Hurst exponents do not significantly predict retention self-explanation quality over and above pretest scores¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2016 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Students' Hurst exponent did not significantly predict retention self-explanation quality over and above pretest self-explanation quality (R² = .27, F(1,37) = 2.70, p = .10). → 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 · r2

Second linear regression model predicting retention self-explanation quality from pretest scores and Hurst exponents in the same 40-student sample. The article reports the Hurst predictor was not significant (R² = .27, F(1,37) = 2.70, p = .10); no effect size is printed.

"students ’ Hurst exponent did not significantly predict the quality of their retention self-explanation quality over and above pretest self-explanation quality (R2 =. 2 7 ,F(1,37) = 2.70, p =. 1 0"

Discussion¶

Related Claims¶

• Hurst exponents predict daily training self-explanation quality over and above pretest self-explanation ability — related
• Deterministic interaction patterns relate to delayed retention self-explanation quality but not posttest performance — related
• Hurst exponents are unrelated to the frequency of interacting with any specific game-based feature — related
• Surrogate analysis validates that observed Hurst exponents reflect genuine persistence rather than short-series artifacts — related
• Students who interact more deterministically within iSTART-ME generate higher quality self-explanations during training — related