Mastering knowledge: the impact of generative AI on student learning outcomes
Jessica L. Pallant, Janneke Blijlevens, Alexander Campbell, Ryan Jopp
Abstract
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.