Key points:
- Defining the relationship between student affairs and AI can help guide data policies
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- How AI impacts IT-based connectivity on the phygital campus
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“We have this information. Can we please do something with it?” These words from a student affairs (SA) administrator are no surprise to those in the field of higher education. For all the wonderful (or not so wonderful) insights we glean from our students and colleagues, we often have little to show for it. Information sits unusable in databases–usually more than one–and, even though new technologies arise, we remain under-informed.
To explore concepts of data collection, use, and applications of artificial intelligence (AI) within higher education, our team conducted 26 semi-structured interviews with student affairs professionals at our institution. In these conversations, we encountered hesitancy and a lack of awareness around the integration of cutting-edge technologies into the workflow. That said, we also found an abundance of curiosity and willingness to use AI to add to the work of student affairs.
As we continue to learn about data usage and technologies powered by artificial intelligence, let’s unpack a few questions that SA staff have on this topic.
How usable is our data and where can we apply it?
Colleagues within the same institution should realistically all have access to the same information, but our interviewees described how departments create their own workarounds for otherwise clunky data management systems. There are significant data pools at our disposal, but we either do not have access to everything we need, the data is messy, or we don’t know what other departments have. Our interviewees frequently pointed out how existing and outdated systems don’t have interconnectivity. Silo-ing of data adds barriers to information that could help establish new programs, eliminate duplication, or provide students with necessary support. Additionally, using databases with varied input styles means multiple formats and mismatched information. This alone makes data cleaning and usage complicated; it also puts student affairs professionals at a disadvantage, even if the desired information technically exists.
As student affairs professionals, we know we have the data–the question is whether we can use it to guide our work. While there is still much to be learned about advanced technologies, we know that we need to have reliable data to put into the system. This makes using generative AI or similar technologies extremely difficult: see the garbage in, garbage out principle. Student affairs staff in higher ed spaces are knowledgeable, but expecting entire departments to piece together disparate data is an unrealistic expectation for staff that are already overworked.
What restrictions on data and AI use exist in higher education and how can we learn more about them?
As we observed in our interviews, these powerful technologies can be intimidating. When exploring and playing with new tech as student affairs folks, we want to know two things: 1) the features of the platform; and 2) the guidelines to best protect our students, our institutions, and ourselves. What do we need to be aware of when we screen novel technologies? Here we turn to our expert colleagues, IT departments, and university leaders to show the way. Further, one interviewee also raised concerns about the Family Educational Rights & Privacy Act (FERPA) and General Data Protection Regulation (GDPR), as they can have a major impact on how we’re storing data and how we’re allowed to use it. Understanding the limitations imposed by these policies should be top of mind, especially when assessing tech tools.
Perhaps most important, though, is who we can ask for help about these topics. Are there AI/new technology committees or advisors that can help us navigate this arena? Are they internal, or are there external professional organizations that we should be aware of? These considerations are fundamental before we start plugging institutional data into unfamiliar systems.
How do we make the most of cutting-edge tools in the student affairs space?
Once we understand what we have and how we’re able to use it, we want to know how to leverage advanced tools to make the most impact at our universities. Where can we find advanced learning or professional development opportunities? If we have questions about prompt generation, for example, there isn’t currently a clear to-do list of training. On the backend of advanced technologies, should SA professionals be prepared to help train new models or validate output for ones in development? Given these systems could have an impact on student affairs, we would argue yes.
Finally, given that higher education is an industry built on relationships and mentorship, how do we ensure a human remains in the equation? While there is certainly benefit to using tools powered by generative AI, we have to be aware of what information we choose to use and how we do so. Our interviews confirmed that the institution has started these conversations at a high level, but have not yet involved a significant number of staff voices.
Why worry about data and advanced technology as student affairs staff?
With the right data and engagement, AI could serve as a means of collaboration across constituency lines in higher education, becoming a tool for collaboration, a bridge, a way to connect and make sense of an increasingly complex world. There has been much research on how generative AI can be leveraged in classroom settings –including as a mode of evaluation or steward of personalized tutoring –but the vast amounts of data and range of tasks that exist in student affairs makes it a ripe place for implementation. Defining the relationship between student affairs and AI can touch on topics from data collection practices and basic data training, to broader concerns around student affairs burnout and encouraging development of meaningful relationships.
Student affairs professionals are growing increasingly powerful within our colleges and universities. If we want them to be best prepared to guide students and complement the curricular experience, we need to answer the questions above–for each institution, and the industry as a whole.
Meghan Plate, MA, is the assistant director of Education in the UR Health Lab, an innovation incubator within the University of Rochester Medical Center. She also serves on the board of TechRochester, and her research interests include higher education administration, transdisciplinary research/projects, and how tech plays into various aspects of education.
Andrea Barrett, EdD, is an assistant professor and co-chair of the Educational Leadership department at the University of Rochester’s Warner School of Education. Her teaching and research interests include contemporary issues in higher education, leadership and management in higher education, and the impact of technology on student affairs professionals’ work.
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