Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

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,…

Higher education institutions adopt conversational agents, or chatbots, to perform and automate certain business functions. While chatbots exist to support Enrollment Services, Financial Aid, and other departments within an institution, Institutional Research lacks options. Institutional Research supports higher education institutions by providing…

College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…

As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…

Academic choice and exploration are essential aspects of undergraduate education in the United States, allowing students to select courses with minimal restrictions. However, students often face challenges in navigating the complex academic landscape, hindered by limited information, insufficient guidance, and an overwhelming number of choices.…

Generative AI has been expanding at an exponential rate since its widespread emergence in late 2022, yet limited research has explored its adoption or use among higher education faculty. Guided by the Diffusion of Innovations theory, this quantitative survey research study investigated higher education faculty's perceptions, adoption, and use of…

With the advent of ChatGPT and other artificial intelligence (AI) tools, students have a new instrument that can create writing samples for them, making it easy to violate academic integrity. A constructivist grounded theory multiple-case study was conducted to address faculty perceptions of ChatGPT as a tool for learning and teaching instead of a…

This dissertation comprises three cross-disciplinary essays on information systems, marketing, and financial outcomes research for nonprofit service organizations. In our first essay, we explore service quality impacts on the constructs of positive and negative word of mouth, developing and validating a new measurement scale, testing it…

Higher education is examining artificial intelligence (AI) as a key to increasing productivity and efficiency as colleges race to remain relevant and competitive in a rapidly evolving industry. With the increase of students taking online classes, professors are looking for solutions to help maintain integrity with their testing remotely. AI has…

This study examines the effectiveness of implementing a chatbot solution to supplement existing student support or service models on campus, specifically for transfer students. Chatbots, an artificial intelligence solution meant to mimic human conversation and personality, have been viewed as a viable option for supporting transfer students…