Researching Education

Considering Newer Research Methodologies Presently most researchers will consider themselves in one preset methodologies set forth decades ago in the mid 2000s. These are usually divided into qualitative, quantitative, or mixed methods.  This is fine and good, and allows researchers to fall back on traditions that have been years in the making. This is how we expand precedent and appeal to previous logic to ground the case that our data collection is sound. However, what about making the case that that it is time for new methodologies more intersectional than mixed? Can we add richness to research methodologies and take on some of the emerging issues in education when we invite transdisciplinary involvement with research data? One methodology that I have considered recently is traversing qualitative research with content analysis, and digital humanities methods. I argued that starting from the archive, staging, and preliminary analysis, borrowing from data science, gives researchers co

  In the realm of institutional effectiveness, it is often necessary to batch process the hours earned and gpas of both the content area and cumulative area for undergraduates that are applying for particular majors in certain programs of study. Such calculations involve many students applying at one time for majors. Therefore, one can either calculate tens to hundreds of students at a time or automate the process. To ease the process through automation, I have created a function in R called 'bulkgpa' in the 'coogs' package, available to the institutional effectiveness community at the College of Education at the University of Houston.  The function is a hard worker. It takes three raw files directly from peoplesoft queries and cleanses them by eliminating unneeded columns, duplicated rows, and eliminates classes that have drop dates associated with them.  Argument slots are created for raw data excel spreadsheets including transfer classes, transfer hours, UH course