Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Revolutionizing EFL writing: unveiling the strategic use of ChatGPT by Indonesian master’s students
12
Zitationen
7
Autoren
2024
Jahr
Abstract
The primary aim of this study is to delve into the experiences of postgraduate EFL students in using ChatGPT and to uncover the strategic approaches they implement throughout their writing process. This qualitative case study research design engages 16 Master’s degree students from four different universities in Indonesia, each with varying levels of English proficiency. Findings indicate a positive reception of ChatGPT among EFL students, who note its versatility in improving vocabulary, grammar, idea generation, essay structuring, and language refinement. Students utilize a range of strategies in their interactions with ChatGPT, including critical evaluation, peer consultation, and the use of primary research sources, which demonstrates its adaptability as an educational resource. These findings suggest that ChatGPT could revolutionize EFL instruction by serving as an adaptable cognitive tool that aligns with diverse pedagogical models and cognitive development stages. Its capabilities support educational theories such as Scaffolded Writing, Distributed Cognition, and Cognitive Flexibility Theory, which enhance students’ self-efficacy and academic success. However, the study’s reliance on self-reported data and its limited sample size are notable limitations, potentially impacting the generalizability of the results. The study recommends that future research with a broader, more diverse sample and a mixed-methods framework could provide deeper insights into the effectiveness of ChatGPT in EFL contexts and its potential to augment students’ writing competencies.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.245 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.100 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.466 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.429 Zit.