Claims

Empirical ILE papers show a strong increase in breadth of content and time of use

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2016 · not yet checked against its sources · 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? Across the analysed years, empirical papers shifted from single-topic, single-session systems to environments covering many topics over a month or more. → Ido Roll & Ruth Wylie 2016

Evidence

Ido Roll & Ruth Wylie 2016

Ido Roll & Ruth Wylie. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education, 26, 582-599. https://doi.org/10.1007/s40593-016-0110-3

q2 · i? · review · r2

Breadth coding of only the empirical papers (Table 4), using the rubric of 1 topic/less than 1 h, few topics/less than 5 h, or many topics/over a month: in 2014, 5 of 10 empirical papers (50%) covered many topics over a month or more.

"As shown in Table 4, there is a very strong increase in the breadth of content that is covered and in the time spent using the environments. We see this as a positive trend."

Discussion

Page metadata
Field Value
type claim
id aied-breadth-increase-topics-time
title Empirical ILE papers show a strong increase in breadth of content and time of use
description Empirical ILE papers show a strong increase in breadth of content and time of use
status review
evidence_strength moderate
newest_evidence 2016
generated by process:wiki-ingest on 2026-10-16
trust unverified — no one has confirmed this page's content
sources 1 — ido-roll-ruth-wylie-2016

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