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

и другие.

Education Sciences, Год журнала: 2024, Номер 14(12), С. 1330 - 1330

Опубликована: Дек. 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.

Язык: Английский

Large language models in patient education: a scoping review of applications in medicine DOI Creative Commons
Serhat Aydın, Mert Karabacak,

Victoria Vlachos

и другие.

Frontiers in Medicine, Год журнала: 2024, Номер 11

Опубликована: Окт. 29, 2024

Large Language Models (LLMs) are sophisticated algorithms that analyze and generate vast amounts of textual data, mimicking human communication. Notable LLMs include GPT-4o by Open AI, Claude 3.5 Sonnet Anthropic, Gemini Google. This scoping review aims to synthesize the current applications potential uses in patient education engagement.

Язык: Английский

Процитировано

7
Through ChatGPT’s Eyes: The Large Language Model’s Stereotypes and what They Reveal About Healthcare DOI
A. Meyer, Wolfgang A. Wetsch, Andrea U. Steinbicker

и другие.

Journal of Medical Systems, Год журнала: 2025, Номер 49(1)

Опубликована: Фев. 5, 2025

Язык: Английский

Процитировано

0
Lights and shadows of artificial intelligence in laboratory medicine DOI Creative Commons
Giuseppe Lippi, Mario Plebani

Advances in Laboratory Medicine / Avances en Medicina de Laboratorio, Год журнала: 2025, Номер 6(1), С. 1 - 3

Опубликована: Фев. 24, 2025

Язык: Английский

Процитировано

0
Luces y sombras de la inteligencia artificial en la medicina de laboratorio DOI Creative Commons
Giuseppe Lippi, Mario Plebani

Advances in Laboratory Medicine / Avances en Medicina de Laboratorio, Год журнала: 2025, Номер 6(1), С. 4 - 6

Опубликована: Март 1, 2025

Процитировано

0
Comparing Large Language Models for antibiotic prescribing in different clinical scenarios: which perform better? DOI Creative Commons
Andrea De Vito, Nicholas Geremia, Davide Fiore Bavaro

и другие.

Clinical Microbiology and Infection, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Generative artificial intelligence (AI) for reporting the performance of laboratory biomarkers: not ready for prime time DOI
Laura Pighi, Davide Negrini, Giuseppe Lippi

и другие.

Clinical Chemistry and Laboratory Medicine (CCLM), Год журнала: 2024, Номер unknown

Опубликована: Июль 30, 2024

Язык: Английский

Процитировано

1
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

и другие.

Education Sciences, Год журнала: 2024, Номер 14(12), С. 1330 - 1330

Опубликована: Дек. 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.

Язык: Английский

Процитировано

0