UROP Project
Tracking L2 Learners’ Engagement with AI-Generated Corrective Feedback and Learning Gains: A Multiple-Case Study
AI-Generated Corrective Feedback; Engagement with Feedback; L2 Writing Instruction
Research Mentor: Zhiying Li, she/hers
Department, College, Affiliation: School of Teacher Education, Second Language Education Program, Education, Health, and Human Sciences
Contact Email: zl23@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: School of Teacher Education, Second Language Education Program, Education, Health, and Human Sciences
Contact Email: zl23@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Open to all majors
Project Location: Virtual
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Number of Research Assistants: 1
Relevant Majors: Open to all majors
Project Location: Virtual
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Project Description
The integration of generative AI (Gen-AI) tools into second language (L2) writing has transformed how L2 learners receive and process corrective feedback, but little is known so far about how learners’ engagement with AI-generated feedback shapes long-term knowledge development. This mixed-methods, multiple-case study will contribute to this gap. The data collection procedure will last for approximately five weeks: 5-10 university-level participants will complete weekly writing tasks online, submit drafts to a Gen-AI tool, learn from the generated feedback, and complete immediate and delayed repeated writing tasks. With the longitudinal data, this study intends to track (1) students’ cognitive and affective engagement with the Gen-AI feedback through surveys and interviews, (2) students’ learning gains gauged by their successful error correction in immediate post-writing (which is, immediate gains) and delayed post-writing (which is, sustained gains). Research findings will empower educators to leverage AI’s potential to facilitate L2 learners’ immediate and long-term learning growth.Research Tasks: 1. Contribute to draft IRB documents (protocol, consent forms, recruitment materials) under the mentor’s guidance.
2. Schedule writing sessions for participants on synchronous video-communication platforms.
3. Collaborate with the mentor to collect data remotely, including monitoring and recording participants’ processes of pre-writing, feedback learning, and post-writing, distributing surveys, and conducting structured interviews using pre-approved protocols.
4. Collaborate with the mentor to analyze data.
5. Maintain organized datasets and keep them anonymized.
Skills that research assistant(s) may need: Interest in the research of AI in education (Required).
Organizational skills for managing multiple participants/timelines (Required).
Communicative skills for giving clear instructions to participants (Required).
Background/coursework in Applied Linguistics, Education, Psychology, or TESOL (Recommended).