Advancing Project-Based Learning Through Iterative AI Feedback: Strengthening Girls’ Confidence and Agency in Grade 9 Religious Experience · ICGS Research Library

Title

Advancing Project-Based Learning Through Iterative AI Feedback: Strengthening Girls’ Confidence and Agency in Grade 9 Religious Experience

Author

Marianne Rule

Year Published

2026

Description

The widespread accessibility of generative artificial intelligence (AI) has raised questions for educators regarding ethical use, student dependence, and intellectual agency. This mixed-methods action research study examined how iterative, teacher-calibrated AI feedback fostered girls’ confidence, feedback literacy, and intellectual agency during Grade 9 project-based learning in a Roman Catholic all-girls’ school. Sixteen girls participated in a 16-week classroom intervention centered on the Teacher-Calibrated Iterative Feedback Framework, which integrated AI-generated feedback, teacher conferencing, metacognitive reflection, and scaffolding reduction across iterative revision cycles. Data included pre- and post-surveys, student artifacts, reflections, AI interaction logs, teacher conference logs, interviews, and field notes, supporting polyangulation across student perceptions, feedback interactions, and revisions. Quantitative data were analyzed descriptively, and qualitative data were coded thematically to identify patterns in confidence and revision behavior. Findings indicated that students distinguished between exploratory AI feedback and evaluative teacher feedback, using each strategically. Over time, this differentiation was associated with increased confidence in revision decisions and strengthened intellectual agency in evaluating and applying feedback. Iterative feedback cycles supported by reflection and teacher conferencing also contributed to more critical engagement with revision processes. The study contributes an adaptable framework for integrating AI-supported feedback within project-based learning while preserving the central pedagogical role of the teacher. Findings suggest that calibrated feedback systems combining AI, reflection, and teacher expertise can support student agency and self-directed revision practices in secondary classrooms. These findings will inform continued implementation of the Teacher-Calibrated Iterative Feedback Framework in future project-based learning contexts.