Purpose: Since creating an information commons a couple years ago, this library’s research team has been coordinating data gathering methods with the writing center. With both units using standard check-in procedures at a shared desk and hosting in-depth consultations in a shared space, it made sense to share technologies. Since Spring 2015, we have logged students for research consultations with software that is commonly used by writing centers, tutoring and other academic support units. We are not only able to count the number of consultations, but we are also able to record cross-referrals with the writing center, calculate average consultation session lengths, and more.
As we began reviewing research consultation data, we saw information that could not only help the research team and the information commons, but it could help inform our library instruction efforts, particularly outreach. We see opportunity in moving from anecdotal evidence that classes were coming in for research support to documenting exactly which classes were coming in for research support. We were curious in knowing which research consultations could be classified as follow-ups from an instruction session. We likewise wanted to know which courses were driving students to a research consultation, whether as an instruction session follow-up or in cases where no instruction had been provided. The consultation data could help us answer these questions and help us develop a proactive outreach model.
This data, along with instruction data for comparison, will provide a basis for developing faculty outreach opportunities, whether for instruction or facilitating greater use of our writing and research consulting services.
Design/Methodology/Approach: Both research consultation data and instruction data will be analyzed. The research consultation data, which will ultimately include three semesters, contains information relating to semester, meeting date, department and course number, and instructor. We have culled instruction data for the last four semesters, with the same data fields as the research consultation data. By comparing the two files, we can ascertain whether research consultations occurred after an instruction session or, more tellingly, where the absence of any instruction sent the student for research help.
Potential Findings: We anticipate that the data will help us identify potential courses that might benefit from librarian collaboration, whether it is instruction, additional material support, or expanded use of services in our information commons. The initial findings would help us develop an outreach plan targeted at faculty with the ultimate goal of facilitating student learning.
Practical Implications: Although not without controversy, using standardized swipe data helps create a uniform set of data files that can be analyzed by the units housed in the information commons. By using data collected from one service point to help analyze the work of a related library service, we will be able to determine relevant campus constituents for a targeted, proactive outreach plan. Session attendees will be able to consider the implications and utility for this method at their own institutions.
Available at: http://works.bepress.com/hector_escobar/6/