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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