Staged research agenda for GenAI peer feedback: feasibility, quasi-experimental quality and literacy studies, uptake trials, stakeholder perspectives, and equity analyses¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article outlines a five-strand research agenda. Initial mixed-methods case studies should establish feasibility, usability, and classroom fit, using "usage logs (e.g., completion times, access frequency), short post-activity surveys, and semi-structured interviews". Quasi-experimental or randomized designs can then compare Trainer classes with business-as-usual peer review using established coding schemes and feedback literacy scales; Synthesizer studies can compare processing with and without synthesized reports using action plans, recorded performances, and self-report measures; interview and observation studies should examine stakeholder perceptions of redistributed authority; and multi-site designs should disaggregate outcomes by learner subgroups to detect equity gaps.

Design Implications¶

Context¶

Requirements¶

• Close collaboration between researchers, teachers, and students to keep AI-supported feedback grounded in pedagogical priorities

Constraints¶

• Early work should be small-scale classroom trials refining the tools and validating measures before more rigorous comparative designs are adopted

Target Learners¶

• EFL/ESL learners across institutional types, proficiency levels, and cultural contexts

Target Learning Goals¶

• Feedback quality, feedback literacy, uptake, affect, and speaking performance outcomes

Related Strategies¶

• Collaborative cross-cultural research agenda for validating AI-enabled pedagogical accompaniment

Examples¶

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Key Sources¶

• Bradley Irwin and Theron Muller. (2026). Positioning Generative AI in EFL Peer Feedback: Training Feedback Literacy and Enabling Uptake in Speaking Classes. Educ. Sci. 2026, 16, 544. https://doi.org/10.3390/educsci16040544