# Optimizing feedback-based learning in children with developmentallanguage disorder.

> **NIH NIH R01** · MGH INSTITUTE OF HEALTH PROFESSIONS · 2024 · $413,925

## Abstract

ABSTRACT
This project aims to optimize a critical but understudied ingredient of language intervention provided to children
with developmental language disorder (DLD) – feedback. The project is designed to bridge the gap between
previous findings in our lab of inefficient feedback processing in DLD and clinical practice by identifying the
conditions under which feedback-based learning can be improved in DLD. We hypothesize that the
effectiveness of feedback can be significantly enhanced for children with DLD when it is tailored to their unique
learning strengths. The rationale for this project is based on evidence that learning can be improved by
enhancing the dominance of an intact learning system through feedback. The project will achieve its aim by
manipulating (1) the timing of the feedback (immediate vs. delayed) and (2) the level of the learner’s
involvement in error correction dictated by feedback (active vs. passive correction) to modulate the dominance
of the implicit and declarative learning systems. While immediate feedback is processed by the implicit learning
system, delaying the feedback by a few seconds implicates the declarative system. Likewise, teaching
approaches that prompt active self-correction are associated with declarative learning, while passive exposure
to corrective feedback (e.g., corrective recast) is assumed to support implicit learning. Aim 1 will determine
the effect of manipulating feedback timing on declarative and implicit learning in 140 school-age children (8-12
years) with DLD. Evidence that delaying feedback improves learning in DLD would support the hypothesis of
the implicit deficit theory that intervention should capitalize on declarative learning mechanisms. The project
will test a novel alternative feedback-learning parity hypothesis whereby feedback-based learning is optimized
when the timing of the feedback is aligned with the dominant learning system at a given time (i.e., immediate
feedback during implicit learning; delayed feedback during declarative learning). Within the same group of
children, Aim 2 will compare feedback-based learning in children with DLD when feedback (a) prompts active
self-correction or (b) passively exposes learners to error corrections. Children will engage in two nonword-
object paired-associate learning tasks. In one task feedback will promote active self-correction, which is in line
with declarative learning. In the other task, feedback will passively expose the learner to corrective feedback
and lead to learning that is assumed to be implicit. The project will determine whether children with DLD learn
better when feedback prompts self-correction or when they are exposed to passive corrections. For both aims,
behavioral indicators of response to feedback will be complemented by electrophysiological measures of
feedback processing that can determine the involvement of implicit and declarative brain systems during the
learning process. This work is scientifically and clin...

## Key facts

- **NIH application ID:** 10772094
- **Project number:** 5R01DC020735-02
- **Recipient organization:** MGH INSTITUTE OF HEALTH PROFESSIONS
- **Principal Investigator:** Yael Arbel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $413,925
- **Award type:** 5
- **Project period:** 2023-02-01 → 2028-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10772094

## Citation

> US National Institutes of Health, RePORTER application 10772094, Optimizing feedback-based learning in children with developmentallanguage disorder. (5R01DC020735-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10772094. Licensed CC0.

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