Reflection - Methodology

My methods are constructed well, but I am catching up and trying not to rush. It has been challenging with both courses having due dates of significant work around the same time, but we are in a doctoral program, so one must balance time appropriately. One of the factors of my research study is dealing with secondary data. It's critical to fully understand the format and content of the Integrated Postsecondary Education Data System (IPEDS) dataset before finalizing my methodology and collecting data. To do this, I need to learn about the available variables, what they mean, and any limits or constraints that come with the data. I must also find the critical variables in the IPEDS dataset related to the study's research questions. I determined that my approach to the case analysis uses a multiple-case analysis approach. By looking at different institutions, you can find similarities, differences, and environmental factors that affect how well you teach and understand facts. One of the things that was missing from my slides was what variable constructs I would use. The IPED datasets provide so much information that narrowing down your research questions and study goals is essential. I have some variables selected, but they need to be finalized so I know exactly what data I am extracting. Once I choose the necessary variables, I can create the codebook to familiarize myself with the variables and dataset I will use for the study.

Also, I am using a mixed-method approach because a mixed-methods study uses qualitative and quantitative methods to gather and analyze data. This method combines the best parts of both techniques to help you get the complete picture. I will use quantitative analysis methods to look at how institutional variables affect results related to data literacy and teaching methods. It could use other statistical techniques like association analysis, regression modeling, descriptive statistics, or both. Even though I am using secondary data, there are so many components to the large datasets. I got excited when I selected the University of North Texas – Denton location. Its ID is 227216, and the University of Texas in Austin's ID is 228778. You can also select multiple institutions from the IPEDS datasets.

The collected data include institutional characteristics, admissions, enrollment, degrees and certificates, student persistence and success, financial aid, and institutional resources. For analysis, IPEDS variables can be used to group institutions meaningfully, such as community schools and flagship universities. There are several training modules to help you navigate through the datasets. I need to improve and be more decisive on whether the variables align with the research questions and the study's goals. I need to also decide on my sampling size and procedure. The sample size and selection criteria are a part of that sampling procedure. There is always room for improvement; the best research method is not to rush because you will miss something. Ensure you outline with a plan of action so you are carefully getting all the details so the data you are analyzing is credible and reliable. Another improvement is logically aligning with your research investigation's theoretical framework and aim. If you work with secondary material, you need to clean and prepare it first. Please clean up any errors, missing numbers, or inconsistencies in the data. As required, preprocess the data to ensure the factors are compatible and consistent.