Data-informed decision-making is no longer an optional or occasional practice, as higher education professionals now routinely respond to calls for accountability by providing data to show how their work impacts students. Institutions are operating with a culture that, at a minimum, includes the use of descriptive and diagnostic analyses to assess…

We propose a cognitive-psychological model of linguistic intuitions about copredication statements. In copredication statements, like "The book is heavy and informative," the nominal denotes two ontologically distinct entities at the same time. This has been considered a problem for standard truth-conditional semantics. In this paper, we…

In this chapter, we walk the reader through a set of scenarios that administrators might face when using different types of data on campus. We also provide guiding questions to help institutional research professionals explore how to think about these scenarios with ethics in mind.

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…

Student success, both during and after college, is central to the mission of higher education. Within the higher-education and, more specifically, the student-success context, the core raison d'être of machine learning (ML) is to help institutions achieve their social mission in an efficient and effective manner. While there should be synergy…

As institutions seek to shift into more advanced analytics and data-based decision-support, many institutional research offices face the challenge of meeting the office's current demands while taking on more intricate and specialized work to support decision-making. Given the great need organizations have for information that supports real-time…

The newsvendor problem is a classic problem of decision making under risk that is taught in traditional Operations and Supply Chain Management classes as a single-period inventory problem. We discuss the following three pedagogical points of interest to any instructor tasked with teaching this topic: a) why the newsvendor model is relevant in this…

Selecting less hazardous chemicals is a core tenet of green chemistry but is difficult to teach in practice. The upper-year undergraduate or graduate level exercise described here empowers students to make such decisions themselves. Students are tasked with finding the greenest chemical for a specific purpose described in a hypothetical scenario,…

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…

Contemporary education policy involves the integration of novel forms of data and the creation of new data platforms, in addition to the infusion of business principles into school governance networks, and intensification of socio-technical relations. In this paper, we examine how "computational rationality" may be understood as…

Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking high school, college, and earnings registries spanning the state of Texas, we identify relative college value-added…

This teaching brief describes a three-echelon supply chain simulation that involves complex decision making in a dynamic environment. Using a team-based logistics simulation operating on a live commercial-software application (SAP ERP) as a foundation, a supplemental exercise is proposed for deeper learning of transportation and logistics aspects…

As part of Japanese Lesson study research focusing on "comparing and describing likelihoods", fifth grade elementary students used real-world data in decision-making. Sporting statistics facilitated opportunities for informal inference, where data were used to make and justify predictions.

All students, from college freshmen to advanced graduate students, have asked themselves, "Will this decision make me happy?" The vast majority of them have been wrong. Affective forecasting, the process of predicting future feelings, is a topic of great interest to students due to its applicable and highly relatable nature. This article…

Within the classroom it is often difficult to convey the complexities and intricacies that go into making sales and operations planning decisions. This article describes an in-class simulation that allows students to gain hands-on experience with the complexities in making forecasting, inventory, and supplier selection decisions as part of the…