The Altair (engine) main effect is not significant for winter RIT scores in either content area, but an Altair-by-sex interaction is significant in Reading only¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r2 · q2
Currency · newest study 2020 · checked against its sources 2026-10-15 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q2 i? Adding the Altair treatment variable does not improve model fit for winter RIT scores in Reading or Mathematics. → Bo 2020 q2 i? An Altair-by-sex interaction significantly improves model fit in Reading (chi-squared = 6.75, p < 0.01) but not in Mathematics (chi-squared = 0.31, p = 0.57). → Bo 2020 (2)

Evidence¶

Bo 2020¶

Bo, E., & Meyer, P. (2020). Comparability of MAP Growth tests administered through different technology and psychometric infrastructure: An engine evaluation study based on empirical data. Portland, OR: NWEA. https://www.nwea.org/research/publication/comparability-of-map-growth-tests-administered-through-different-technology-and-psychometric-infrastructure-an-engine-evaluation-study-based-on-empirical-data/

q2 · i? · causal · r2

Mixed-effect model comparison (students nested within schools; 165,906 Reading and 163,058 Mathematics students) testing the Altair fixed effect. The article reports nonsignificant chi-squares, and profile confidence intervals for Altair included 0 in both content areas.

"The chi-square test for deviance of Model 2 and Model 3 yielded nonsignificant chi-squares for both content areas (chi-squared = 0.04, p= 0.83 in Reading; chi-squared = 1.06, p= 0.30 in Mathematics), indicating that the Altair variable is not needed to predict the winter RIT scores in both content areas."

Bo 2020 (2)¶

Bo, E., & Meyer, P. (2020). Comparability of MAP Growth tests administered through different technology and psychometric infrastructure: An engine evaluation study based on empirical data. Portland, OR: NWEA. https://www.nwea.org/research/publication/comparability-of-map-growth-tests-administered-through-different-technology-and-psychometric-infrastructure-an-engine-evaluation-study-based-on-empirical-data/

q2 · i? · causal · r2

Likelihood-ratio test comparing Models 3 and 4 in the same nested mixed-effect analysis. The Altair-by-sex coefficient was significant in Reading, with a 95% profile confidence interval of 0.14 to 1.02 (Altair:Male). No standardized effect size was printed, so impact is coded i?: the size of the effect is not reported, which is not the same as no effect.

"The chi-square test for deviance of Model 3 and Model 4 yields a significant chi-square in Reading (chi-squared = 6.75, p < 0.01) and a non-significant chi-square in Mathematics (chi-squared=0.31, p=0.57), indicating that the sex and Altair interaction variable should be included to predict the winter Reading RIT scores."

Discussion¶

Learner Variables¶

• Gender — moderator: an instructional effect differs by group

Related Claims¶

• GenAI function, intervention duration, publication year, and gender were not significant moderators of GenAI's motivational effect — the general claim this finding bears on, with the studies behind it
• Growth-score differences between CBE and COLO are small, exceeding 0.2 only in Reading Grades K–1 (favoring CBE) and Mathematics Grade 8 (favoring COLO) — related
• Marginal reliabilities of MAP Growth winter scores are comparable across engines and all in the 0.90s, with CBE showing slightly higher precision (lower SEM) — related