Recommendations for Hart Banach

1. We discussed several designs in class, but not all designs answer the same research question. It is important to clearly define your research question so that the right design can be selected. For instance, if you hope to prove that curriculums built around students’ funds of knowledge improve their ability to learn (measured by some quantitative factor), then the design where all participants partake in a program seems fitting.

2. It may be useful to consider quantitative measures that you could reasonably expect to see a difference in between the treatment and control groups. The larger the expected difference, the greater the statistical power of your analysis. Since you mentioned that your sample size is relatively fixed around 40 students, choosing a metric that will reflect a difference between the two groups is important.

1. Since the study lasts for quite a long time, quite a few subjects might quit from the study. Please keep a detailed record about the reason why they intend to quit, since these information plays an important role in our statistical analysis of missing data.

2. As we know, for general treatment and control study, the subjects themselves have no idea of which group they are divided into, just as we have come across in acupuncture study. For this study, the researcher seems to pay little attention to this point. In my opinion, this design might lead to some bias, which means difference produced by other factors, rather than treatment and control.

1. As the main objective of the study is to make some necessary steps in the policy implementation, so I think, it would be better to take more schools in different areas rather than one (stratified sampling).

2. The subjects should be selected using probability sampling procedure not subjective sampling.