A comparative longitudinal data analysis between two online non-thesis master's programs--natural resource management and environmental science--in a college of natural resources to determine the relationship between student characteristics and disenrollment risks. Risks varied between the two programs, with significance found to increase the risk…

A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

Higher education administrators lack strong understanding about using course evaluation data to make judgments and decisions. Using archival student course evaluation data from a pharmacy school, we examined (a) course evaluation instrument reliability and validity; (b) bivariate relationships between eight course rating items and the overall…

Identifying at-risk students at an early stage is a challenging task for colleges and universities. In this paper, we use students' oncampus network traffic volume to construct several useful features in predicting their first semester GPA. In particular, we build proxies for their attendance, class engagement, and out-of-class study hours based…

Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…

Building Assets Reducing Risks (BARR) is a social emotional model that achieves academic outcomes through combining use of real-time student data with proven relationship-building strategies and intensive teacher collaboration to prevent course failure. BARR is a recipient of US Department of Education "Investing in Innovation (i3)"…

By probing the micro-level interactions and experiences shaping students' thoughts, behaviors, and decisions during college the authors hope to generate a better picture of how individuals enact the intersection of their own agency with their given social context. Such insights may enable a more accurate and meaningful interpretation of the…

An extension of the methods of path analysis to include studies of categorical data was described and exemplified in a causal study of college dropouts. The usual models and methods of causal (path) analysis were designed for the study of quantitative variables and are not appropriate when the variables under investigation are categorical.…

This paper presents study results concerning the nature of successful academic performance, specifically examining to what extent self-regulated learning played a role in successful academic performance at the college level. (Self-regulated learning is defined as the integration and utilization of cognitive, metacognitive, motivational,…

The effects of working and attending high school simultaneously on the academic achievement of students had more absences, and the effects of absences on achievement. Subjects were 130 juniors and 110 seniors, of whom 57 percent were working during the school year. Forty-six percent were male and 54 percent were female, and 86 percent were white…