Advancing a field of research isn’t always about gathering new data—sometimes progress is rooted in the systems that support analysis. Jordan Harshman is a member of EDU-STEM who is using his background in coding to push education research forward in exciting and innovative ways.

Jordan is an assistant professor at Auburn University wrapping up his third year on the job. In that short time he’s already established his own lab that focuses on doctoral level chemistry education. His specialization in chemistry gives him a unique view among other EDU-STEM partners, helping to broaden the network’s reach across STEM disciplines.

From the beginning, Jordan knew that he wanted to be a teacher, and while chemistry was a subject he always had a talent and passion for, his first love was music. For a time he intended to pursue teaching music, but being unable to play piano made that route difficult. Ultimately, this led him to choose a path in science, and later on begin researching STEM education. Born and raised in Wisconsin near the Minnesota border, Jordan considers himself a Northerner at heart. Now based in Alabama, he recently became a father—his first child was born just six months ago. While the mix of child care and teaching keeps him busy, he still finds some time for his hobbies. He enjoys gaming, and has even built PCs in the past. Jordan is also a self-taught coder, specializing in the R programming language—a skill set that would be at the center of his contribution to the EDU-STEM network: BUDDIE.

The Biology URM Diversity Data Interactive Explorer, or BUDDIE for short, is a program that facilitates the graphing and comparisons of data. The basic process is simple: BUDDIE is loaded with a large data set, the user selects the variables they’d like to examine, and then BUDDIE creates the best suited graph - be it a heat map, a line graph, or one of many other formats. The graph is then immediately available for both download and sharing, making BUDDIE’s analyses easily transferable to publications, presentations, or even just emails. The program allows users to compare data on axes of identity as well; After a graph is generated, the user can select the results to be grouped by factors like gender or ethnicity and BUDDIE will create a side by side display of the results. Survey answers from inventories that measure concepts like confidence and self-advocacy are present as groups within the program as well.

The psychometrics that underlie many of the concept inventory data points work best when examined in a group, but at the current time, BUDDIE allows users to select results for specific inventory questions. In the future Jordan hopes to group these into subscores instead. Subscores are averages of inventories that take groups of questions which all focus on the same theme and are statistically proven to be related. A set of questions within a subscore might measure students’ confidence with scientific topics, for instance.

Whether the focus of a study is qualitative or quantitative, researchers tend to release aggregate data and graphs rather than raw data. BUDDIE will allow researchers within the network to easily upload entire raw data sets that will be combined with every other network partner’s data—creating a large collaborative pool for everyone to draw from. “No one researcher can look at all of [EDU-STEM’s data] and try to digest all of it - BUDDIE is a resource to both crowd source analysis as well as provide people access to the aggregated data itself,” said Jordan.

Indeed, access to the full EDU-STEM data set is a complex problem. While the network has the means and potential to create a pool of data with incredible depth, variety, and reach, it can’t just be open and available to anyone. Though efforts are always taken to de-identify personal data, there are still privacy issues. On top of those concerns, public access to data sets that focus on BIPOC or other minority student populations have the potential to be used to serve harmful agendas. There’s always a way to make things look negative, especially when numbers are taken out of context. Having a tool like BUDDIE allows for a safe and streamlined means of sharing data throughout the network while still keeping it in a contained group.

In order for the tool to work though, the group must make consistency a priority—BUDDIE can only function correctly when the data it’s loaded with fits one tight standard. This makes maintaining standard procedures throughout the network extremely important. “Consistency is the key.” Jordan said. “The second that University A modifies the survey—even just a little bit—you can’t combine it with other people’s data anymore.” Efforts are already being taken to make sure every researcher within the network has the tools and ability to keep things consistent.

BUDDIE’s development is coming to an end, but before it launches Jordan intends to ask the wider EDU-STEM network what other features they’d like added to the system. BUDDIE will be a game-changer when it releases. Jordan’s hard work is already pushing the network forward and keeping us trending toward success.