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Table 6 Study 2—summary of hierarchical linear model results of outcomes on the summative assessment

From: Iterative design of a simulation-based module for teaching evolution by natural selection

Q: Does treatment (workbook version vs tutorial version) predict student summative assessment score?
A: No. Students in the two treatments, workbook version and tutorial version, did not differ in their summative assessment performance
Score ~ treatment
Fixed predictor Estimate ± SE p value
Intercept 69.55 ± 2.32 < 0.0001
Treatment (workbook) − 0.49 ± 3.24 0.881
Q: Does treatment (workbook version vs tutorial version) predict student summative assessment score controlling for their type of class (Advanced vs Beginner)?
A: No. There is not an interaction between treatment and type of class
Score ~ treatment + type of class + treatment * type of class
Fixed predictor Estimate ± SE p value
Intercept 67.80 ± .2.76 < 0.0001
Treatment (workbook) − 2.20 + 4.04 0.589
Type of class (Advanced) 5.35 ± 4.79 0.272
Treatment * type of class 2.33 ± 6.50 0.722
Q: Do advanced students perform better than beginner students on the summative assessment, regardless of treatment?
A: Yes. Advanced students perform better on the summative assessment regardless of which module version they used (workbook or tutorial)
Score ~ Type of class
Fixed predictor Estimate ± SE p value
Intercept 66.79 ± 1.97 < 0.0001
Type of class (advanced) 6.44 ± 3.13 < 0.05
  1. All models include random factors for class (level 2) to account for the nesting of students in classes (2605 students within 38 classes). Full model taxonomy can be found in Additional file 1: Table S12