Using GenAI to Support Learning: Reading Empirical Articles
Victoria Cross
Description
We can't forbid it...we can't ignore it...we had better teach it. I have developed a template that encourages students to use Generative AI appropriately as they tackle reading an empirical journal article. The template alternates between tasks that can be outsourced to GenAI and tasks that the student completes without GenAI. The template is content-neutral, so it could be used to tackle empirical articles in many disciplines. It walks students through summarizing complex technical information in plain language, finding evidence to support the summary, verifying that the summary is accurate and not taken out of context, and critiquing both generative AI and the article. Students have used this template to support their learning in a GE writing course. In this prerecorded presentation, I will share the template and describe usage and feedback from the students and the TAs. The template is available for others to adopt and adapt.
Link to the video [video.ucdavis.edu]
Access the presentation slides (PDF)
♦ Dr. Cross will be participating in a live panel session on September 12th at 12:00 pm to briefly discuss her talk and answer questions from the audience. To submit a question for Dr. Cross, use the SITT 2024 Panel Questions Google Form.
About the Presenter
Victoria Cross, Ph.D. is an Associate Professor of Teaching in the Department of Psychology. She primarily teaches courses on research methods, scientific reasoning, and critical thinking. Her early career focused on effective uses of educational technology in higher education. Her current research interests in the scholarship of teaching and learning are around investigating the challenges faced in leveling the playing field when teaching critical thinking skills to a diverse student body and the cognitive mechanisms at play in student learning.
