Evaluating Students' Attitude of the AI-integrated Tasks in TCSOL Classroom Using the CAC Model

AI is rapidly transforming education, supported by global initiatives like the EU's 2020 White Paper on AI, the 2023 EU AI Act, the U.S. AI Risk Management Framework, and China's 2017 New Generation AI Development Plan. Researchers increasingly focus on AI chatbots in teaching and learning, recognizing their potential to revolutionize classroom dynamics. AI has been used by teachers for creating materials, designing activities, and providing feedback. However, AI can also empower students by enhancing their knowledge acquisition and critical thinking skills. Despite extensive research on AI's pedagogical applications, a significant gap exists in understanding students' attitudes and experiences with AI in real classroom settings. This study addresses this gap by exploring AI's integration into TCSOL tasks to boost student engagement and learning. The research employs a mixed-methods approach, combining quantitative and qualitative data collection techniques. This includes anonymous questionnaire surveys and semi-structured group interviews with 27 students who have been practicing AI-integrated tasks in the CLT202 course at XJTLU. The mixed-methods design allows for a comprehensive analysis of students' cognitive, affective and behavioral attitude with AI in the classroom, providing both breadth and depth to the findings. By examining students' perspectives and readiness to engage with AI, the study aims to provide actionable insights for educators.

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Published
2025-05-14
DOI
https://doi.org/10.1109/icaie64856.2025.11158353
Primary Topic
Technology and Data Analysis
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article
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article

Evaluating Students' Attitude of the AI-integrated Tasks in TCSOL Classroom Using the CAC Model

Henghua Su, Haixia Wang
Technology and Data Analysis
article

Evaluating Students' Attitude of the AI-integrated Tasks in TCSOL Classroom Using the CAC Model

Henghua Su, Haixia Wang
article en

Abstract

AI is rapidly transforming education, supported by global initiatives like the EU's 2020 White Paper on AI, the 2023 EU AI Act, the U.S. AI Risk Management Framework, and China's 2017 New Generation AI Development Plan. Researchers increasingly focus on AI chatbots in teaching and learning, recognizing their potential to revolutionize classroom dynamics. AI has been used by teachers for creating materials, designing activities, and providing feedback. However, AI can also empower students by enhancing their knowledge acquisition and critical thinking skills. Despite extensive research on AI's pedagogical applications, a significant gap exists in understanding students' attitudes and experiences with AI in real classroom settings. This study addresses this gap by exploring AI's integration into TCSOL tasks to boost student engagement and learning. The research employs a mixed-methods approach, combining quantitative and qualitative data collection techniques. This includes anonymous questionnaire surveys and semi-structured group interviews with 27 students who have been practicing AI-integrated tasks in the CLT202 course at XJTLU. The mixed-methods design allows for a comprehensive analysis of students' cognitive, affective and behavioral attitude with AI in the classroom, providing both breadth and depth to the findings. By examining students' perspectives and readiness to engage with AI, the study aims to provide actionable insights for educators.

Xi’an Jiaotong-Liverpool University (CN)
Openalex Percentile: Top 62%
Technology and Data Analysis
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