Mastering knowledge: the impact of generative AI on student learning outcomes
研究通过192名学生反思的准实验分析，发现使用生成式AI构建和增强知识（掌握法）能带来更高层次的学习成果，而程序化使用则效果较差。
Generative AI (GenAI) has had a significant impact across industries since the launch of ChatGPT in late 2022. Much of the focus of existing research in the higher education space has considered the impact GenAI has had on academics and institutions. Conversely, research has been less focused on the impact this technology will have on students. Our research investigates how GenAI impacts student learning outcomes in higher education. We applied a quasi-experimental lens to analyse qualitative data of 192 student reflections and apply quantitative content analysis (QCA). Results indicate that a higher level of learning occurs when students use GenAI to construct and augment knowledge (mastery approach). In contrast, lower-level learning outcomes resulted from using GenAI procedurally without augmenting knowledge (procedural approach). Through a practical lens, the course curriculum can be designed to include GenAI to scaffold students’ learning from basic knowledge construction tasks to more complex augmentation of knowledge. Assessment design can be adjusted to promote mastery goal structures, encouraging students to critically engage with GenAI outputs rather than simply reproducing them, fostering optimal learning outcomes.