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A new study from Tyton Partners suggests supporting academic advisers with generative AI to reduce the burden of heavy caseloads.
Abdullah Drmaz/iStock/Getty Images
Academic advisers are at the forefront of student success work, helping guide learners through their academic programs and often connecting them with other campus resources. Growing demands for personalized guidance, advisers reporting high caseloads and retention of staff are some of the greatest challenges in the field today, according to new data from Tyton Partners.
Driving Toward a Degree—an annual longitudinal study from the consulting group, which focuses on holistic student supports through survey data—has historically reported that high caseloads (43 percent), a lack of coordination among institutional departments (36 percent) and low student engagement with resources (33 percent) impact the work of support staff.
This year, adviser burnout and turnover gained prominence, with 37 percent of respondents ranking it as top issue, nine percentage points higher than the year prior.
To address these concerns, Tyton researchers recommend implementing generative artificial intelligence tools into course registration to improve advising capacity and reduce the burden of transactional course selection and scheduling processes.
Methodology
Tyton’s report is based on a survey of over 3,000 higher education stakeholders. Respondents included approximately 1,000 four-year students, 530 community college students, 1,300 academic advisers and support professionals, and 300 administrators.
What’s the need: Tyton’s survey found, among advisers, helping students select courses or a plan of study was the top daily activity, with 95 percent of academic advisers and 59 percent of faculty advisers selecting this option.
The majority of students, however, are confident that they can select their own classes each term without help from an adviser. Over half of first-year students believe they could select the right courses each term, and 60 percent of students beyond their first year agree with this, as well.
Implementing generative AI for academic planning “can potentially save advising meeting time spent on the technical aspects of course registration, enabling more holistic advising conversations,” according to the report.
When asked if they would prefer to interact with campus professionals or automated or generative AI services, most students preferred engaging with technology for course registration (2.79 out of 5), academic advising (2.66), financial aid (2.65) and career advising (2.71).
Technology should not replace advisers, researchers write, because students will still need support from advisers and counselors to leverage tools accurately and efficiently, but these tools can augment capacity of limited personnel resources.
The Bigger Picture
While Tyton’s report places special emphasis on generative artificial intelligence and the role technology plays in addressing personnel concerns, the greatest detriment to retention and support for staff was large caseloads, which can be tackled in other ways. Some of Tyton’s suggested strategies included:
- Partnering across campus for specific tasks to prioritize personalized support for students, such as student success coaches and career services.
- Prioritizing proactive outreach to students to assist those who may be struggling.
- Investing in professional development and strategic onboarding to reduce adviser turnover and build support for existing staff.
AI in action: Generative AI may have the power to improve capacities for front-line advisers, but there is still an awareness gap among higher education stakeholders that needs to be addressed before deploying technology.
Among front-line student support providers, only 25 percent of respondents used AI at least monthly, compared to 59 percent of students. Almost half (49 percent) of staff said they hadn’t used generative AI tools or weren’t familiar with them.
At the institutional level, only 18 percent of staff said their institution provided training for generative AI use, and 17 percent said their campus introduced policies around generative AI usage for support staff.
Since the release of ChatGPT in November 2022, more higher education institutions have adopted generative AI technology into their procedures. Much of this work has been focused in the classroom, with individual instructors co-opting tech to improve learning, but colleges and universities are also integrating services to supplement or support existing work in counseling, advising and more.
Around half of college presidents say they’re optimistic about artificial intelligence’s growing impact on higher education, according to Inside Higher Ed’s 2024 Presidents Survey, conducted by Hanover.
About one-third of respondents agree their institution is prepared to handle the rise of AI, as well. Most institutions are considering AI for virtual chat assistants or chat bots; only 16 percent of public college presidents and 9 percent of private college presidents said their institutions are considering it for student advising and support.
Research from EAB earlier this summer found a majority of surveyed student support staff believe AI could be used to identify at-risk students (58 percent) or nudge students (54 percent), and around one third see opportunity for AI to recommend academic pathways and courses (30 percent).
Applications: Based on the survey findings, Tyton’s report recommends:
- Leaders audit and enhance data quality to unlock generative AI’s potential. Incomplete, inaccurate or biased data can impact AI’s ability to provide accurate content as well as reduce the quality of output. Having better quality data will improve the campus community’s trust in the tech as well. Leaders should audit student data for completeness, standardize terminology and establish consistent units to prepare for future information access needs.
- Staff engage with generative AI tools. Many front-line support personnel have a lack of trust and familiarity with generative AI, so promoting increased exposure to and clarity around these tools can address some hesitancy. When asked what elements are top priorities for generative AI activities for student success, staff ranked training (39 percent) and student-facing tools (30 percent) as most important over internal-facing tools (25 percent).
