Claims

The ICAP Framework was found effective for assessing potential for active learning in an asynchronous online environment and identifying where design improvements are needed

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · recheck by 2028: tool and model accuracy changes quickly

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 authors found the ICAP Framework very effective as a codified, objective way of assessing the level of active learning required by activities in the audited asynchronous online course. → Pollard 2025

Evidence

Pollard 2025

Pollard, V., Armatas, C., & Pepe, A. (2025). Feedback is integral: Using a revised ICAP Framework to achieve active learning in an asynchronous online course. Online Learning, 29(3), 236-253. https://doi.org/10.24059/olj.v29i3.4555

q2 · i? · design · r2

Authors' interpretation from the case-study audit addressing their first research question. They report the Framework "provided a codified and objective way of assessing the level of active learning" in the audited course; no effect size is reported.

"We found the Framework to be very effective in this regard as it provided a codified and objective way of assessing the level of active learning required for the activities in the audited course."

Studies bearing on this claim

Can a course's activities and learners' talk be coded reliably into ICAP modes, so a designer can audit a design? This table gathers the studies behind this claim and the 3 narrower claims that bear on it: 3 distinct studies (2 design, 1 associational), q2, 0 of 3 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Study Design Effect as recorded Bears on this claim through
Pollard 2025 q2 · design · r2 i? this claim; Engagement modes were unevenly distributed across units, with some units rated Interactive (supports)
Lan Anh Do 2026 q2 · design · r3 i? Human and agent framework revisions concentrate on the mid-level engagement categories (Le (qualifies)
Chen 2026 q2 · associational · r2 i? Learning-oriented engagement is recurrent but selective in everyday human–LLM conversation (supports)

Discussion

Page metadata
Field Value
type claim
id icap-effective-audit-tool-asynchronous-online
title The ICAP Framework was found effective for assessing potential for active learning in an asynchronous online environment and identifying where design improvements are needed
description The ICAP Framework was found effective for assessing potential for active learning in an asynchronous online environment and identifying where design improvements are needed
status review
evidence_strength moderate
newest_evidence 2025
source_checked 2026-10-20
recheck_by 2028
generated by process:wiki-ingest on 2026-09-26
trust unverified — no one has confirmed this page's content
sources 1 — pollard-2025

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