Kindly specify why you are doing cluster analysis. I assume that your data consists of demographic items combined with some attitude study. As a starting point you can use k means clustering. If you have data with respect to attitude towards an idea, product or service etc you can cluster them in to groups. (You can specify the number of groups). For example we may have data with respect to attitude of customers towards branded apparels with different variables rated on a Likret Scale. Your data can be analysed using the k means clustering so that you can have three groups. You have to examine the output and find the characteristics and make a decision on naming each of the groups. The simple way to do is to examine the magnitude and name them as high, medium and low. I have over simplified the concept. However, if it provides some idea for you, it is fine. Please get the latest edition of Multivariate Analysis by Hair et al. You will have good grasp of the subject.
My respondents were 710 of school librarians, their qualifications and also self-report of their information literacy skills. I am looking into if it is possible for me to group them into groups based on whether they are ready (readiness) for information literacy implementation in schools.
Yes, I will look into Multivariate Analysis by Hair et al.