Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Teacher’s Perceptions and Hesitancy: Integrating ChatGPT as a Tool in English Language Learning
2
Zitationen
2
Autoren
2024
Jahr
Abstract
Incorporation of innovative technologies has acquired importance for enhancing pedagogical strategies for effective language learning. This study explored the perceptions and hesitancies of English teachers in Bangladesh regarding the integration of ChatGPT as a language learning tool. Thirty-one English teachers from diverse educational institutions of high school and above across different regions of Bangladesh were recruited for the study in August 2023. A structured questionnaire was designed and utilized to elicit socio-demographic information, perceptions and hesitancy of these teachers towards adoption of ChatGPT as a language learning tool. Data analysis was carried out using SPSS. Almost 80% participants were willing to recommend the use of ChatGPT to other English teachers yet hesitant about it. Familiarity with ChatGPT, confidence in incorporating ChatGPT into their English lessons (p0.001) were found to be positively correlated with the positive attitudes towards its integration. Teachers less likely to encourage students to use ChatGPT for English language learning outside the classroom are more hesitant to adopt Chatbot GPT in their teaching practice (p = 0.004). A consistent pattern of positive agreement among participants was seen regarding the willingness to receive professional training on ChatGPT. The findings of this pilot study shed light on the initial attitudes of English teachers in Bangladesh towards incorporating ChatGPT in language learning. While some displayed enthusiasm due to its potential benefits, others expressed hesitations regarding its impact on traditional teaching methods. The outcomes highlight the need for further exploration and teacher training in integrating such technologies effectively.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.561 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.452 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.948 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.797 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.