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,…

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…

In this article, we provide an approach to solve the problem of academic specialty selection in higher educational institutions with Ukrainian entrants as our target audience. This concern affects operations at universities or other academic institutions, the labor market, and the availability of in-demand professionals. We propose a…

Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…

Learning data analytics improves the learning field in higher education using educational data for extracting useful patterns and making better decisions. Identifying potential at-risk students may help instructors and academic guidance to improve the students' performance and the achievement of learning outcomes. The aim of this research study is…

Higher education institutions are striving to lower student dropout rates to increase the number of academically qualified persons in the labour market and decrease misguided investment. Researchers generally acknowledge that students who are firmly decided on their studies tend to drop out of their studies less frequently. Building on the…

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…

Making sense of student feedback and engagement is important for informing pedagogical decision-making and broader strategies related to student retention and success in higher education courses. Although learning analytics and other strategies are employed within courses to understand student engagement, the interpretation of data for larger data…

With the onset of online education via technology-enhanced learning platforms, large amount of educational data is being generated in the form of logs, clickstreams, performance, etc. These Virtual Learning Environments provide an opportunity to the researchers for the application of educational data mining and learning analytics, for mining the…

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

The study abroad experience is an important fixture of American higher education, with politicians, institutions, and mainstream media calling for increased participation. Participation in study abroad can potentially benefit students' personal, academic, and career development. However, historical educational data have shown that some groups,…

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…

Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in…

We estimate the percentage of eligible students who do not take up their federal need-based student financial aid entitlements in a microsimulation model for the German Socio-Economic Panel Study 2002--2013. We find that about 40% of the eligible low-income students do not take up their entitlements. Non-take-up is inversely and rather…

Statistics anxiety has often been linked to performance in statistics modules for psychology students, despite this no research to date has examined whether attitudes towards statistics can predict whether or not a student chooses to carry on psychology from pre-tertiary to higher education. In this pilot study 41 second year A-level psychology…