Aim/Purpose: We aim to bring a better understanding of technology use in the educational context. More specifically, we investigate the determinants of webinar acceptance by university students and the effects of this acceptance on students' outcomes in the presence of personal characteristics such as anxiety, attitude, computer self-efficacy, and…

This study examines the attrition and achievement of a sample of 295 students in an on-campus tertiary bridging program at a regional university. A logistic regression analysis using enrolment status, age and the number of absences from scheduled classes at week three of the semester as predictor variables correctly predicted 92.8 percent of…

There is a very large population of students who struggle with the transition from the middle grades to high school, raising concerns that high school failures are partially a function of poor middle grade preparation. As a result, middle grade practitioners are grappling with questions about what skills students need to succeed in high school,…

An early warning system is a data-based tool that helps predict which students are on the right path towards eventual graduation or other grade-appropriate goals. Through such systems, stakeholders at the school and district levels can view data from a wide range of perspectives and gain a deeper understanding of student data. This "Statewide…

Students with special educational needs and disabilities (SEND) are at a greatly increased risk of poor academic outcomes. Understanding the factors that influence their attainment is a crucial first step towards developing more effective provision. In the current study we present a multi-level, natural variation analysis which highlights…

The present research was a two-year longitudinal study on the effects of a six-day, optional, pre-semester, freshman orientation program on academic credits earned, GPA and college retention. Regression analyses were used to remove the variance associated with other possible predictors of academic success (gender, age, race, developmental need,…

A meta-analysis of the relationship between class attendance in college and college grades reveals that attendance has strong relationships with both class grades (k = 69, N = 21,195, p = 0.44) and GPA (k = 33, N = 9,243, p = 0.41). These relationships make class attendance a better predictor of college grades than any other known predictor of…

A study investigated students' classroom interaction in 16 courses at a small extension campus of Indiana University Purdue University Columbus. Results indicate attendance patterns, student age, week in the semester, course level, and time of day were significant predictors of student interaction level. Impact of gender and instructor gender was…