Опубликована: Янв. 1, 2024
Язык: Английский
Опубликована: Янв. 1, 2024
Язык: Английский
Education Sciences, Год журнала: 2024, Номер 14(8), С. 814 - 814
Опубликована: Июль 25, 2024
This paper investigates the integration of ChatGPT into educational environments, focusing on its potential to enhance personalized learning and ethical concerns it raises. Through a systematic literature review, interest analysis, case studies, research scrutinizes application in diverse contexts, evaluating impact teaching practices. The key findings reveal that can significantly enrich education by offering dynamic, experiences real-time feedback, thereby boosting efficiency learner engagement. However, study also highlights significant challenges, such as biases AI algorithms may distort content inability replicate emotional interpersonal dynamics traditional teacher–student interactions. acknowledges fast-paced evolution technologies, which render some obsolete, underscoring need for ongoing adapt strategies accordingly. provides balanced analysis opportunities challenges education, emphasizing considerations strategic insights responsible technologies. These are valuable educators, policymakers, researchers involved digital transformation education.
Язык: Английский
Процитировано
20Journal of Science Education and Technology, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 18, 2024
Язык: Английский
Процитировано
9Computers and Education Artificial Intelligence, Год журнала: 2024, Номер unknown, С. 100355 - 100355
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
6Computers & Education, Год журнала: 2024, Номер unknown, С. 105224 - 105224
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
5Education and Information Technologies, Год журнала: 2025, Номер unknown
Опубликована: Янв. 3, 2025
Язык: Английский
Процитировано
0Journal of Educational Computing Research, Год журнала: 2025, Номер unknown
Опубликована: Янв. 6, 2025
The rapid development of large language models (LLMs) presented opportunities for the transformation science and STEM education. Research on LLMs was in exploratory phase, characterized by discussions observations rather than empirical investigations. This study a framework incorporating into Science Engineering Practice (SEP), utilizing case submarine construction, followed four-week quasi-experimental validation. research employed conditional cluster sampling, selecting two homogeneous natural classes from middle school China to serve as experimental control groups. key variable inclusion SEP project. Various validated self-developed assessment tools were used measure students’ learning outcomes. Statistical analyses, including pre- post-test paired comparisons within ANCOVA between-class differences, performed evaluate effects LLM integration. results showed that students participating integrated with significantly improved their mastery scientific knowledge, attitudes towards science, perceived usefulness technology, understanding engineering, computational thinking skills, problem-solving abilities. In contrast, traditional exhibited weaker knowledge acquisition, differences engineering concepts, lack skills. pioneering effort integrating education provided reference deeper application future.
Язык: Английский
Процитировано
0Journal of Education and Educational Research, Год журнала: 2025, Номер 12(1), С. 29 - 34
Опубликована: Янв. 17, 2025
This study investigates the role of generative artificial intelligence (AIGC), particularly large language models, in enhancing digital literacy pre-service teachers. With rapid growth AI technologies, integrating into education has gained significant attention. The research focuses on how varying frequencies usage affect teachers’ skills information processing, problem-solving, and critical thinking. Using a polynomial regression model, we analyze relationship between factors such as frequency, problem-solving time, feedback quality, scores. results indicate that frequent use substantially improves literacy, with high-frequency group achieving higher more consistent scores compared to low-frequency group. Personalized project-based tasks, provided by AI, enhance students’ comprehension application technologies. shows incorporating teacher training programs not only supports personalized learning but also fosters essential competencies. findings provide valuable insights for teachers' lay foundation future educational practices involving
Язык: Английский
Процитировано
0Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100367 - 100367
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100377 - 100377
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
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