EDFS 355
Data Based Decision Making
(Summer 2019)
Data Based Decision Making
(Summer 2019)
EDFS 355, Data Based Decision Making, was taught by Professor Tammy Kolbe. This rigorous course included multiple data analysis assignments, as well as a comprehensive overview of the data inquiry process. In data analysis assignments, students analyzed large, hypothetical student data sets and data taken from our own work environments. The variety of content presented created a quick-moving, thought-provoking course.
The class content was jump started with content surrounding identifying and collecting data, leading an inquiry process and an overview of statistics. Statistics used in the class included measures of center (mean, median, mode), measures of data spread (range, minimum, maximum, interquartile range), measures of variance and measures of statistic significance. Professor Tammy Kolbe led the class through different ways to describe data (including variability and frequency). We then learned how best to create cross-tabulations of data, and research-based strategies for presenting data in a clear and consistent manner. As organizational leaders, we were consistently asked to ponder how best to present certain findings or data sets, and how to facilitate an inquiry process. It was important for us to continually frame our learning in our organization's needs, and there was space for us to shape our learning to bolster our team's strengths and smooth out weaknesses.
As the content became more complex, we were given the opportunity to apply our knowledge to our own organizational data. For the final project and final examination, we were asked to build an inquiry process for our professional team to potentially utilize around a question- answered by organizational data. This project and final presentation was a challenge, for we were both synthesizing our learning from the course, and being asked to apply it in our own professional setting.