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Pedagogically Mediated AI Use in Higher Education for Business-Oriented EFL Writing Performance and Student Experience

IMPACT SIGNAL89/100
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Information from the abstract

Aim. Despite growing interest in AI-assisted writing, empirical research rarely examines how pedagogically mediated AI use shapes both learning outcomes and student experience in business-oriented EFL writing within higher education. Thus, this studyinvestigates the design and implementation of an AI-mediated writing pedagogy in higher education, focusing on its impact on students’ academic performance and learning experience. Five artificial intelligence (AI) tools, encompassing ChatGPT, Copy.ai, Invideo.ai, Unsplash.ai, and Quillbot, were purposefully integrated into a business-oriented Creative English Writing course for Thai undergraduate EFL students.Methods. Adopting a convergent parallel mixed-methods design, the study collected quantitative data (pre- and post-writing tests, surveys, and formative assessments) and qualitative data (open-ended reflective responses) from 21 participants over a 16-weekintervention. Results. Quantitative findings revealed a statistically significant improvement in creative writing performance, alongsideconsistently high levels of motivation, enjoyment, engagement, and reduced writing anxiety. Although affective variables did not directly predict writing scores, qualitative analysis indicated that AI-mediated feedback and multimodal support enhanced students’ confidence, creativity, and willingness to revise their work. Temporary differences related to device use emerged at mid-course, whereas no gender-based differences were observed.Conclusions. This study demonstrates that the deliberate integration of AI tools, including ChatGPT, Copy.ai, Invideo.ai, Unsplash.ai, and Quillbot.com, into a business- oriented creative writing course can substantially enhance Thai EFL students’ writing performance, engagement, and affective learning, while also fostering greater autonomy and creativity.

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Why this record is monitored

This record has an Impact Signal of 89/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.

Related topics: Artificial Intelligence in Healthcare and Education · AI in Service Interactions · E-Learning and COVID-19

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Thai researcher and institutional participation

Mohammed Yassin Mohd Aba sha’ar · Somnuk Aujirapongpan · Budi Waluyo · Chanaichon Damsri · Walailak University · Silpakorn University · Nakhon Si Thammarat Rajabhat University

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Data limitations

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