Data Informed Decision Making in Higher Education ((3 Credits))

Catalog description

Increasingly sophisticated methods and technology that include the capability to collect and store large volumes of data has ushered in a new era of data-informed decision making in higher education. Data analytics is the use of large volumes of data that can be combined or analyzed, often with the use of complex statistical/mathematical models to examine a problem or issue under study. Related to student success and administrative decision making, data analytics can be used to better understand current student, faculty, and staff populations as well as if, how, and in what ways students, faculty, or institutions are achieving success. This course will examine issues related to the increasing use of data in highereducation and how higher education leaders can harness the power of data to ask the right questions that enable better decision making. The course will help students become familiar with definitions of major terms such as Big Data, artificial intelligence, machine learning, and it will discuss the ethical, cultural, and managerial implications for the use of data analytics in higher education decision making. Topics will be discussed broadly and will not include hands-on use of statistics or the generation of computer code. An applied project will be proposed.