AI & Data Science

Integrating AI Into the College Admissions Process

May 8, 2024

Artificial intelligence and machine learning have only just begun to revolutionize the landscape of graduate admissions. As the future rapidly unfolds, the heart of this transformation will continue to lie in the evaluation of candidates, where the concept of holistic college admissions plays a pivotal role.

Institutions embracing emergent technologies and strategies can now use data to align their holistic approach with their overarching mission and the specific objectives of individual programs. By defining the qualities and experiences they’re looking for in students, schools and programs can identify the demographic and behavioral characteristics most in sync with their objectives.

For example, factors like grit and empathy, though challenging to quantify, are now navigable through the mapping of institutional and programmatic missions to specific variables, allowing machines to optimize the composition of diverse student cohorts. The emphasis on individual uniqueness ensures that while certain criteria must be met, the admissions process avoids creating a homogeneous student body.

Navigating the integration of AI into college admissions comes down to focusing on three key pillars: skill set, technology, and data. For an institution to be positioned favorably in the AI-driven admissions landscape, it must cultivate a skill set that is adept at handling the complexities of data and technology. At the user level, there must be at least a basic understanding of the concepts of probabilities and prescriptions and a familiarity with machine learning.

Moving beyond traditional statistical methods by developing nonlinear models allows for a more nuanced understanding of individuals. However, the quality and accessibility of data — and the persistent gap in understanding how to collect and maintain data effectively — present critical challenges, including the potential to create bias.

The solution to detecting and addressing bias lies in the responsible application of data science. Once bias is detected, programs should be configured to counteract and rectify it. This iterative process of detection, responsible application, and continuous refinement ensures that AI systems evolve to align with ethical considerations, promoting fairness and inclusivity in the admissions process.

AI integration in education, such as in the evaluation of traditional academic metrics in graduate admissions, offers a new pathway to address inherent challenges and biases associated with simplistic metrics such as test scores or undergraduate GPAs. Those metrics have indications tied to success, but they also carry biases, such as favoring applicants who are in a socioeconomic bracket that allows them to get tutoring for improved test scores.

The AI paradigm shift involves reweighting the attributes that an institution or program wants its applicants and students to possess. It requires adopting a holistic approach that transcends conventional indicators and recognizes diverse forms of excellence. The focus shifts toward developing an understanding of students’ unique personal qualities and then identifying those “diamonds in the rough.”

By consciously tipping the scales in favor of these desired qualities, institutions can counteract biases and foster diversity. In addition to impacting the composition of graduate programs, this intentional approach can positively impact society by improving the future economic mobility of admitted students.

For resource-constrained graduate programs, leveraging AI is a strategic opportunity. Better intelligence allows institutions to pool resources and gain insights into the specific needs of a program, enhancing the ability to identify and support a diverse group of candidates — and reap the benefits of a diverse student body. In this way, AI has the potential to reshape admissions processes and foster inclusivity.


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Over the last three decades, Liaison has helped over 40,000 programs on more than 1,200 campuses more effectively manage admissions through its Centralized Application Service (CAS™) technology and complementary application processing and support services. The higher education technology leader supports its partner institutions’ total enrollment goals by pairing CAS with its Enrollment Marketing (EM) platform as well as the recently acquired TargetX (CRM) and advanced analytics software Othot.