Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on…

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

This study aimed to address the state of data driven decision practices within the Division of Student Affairs at South County College. Framed by an exploratory qualitative case study, this project conducted semi-structured interviews of directors of student affairs and a document analysis of annual reports of the seven departments that constitute…

Speculative reform jumps the gun on notions of data-driven reform, requiring administrators to anticipate and act to ensure problems (and the data that would show them) do not materialize. Speculative reforms are incapable of delivering the outcomes they promise, as they are fueled by a fear of the future that their reforms do not extinguish. In…

The purpose of this project is to explore the limitations of federal postsecondary data as data as those data relate to Indigenous students and to Tribal Colleges and Universities. After first establishing some of the statistical limitations we commonly find in postsecondary data with Indigenous students, we provide strategies and practices that…

Enabling college graduates to achieve career success is increasingly considered a major responsibility of universities. Many studies have developed models of predicting students' career decisions and have sought to provide appropriate treatments or early support for students to achieve this goal. Most studies, however, have focused on using…

We present a historical case study of "data-driven" general education policy reform at the City University of New York, where within-system transfer issues prompted the need for curricular reform that was debated and eventually implemented from 2011 to 2017. Through an empirical examination of artifacts such as meeting minutes, internal…

Data-based instruction (DBI) is a process in which teachers use progress data to make ongoing instructional decisions for students with learning disabilities. Curriculum-based measurement (CBM) is a common form of progress monitoring, and CBM data are placed on a graph to guide decision-making. Despite the central role that graph interpretation…

This paper argues that a data-driven, niche-focused approach to strategy development will assist Higher Education Institutions to direct their financial resources to greater effect by providing a more tailored service to students, therefore, increasing student satisfaction and creating brand loyalty. This approach will give institutions greater…

A gap exists between the ability to gauge the success of institutions by deploying a relatively simple set of measures typically based upon the federal cohort, versus the ability to monitor the successful (or unsuccessful) progression of the varied students who move through them. Daniel Regan questions which matters more. To gauge the health of an…

Decision-making is a critical topic in any management and organizational behavior course. Navigating and understanding the various processes and influences on decision-making, however, can be complicated. This article revises and expands on a common "employee ranking" format activity. It uses in-class student data to systematically…

In this article, I examine campus climate studies through radical incrementalism and queer pragmatism. As a statistician and institutional researcher, I embrace data-informed decisions to promote resource reallocation and policy formation. Yet, as a queer person, I have misgivings about incrementalism as a dominant strategy that aligns queerness…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

This study explores the dynamics of student interaction networks within an online asynchronous discussion forum, focusing on both whole group discussions and subgroup interactions distinguished by the Louvain algorithm, a renowned community detection method. Analyzing 2481 posts from 154 undergraduate students across three sections of a…