I have data on 26 participants (13 from computing and remaining 13 from non computing) who have participated in my research. Each participant is treated with a lab module (Hands on Robotics Session). Now each participant will be evaluated using a rubric on scale of 1 to 4. This experiment has both pre and post test.
For my research i want to evaluate the following questions:
Research question 1
- Null Hypothesis: students do not learn about computational thinking (programming basics and algorithmic thinking) with the help of robotics.
- Alternate Hypothesis: Students learn about computational thinking (programming basics and algorithmic thinking) with the help of robotics.
To evaluate the above question, the categories i will be considering are Plan, Implementation and Knowledge gained on a scale of Excellent, Good, Fair and Poor.
I think i should use DEPENDENT T-TEST FOR PAIRED SAMPLES. Am i correct?
Research question 2:
- Null Hypothesis: Participants background (computing and non computing) has no effect in learning about algorithmic thinking with help of robotics
- Alternate Hypothesis:Participants background (computing and non computing) has an effect in learning about algorithmic thinking with help of robotics
I will also evaluate question 2 on a scale of Excellent, Good, Fair and Poor, but with respect to background.
My Statistical Question
Which T test should I use for each of my research questions?
Best Answer
Since you are interested in measuring an increase pre- and post-test, it seems to me that you should use a paired test.
An issue here is that your variables are likely non Gaussian since they are among 4 categories. If your sample size is big (very roughly larger than 50), then it is no big deal. Otherwise, I would use the Wilcoxon signed rank test which is a non parametric analog of the paired t-test.