Suppose that you have collected data throughout a semester from a large elementa

Question

Suppose that you have collected data throughout a semester from a large elementary school regarding the number of days per week each math teacher spends in a collaborative teaching community. The average ranges from 0 to 7 days per week. You have also obtained the pre-test and post-test scores in math administered in those same classrooms in the beginning and end of the semester, and you have calculated a score that shows learning during the semester by subtracting the pre-test score from the post-test score for each student.

You are interested in examining any potential differences in student learning (i.e., post-test minus pre-test) that may be due to the number of days of teacher participation in a collaborative community. Is group comparison the best approach to analyze the available data? Why or why not?

Explanation / Answer

Here we have obtained the pre-test and post-test scores in math administered in classrooms in the beginning and end of the semester, and we have calculated a score that shows learning during the semester by subtracting the pre-test score from the post-test scores for each student.

Now we are interested in examining any potential differences in student learning that may be due to the number of days of teacher participation in a collaborative community.

So here we have dependent samples and from there we get a single sample which is the difference between the pre-test score and the post test score.

No, group comparison is not the best approach to analyze the available data.

In this case group comparison cannot answer our research questions as we are interested to check whether there is differences for the same set of student learning that may be due to the number of days of teacher participation in a collaborative community.

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