Approximately 120 college campuses across the United States are testing a new artificial intelligence tool, CourseWise, which aims to clarify and standardize transfer course equivalencies, a significant point of contention for students and administrators alike. Daniel Knox, director of the Center for Data & Analytics at the National Association of Higher Education Systems (NASH), noted that current evaluation practices vary widely from one institution to another and are often not systematically tracked. The introduction of CourseWise seeks to alleviate this friction by offering a more streamlined process for evaluating transfer credits.
Developed by the University of California, Berkeley’s lab focused on Computational Approaches to Human Learning (CAHL), CourseWise utilizes AI to learn from past transfer credit decisions made by various institutions. By recommending which courses from one college align with those at another, the tool allows administrators to approve or deny these suggestions, ultimately reducing the time spent sifting through extensive course catalogs.
Heather Adams, a transfer consultant at higher education consulting firm Sova Solutions, described the current landscape of higher education data as “a hot mess,” with institutions organizing, collecting, and defining data inconsistently. She emphasized that very few institutions are even tracking transfer data. CourseWise Chief Operating Officer Angikaar Singh Chana highlighted the challenges posed by disparate data formats, including physical course catalogs, student transcripts in unreadable PDFs, and past course equivalency decisions recorded in varied Excel formats. The goal of CourseWise is to unify this data, presenting it in one screen with simplified suggestions.
The process of course articulation—the evaluation of whether two courses are equivalent—can often be subjective. For instance, Texas A&M University mandates that students take a course on Texas government, but the determination of whether a similar course from another institution meets this requirement may depend on individual faculty opinions. Isaiah Vance, Assistant Vice Chancellor for Advising at Texas A&M, pointed out that while the content might vary, the overarching principles of how state governments function are often similar across states.
Course articulation is not only time-consuming for faculty and staff but also frustrating for students, who frequently encounter difficulties navigating the transfer process. A report by the U.S. Government Accountability Office indicated that students transferring between institutions lost, on average, 43 percent of previously earned credits during the transfer process from 2004 to 2009, underscoring the immediate need for solutions like CourseWise.
CourseWise is informed by over a decade of research at the CAHL lab on how users interact with AI-generated course recommendations, making it distinct from other educational technology tools. Zachary Pardos, the lead researcher at UC Berkeley and the creator of the tool, initially designed models using millions of existing equivalencies and enrollment records from the SUNY system. Early iterations yielded an average of 10 to 12 suggested course equivalencies, though some matched poorly. Vance recalled instances where unrelated courses, such as physics and carpentry, were suggested as equivalents.
Currently, CourseWise provides one primary recommendation for each course taken at a previous institution, significantly refining its suggestions through validation testing on SUNY data. “That was what the algorithm needed to get the accuracy on par with human mappings,” Knox noted. For institutions to utilize CourseWise, they must upload their own articulation histories and course information. Chana assists schools in organizing their data to ensure compatibility with the platform, which also offers guidance on standardization practices for articulation data.
As three of Texas A&M’s 12 universities prepare to transition from the input phase to testing CourseWise, Vance remarked on the potential for the tool to reduce duplicated efforts among the numerous public universities in Texas. “If each of them are reviewing courses independently, that is a lot of wasted resources,” he explained.
Looking ahead, CourseWise developers plan to enhance its features, including expanding the types of data schools can input and creating a student-facing tool to aid in degree planning. Pardos emphasized the importance of addressing the transitional process between advising and admissions, suggesting that a comprehensive planning tool could follow students to their new institutions, reinforcing adherence to degree requirements.
Those involved in testing CourseWise see broader implications for the tool beyond individual institution needs. Vance pointed out that data derived from CourseWise could yield insights into students’ academic pathways and highlight trends in course enrollment. Additionally, there is potential to expand reciprocal transfer agreements, facilitating the flow of credits not just from two-year to four-year institutions but also how university credits may transfer to community colleges. By simplifying the student experience, CourseWise could positively impact enrollment trends in higher education, as Knox noted that speeding up processes around admissions and credit evaluations has shown to increase enrollment rates. “We’ve taken processes that would take on average 45 days and got it down to 48 or 72 hours, and we see enrollments go up,” he said.
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