Calibrated hybrid feedback model for EAP writing instruction¶

Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description¶

The article proposes a hybrid model of feedback provision in which language instructors leverage generative AI to support formative assessment while maintaining pedagogical oversight. It works through calibrated prompts and pedagogical (re-)framing, so that GenAI supplies immediate comments on student writing and the instructor supplies depth and pedagogical value. The model is grounded in the study's finding that GenAI "can supplement human feedback effectively but will not replace it."

Design Implications¶

Context¶

Requirements¶

Calibrated prompts designed by the instructor
Instructor pedagogical oversight of the feedback process

Constraints¶

GenAI supplements rather than replaces human feedback
Intended for academic writing instruction in EAP contexts

Target Learners¶

first-year EAP students in higher education

Learning Goals¶

academic argumentative writing
formative feedback on second language writing

Claims¶

Examples¶

-

Key Sources¶

Reza Farzi. (2026). Human–AI Collaboration in Academic Writing Instruction: Calibrated Feedback Model for EAP. OLBI Journal. https://doi.org/10.18192/olbij.v15i1.7773

Page metadata

Field	Value
`type`	`design`
`id`	`calibrated-hybrid-feedback-model-eap`
`title`	`Calibrated hybrid feedback model for EAP writing instruction`
`description`	`The article proposes a hybrid model of feedback provision in which language instructors leverage generative AI to support formative assessment while maintaining pedagogical oversight.`
`status`	`review`
`generated`	by `process:settle-candidates` on `2026-10-11`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `reza-farzi-2026`

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