The Impact of Generative Artificial Intelligence on
Students Learning Outcomes
Chuanjia Wei
Quanzhou College of Technology, Quanzhou, Fujian 362200, P. R. ChinaE-mail: 15080406979@163.com; weichuanjia1983@gmail.com
[Abstract]Since the launch of ChatGPT at the end of 2022, generative artificial intelligence (GenAl) hasexerted profound impacts across all industries, Extant research in higher education predominantly focuses on theimplications of generative AI for instructors and institutions, while studies examining its effects on studentsremain relatively scarce. This study explores how generative artificial intelligence shapes undergraduate learningoutcomes, Adopting a quasi-experimental framework, the research analyzes qualitative data from 192 studentrefective reports via Quantitative Content Analysis (QCA). The results reveal that students achieve higher-orderlearning outcomes when they employ generative AI for knowledge construction and expansion (mastery-orientedapproach). In contrast, students who utilize generative AI merely for task completion without subsequentknowledge elaboration (prject-oriented apprach) demonstrate low-level learning performance. Practically, syllabican integrate GenAI-oriented instructional design to scaffold students' learning progresion from foundationalknowledge-building tasks to advanced knowledge expansion activities. Assessment frameworks can berestructured to prioritize mastery goal structures, prompting students to engage in critical evaluation rather thanpassive replication of Al-generated outputs, thereby optimizing their learning achievements.
[Keywords]: learning outcomes; generative artificial intelligence; higher education; goalstructure;Quantitative Content Analysis (QCA)
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