Skip to main content

Table 2 Multiple linear regression model results for post-class tree thinking concept inventory scores

From: A comparison study of human examples vs. non-human examples in an evolution lesson leads to differential impacts on student learning experiences in an introductory biology course

  TTCI Post-Score (Model 1) TTCI Post-Score (Model 2)
CC MI CC MI
Β
(Std. error)
p-value Β
(Std. error)
p-value Β
(Std. error)
p-value Β
(Std. error)
p-value
Intercept 1.96
(1.44 – 2.49)
 < 0.001 1.895
(1.66 – 2.13)
 < 0.001 2.50
(1.86 – 3.14)
 < 0.001 2.428
(2.14–2.72)
 < 0.001
TTCI Pre-Score 0.59
(0.49 – 0.69)
 < 0.001 0.606
(0.558 – 0.654)
 < 0.001 0.46
(0.32 – 0.60)
 < 0.001 0.468
(0.40 - 0.54)
 < 0.001
Year (Reference: Year 1) − 0.40
(− 0.82 to 0.01)
0.059 − 0.22
(– 0.39 to – 0.05)
0.197 − 0.41
(– 0.83 to 0.00)
0.050 − 0.254
(− 0.42 – 0.09)
0.134
I-SEAH (Centered) 0.02
(− 0.03 to 0.08)
0.393 0.032
(0.01 – 0.06)
0.196 0.01
(– 0.03 to 0.05)
0.560 0.012
(− 0.01 – 0.03)
0.502
Treatment (Reference: Animal) 0.35
(− 0.07 to 0.77)
0.102 0.281
(0.09 – 0.48)
0.153 − 0.77
(– 1.65 to 0.12)
0.090 − 0.692
(– 1.094 to − 0 .29)
0.086
Treatment X I-SEAH − 0.03
(− 0.11 to 0.05)
0.477 − 0.042
(− 0.08 − 0.01)
0.231 - - - -
Treatment X TTCI Pre-Score - - - - 0.28
(0.08 – 0.47)
0.006 0.249
(0.157 – 0.342)
0.008
Observations 282 673 275 673
R2 / adjusted R2 0.343/0.331   0.376 / 0.364  
  1. Full model results predicting student TTCI post-scores using complete-case data (CC) and multiple imputation (MI). Year and treatment are binary variables with reference values in parentheses. MI results are pooled following Rubin (2004). Coefficients significant at p ≤ 0.05 are bolded