Claims

Adaptivity does not sacrifice enjoyment

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2024 · checked against its sources 2026-10-28 (automated, 1 of 1 entry) · not reviewed by a person
Design limits · Yannier 2024: groups were assigned but students were analysed as independent (read from the study by two models, 2026-10-28)

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.

q3 i? No significant difference in enjoyment between adaptive and randomized conditions. → Yannier 2024

Evidence

Yannier 2024

Yannier, N., Hudson, S. E., Chang, H., & Koedinger, K. R. (2024). AI Adaptivity in a Mixed-Reality System Improves Learning. International Journal of Artificial Intelligence in Education, 34, 1541–1558. https://doi.org/10.1007/s40593-023-00388-5

q3 · i? · causal · r2

Enjoyment surveys given after interaction showed "no significant difference in the enjoyment outcomes of the different conditions"; equivalence was not tested.

"We confirmed that the reduced variability in the adaptive condition (e.g., getting another base question once they get a base question wrong) did not reduce engagement. There was no significant difference in the enjoyment outcomes of the different conditions."

Discussion

Learner Variables

Page metadata
Field Value
type claim
id bkt-adaptivity-no-enjoyment-cost
title Adaptivity does not sacrifice enjoyment
description Adaptivity does not sacrifice enjoyment
status review
evidence_strength moderate
newest_evidence 2024
source_checked 2026-10-28
generated by process:wiki-ingest on 2026-10-28
trust unverified — no one has confirmed this page's content
sources 1 — yannier-2024

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