Insta-Reviewer

Product or Programme · All products and programmes
Evidence · 1 claim (1 against) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

Insta-Reviewer is a research-developed software system that extracts salient sentences from student project reports and uses a fine-tuned BART model to generate textual feedback.

Components

Claims

• In one essay-feedback system, fine-tuned models produced no usable deep-level feedback output, so only directly prompted LLMs were evaluated; the authors suggest prompting may be more effective than supervised fine-tuning for this task [-W]

Related Products and Programmes

• Dataset of 484 de-identified student project reports with instructor reviews collected over twelve semesters

Key Sources

• Qinjin Jia, Mitchell Young, Yunkai Xiao, Jialin Cui, Chengyuan Liu, Parvez Rashid, Edward Gehringer. (2022). Automated Feedback Generation for Student Project Reports: A Data-Driven Approach. Journal of Educational Data Mining, Volume 14, No 3. https://github.com/qinjinjia/JEDM22_Automated_Feedback_Generation

Page metadata

Field	Value
type	product
id	insta-reviewer
title	Insta-Reviewer
description	Insta-Reviewer is a research-developed software system that extracts salient sentences from student project reports and uses a fine-tuned BART model to generate textual feedback.
status	review
moved_from	element/insta-reviewer-system
product_kind	software
generated	by process:sweep-kinds on 2026-10-10
trust	unverified — no one has confirmed this page's content
sources	1 — qinjin-jia-2022

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