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Applying ChatGPT to tackle the side effects of personal learning environments from learner and learning perspective: An interview of experts in higher education.
Xu, XiaoShu; Wang, XiBing; Zhang, YunFeng; Zheng, Rong.
Afiliación
  • Xu X; School of Foreign Studies, Wenzhou University, Wenzhou, Zhejiang, China.
  • Wang X; School of Information Engineering, Yunnan Vocational College of Mechanical and Electrical Technology, Kunming, Yunnan, China.
  • Zhang Y; Centre for Portuguese Studies, Macao Polytechnique University, Sé Freguesias, Macao, China.
  • Zheng R; School of Education, Baoshan University, Baoshan, Yunnan, China.
PLoS One ; 19(1): e0295646, 2024.
Article en En | MEDLINE | ID: mdl-38170691
ABSTRACT
This paper investigates the capacity of ChatGPT, an advanced language model created by OpenAI, to mitigate the side effects encountered by learners in Personal Learning Environments (PLEs) within higher education. A series of semi-structured interviews were conducted with six professors and three Information and Communication Technology (ICT) experts. Employing thematic analysis, the interview data were assessed, revealing that the side effects stemming from the learner and learning perspectives could be primarily categorized into cognitive, non-cognitive, and metacognitive challenges. The findings of the thematic analysis indicate that, from a cognitive standpoint, ChatGPT can generate relevant and trustworthy information, furnish personalized learning resources, and facilitate interdisciplinary learning to fully actualize learners' potential. Moreover, ChatGPT can aid learners in cultivating non-cognitive skills, including motivation, perseverance, self-regulation, and self-efficacy, as well as metacognitive abilities such as self-determination, self-efficacy, and self-regulation, by providing tailored feedback, fostering creativity, and stimulating critical thinking activities. This study offers valuable insights for integrating artificial intelligence technologies to unleash the full potential of PLEs in higher education.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Metacognición Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Metacognición Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: China