Evidence for agentic AI in education is strongest for formative tutoring and SRL coaching, while orchestration and assessment applications remain at mid technology-readiness stages¶
Claim · All claims
Evidence · 1 study · reviewr2·q2
Currency · newest study 2025 · checked against its sources 2026-10-18 (automated, 1 of 1 entry) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? The review's evidence map finds the strongest empirical grounding in formative tutoring and self-regulated learning coaching, with quasi-experimental and randomized controlled designs reporting measurable improvements in feedback accuracy and strategy use. → Kostopoulos 2025
q2 i? Orchestration and assessment applications remain at mid TRL stages (4-6), emphasizing feasibility and workflow efficiency rather than direct learning gains. → Kostopoulos 2025
Evidence¶
Kostopoulos 2025¶
Kostopoulos, G., Gkamas, V., Rigou, M., & Kotsiantis, S. (2025). Agentic AI in Education: State of the Art and Future Directions. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3620473
q2 · i? · review · r2
Narrative review synthesis: the authors' evidence map (Table 3) consolidates studies into five agentic roles across HE, VET and K-12, aligning each role with evaluation domain, outcome metrics and technology readiness level. The review reports that "quasi-experimental and randomized controlled designs report measurable improvements" in these two areas.
"The strongest empirical grounding appears in formative tutoring and self-regulated learning (SRL) coaching, where quasi-experimental and randomized controlled designs report measurable improvements in feedback accuracy and strategy use."
Discussion¶
Related Claims¶
- Many agentic multi-agent implementations remain at prototype or conceptual stage with limited large-scale deployment and empirical validation — related
- AI's direct impact on SRL concentrates on metacognitive and cognitive aspects while motivation remains underexplored — related
- A randomized controlled trial with 86 K-12 students found a significant gain in self-regulated-learning strategy use from agentic coaching systems — a narrower finding that bears on this claim
- Current AI deployments in higher education remain task-oriented rather than ecosystem-oriented despite advances in LLMs and multimodal AI — related
- In university physics education, AI has been applied for tutoring and explanations, formative feedback and scaffolding, collaborative problem solving, simulation and modeling, instructional design, and AI literacy development — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
agentic-ai-evidence-strongest-tutoring-srl-coaching |
title |
Evidence for agentic AI in education is strongest for formative tutoring and SRL coaching, while orchestration and assessment applications remain at mid technology-readiness stages |
description |
Evidence for agentic AI in education is strongest for formative tutoring and SRL coaching, while orchestration and assessment applications remain at mid technology-readiness stages |
status |
review |
evidence_strength |
weak |
newest_evidence |
2025 |
source_checked |
2026-10-18 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — kostopoulos-2025 |
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