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Model 1 differentiates between the pretests and posttests for the two assessment condition (CBT and PPT).
Sophisticated technologies (e.g., Javascript and multimedia elements) were excluded from our assessment to provide an optimal assessment condition.
None of the assessment condition coefficients were statistically significantly different from zero on either the pretest or posttest.
How does assessment condition (PPT vs CBT) impact student performance on low-stakes RBAs, if at all?
All of the differences between CBTs and PPTs were small, none of the differences were statistically significant, and neither assessment condition was consistently higher than the other.
The final performance model included RBA score as the outcome variable and predictor variables for posttest (level 1), assessment condition (level 2), and course (level 3) (Eq. 3).
Similar(38)
NEPS Reading (including Reading Speed in certain assessment conditions; paper-based only).
Their investigation found no meaningful differences in performance between the three assessment conditions.
These results indicate that the data collection in these courses disproportionately represented higher achieving students in both assessment conditions.
Chuah et al. (2006) examined the impact of assessment conditions on student performance on a low-stakes personality test.
However, these demographic variables had no effect on the impact of assessment conditions on student performance in our models.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com