University Students’ Meaning-Making and Participation in an AI-Supported Collaborative English Course
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This study explores university students’ learning experiences in a collaborative, inquiry-based general English course that employed a range of AI-supported tools. Throughout the course, students used AI-supported generative systems, such as ChatGPT, to produce and refine texts, while non-generative AI-supported tools, like Papago and Natural Readers, supported translation, summarization, and text-to-speech tasks. Together, these AI-supported resources shaped how learners constructed meaning, processed information, and participated in collaborative activities. When fifty student artifacts, including group reports, reflective journals, and open-ended survey responses, were analyzed qualitatively four main themes emerged: (1) expanded and multilayered language-construction processes, (2) evolving structures of collaborative participation, (3) progressive development of AI-supported prompt-formulation strategies, and (4) affective responses tied to the use of AI-supported tools. Students described comparing AI-generated drafts, negotiating meaning with peers, and refining their ideas as they moved between tools. Many learners also noted that practicing prompts repeatedly helped them better control the quality of their output and use AI-supported tools more strategically. For several students, AI-supported assistance reduced anxiety, particularly in speaking and presentation tasks. Overall, the findings suggest that AI-supported tools collectively influence how learners construct meaning, collaborate with peers, and manage emotional aspects of learning. These insights offer important implications for designing AI-supported English instruction and understanding the teacher's evolving role in technology-mediated classrooms.
Abstract
This study explores university students’ learning experiences in a collaborative, inquiry-based general English course that employed a range of AI-supported tools. Throughout the course, students used AI-supported generative systems, such as ChatGPT, to produce and refine texts, while non-generative AI-supported tools, like Papago and Natural Readers, supported translation, summarization, and text-to-speech tasks. Together, these AI-supported resources shaped how learners constructed meaning, processed information, and participated in collaborative activities. When fifty student artifacts, including group reports, reflective journals, and open-ended survey responses, were analyzed qualitatively four main themes emerged: (1) expanded and multilayered language-construction processes, (2) evolving structures of collaborative participation, (3) progressive development of AI-supported prompt-formulation strategies, and (4) affective responses tied to the use of AI-supported tools. Students described comparing AI-generated drafts, negotiating meaning with peers, and refining their ideas as they moved between tools. Many learners also noted that practicing prompts repeatedly helped them better control the quality of their output and use AI-supported tools more strategically. For several students, AI-supported assistance reduced anxiety, particularly in speaking and presentation tasks. Overall, the findings suggest that AI-supported tools collectively influence how learners construct meaning, collaborate with peers, and manage emotional aspects of learning. These insights offer important implications for designing AI-supported English instruction and understanding the teacher's evolving role in technology-mediated classrooms.