient. Gemini had ranging 1.75, 1.20 0.27), suggesting more complete Mann-Whitney U test revealed a statistically significant difference between models’ (p = 0.02), outperforming terms completeness accuracy. ChatGPT generally produces content at lower grade level (average FKGL: 10.3) compared 12.3) 0.004). Conclusions: provides accurate people may seek answers ChatGPT-4, although its less readable. Further improvements model training evaluation consistency are needed enhance reliability utility healthcare settings.

Language: Английский

Citations

1
Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o: correspondence DOI
Hinpetch Daungsupawong, Viroj Wiwanitkit

Clinical Rheumatology, Journal Year: 2024, Volume and Issue: 43(12), P. 4015 - 4016

Published: Oct. 10, 2024

Language: Английский

Citations

0
Innovations in Introductory Programming Education: The Role of AI with Google Colab and Gemini DOI Creative Commons
Joe Llerena-Izquierdo, Johan Méndez Reyes, Raquel Ayala Carabajo

et al.

Education Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 1330 - 1330

Published: Dec. 4, 2024

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

Language: Английский

Citations

0