Technology, Data, and Privilege in College Admissions

The college admissions landscape has shifted from a purely human evaluation to a highly digitized, data-driven system. Understanding how institutions collect, analyze, and use applicant data is essential for anyone navigating the modern path to higher education. This course demystifies the technical side of admissions, revealing how predictive analytics and enrollment management software impact applicant selection. You will gain a clear-eyed perspective on how technological tools can reinforce privilege, and learn how to interpret the digital footprint required of modern applicants. What you'll learn: - Understand the foundational concepts of enrollment management and predictive modeling in admissions. - Analyze how institutional data tracking and behavioral analytics influence selection decisions. - Examine the role of automated screening systems and AI-driven tools in evaluating applicant materials. - Evaluate the ethical implications of using historical data and machine learning to predict student success. - Identify strategies to navigate digital-first admissions processes and protect applicant data privacy. You will start with key terminology and the history of data in higher education before moving into practical analyses of modern recruitment algorithms and digital equity challenges. This text-based course is designed for beginners, prospective students, parents, and educators who want to understand the modern, tech-driven admissions landscape with no prior technical background required. Begin reading to uncover the hidden algorithms shaping college access today.