The best statistical instrument (in my humble oppinion) is SPSS (commercial, expansive - often available as campus licence, needs some time to learn): To run sophisticated data proces and analyses you may take R (yes - it's only R - it's free to use but needs some learning time).
SPSS is excellent but its use depends on the type of data which determines the type of test. Is the data for example parametric or non- parametric ie real numbers or numbers representing sequences or trends or attitudinal scales. I think to get a specific answer you will need to describe your data in more detail. Dave
collaborative learning style? by survey, experimental, quasi-experimental......method? how many students? if quantitative research, how many tests? Plz clarify more 2 get better responsessss
It is vital to provide information regarding your methodology. What are the variables that you are assessing? Are you comparing two or more groups of participants with the different learning styles? Or do you have two or more groups with similar learning styles but differentiated by other descriptive variables. Do you have moderating or mediating variables in the research model? Only when you give clear answers to the above questions can a statistician advise you what statistical procedure(s) to employ to analyze your data. I agree that usually SPSS is the most suitable software to use but you need to decide on the most suitable procedures offered in the SPSS package.
In that case, use the SPSS or SAS statistical software pakages. Choose the ANOVA or MANOVA procedures. There procedures will determine if there are statistically significant variances (differences) between the two or more groups characterized by different learning styles. If you have three or more groups the you would need to use an additional post hoc test such as Duncan, Scheffe or Bonferroni to ascertain between which of the three or more groups the differences are statistically significant (between group A and group B; between group A and group C; between group B and group C and so on).
Haftamu, What is the nature of your data to effect a comparison between these two or more groups. Is it raw numerical, is it numerical but with numbers representing qualitative data or is it pure qualitative data? If you have conducted surveys and have attitudinal scales, you can convert this to numerical data, although the numbers here won't be real numbers and so you test will be different. Still more needs to be clarified? Dave
I would recommend using SPSS, which is a very powerful tool for statistical analyses that will cover your research in most cases. It is also relatively easy to use and has a vast array of YouTube tutorials to walk you through running varied tests as needed.
I recommend epistemic network analysis. See http://epistemicnetwork.org for more details. Also a good paper at https://www.academia.edu/attachments/46651623/download_file?st=MTQ2NjQ0NDAyMiw3Mi4zMy4yLjIxLDM2ODMwNjA%3D&s=profile
I would recommend using Atlas.ti to build connections among for qualitative data and tests in SPSS for quantitative data. In case of having anlarge set of qualitative data, I would use Padilla's unfolding matrix to frame the data before analysis.
In case you got some funds, it is possible to hire professional data analyst for that part. Then you do your part of findings and other steps.
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