Hurst exponents are unrelated to the frequency of interacting with any specific game-based feature¶
Claim · All claims
Evidence · 1 study · associationalr1·q2
Currency · newest study 2016 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2019: 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? Hurst exponents were not significantly related to frequency of interactions with generative practice games (r = .25, p = .11), identification mini-games (r = −.12, p = .45), personalizable features (r = −.06, p = .70), or achievement screen views (r = −.24, p = .13). → Erica L. Snow 2016
Evidence¶
Erica L. Snow 2016¶
Erica L. Snow, Aaron D. Likens, Laura K. Allen, & Danielle S. McNamara. (2016). Taking Control: Stealth Assessment of Deterministic Behaviors Within a Game-Based System. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-015-0085-5
q2 · i? · associational · r1
Pearson correlations between Hurst exponents and frequency of interaction with each of the four iSTART-ME feature categories. All four correlations were non-significant; the article concludes Hurst exponents capture "how they interact with these features," not which features students choose.
"students’ Hurst exponents were not significantly related to students ’ frequency of interactions with generative practice games ( r =. 2 5 , p = .11), identification mini-games (r = −.12, p = .45), personalizable features ( r = −.06, p = .70), or achievement screen views ( r = −.24, p = .13)"
Discussion¶
Related Claims¶
- Students who interact more deterministically within iSTART-ME generate higher quality self-explanations during training — related
- Deterministic interaction patterns relate to delayed retention self-explanation quality but not posttest performance — related
- Hurst exponents predict daily training self-explanation quality over and above pretest self-explanation ability — related
- Hurst exponents do not significantly predict retention self-explanation quality over and above pretest scores — related
- Surrogate analysis validates that observed Hurst exponents reflect genuine persistence rather than short-series artifacts — related
- A regularity view of causation is less suited than practice analysis to explaining how interaction patterns unfold over time — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
hurst-unrelated-to-feature-frequency |
title |
Hurst exponents are unrelated to the frequency of interacting with any specific game-based feature |
description |
Hurst exponents are unrelated to the frequency of interacting with any specific game-based feature |
status |
review |
evidence_strength |
weak |
newest_evidence |
2016 |
recheck_by |
2019 |
generated |
by process:wiki-ingest on 2026-10-16 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — erica-l-snow-2016 |
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