Abstract
AI tools have introduced both promise and challenge into higher education. While these tools can accelerate access to information and support writing processes, they remain unreliable in sourcing and citation—often fabricating references or obscuring the origins of knowledge. For educators, this challenge is also an opportunity: to foreground citation, source evaluation, and critical literacy in ways that traditional classrooms did not always demand. In this poster, I share my experience as a teaching professor of introductory biology and nutrition who, feels the pedagogical urgency of teaching in-text citations as a central practice in introductory science classes. The arrival of AI changed everything: rather than treating citation as a mechanical add-on, I now frame it as a means of guiding AI toward academically rigorous collaboration. Students are presented with opportunities to identify gaps, and redirect AI toward scientifically reliable sources. In this way, they are not passive consumers of machine-generated text but active agents in knowledge co-creation. Context is introductory biology and nutrition courses. Assignments require in-text citation as a rubric criterion, ensuring close engagement with readings. Formative tasks emphasize source evaluation, accurate citation, and reflection on reliability. Citation requirements prevent superficial copying and promote deeper engagement with scholarly practices. This practice speaks to key challenges of ubiquitous learning: using new technologies for new learning, teaching careful judgment of digital information, and shifting agency toward student-driven collaboration.
Presenters
Yevgeniya LapikAssociate Professor, Biology, Harold Washington College, Illinois, United States
Details
Presentation Type
Theme
2026 Special Focus—Human-Centered AI Transformations
KEYWORDS
AI, Digital Pedagogy, Critical Literacy, Scholarly Integrity, Student Agency
