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Recently, there has been an increased interest in the well-being of students in higher education. Despite the widespread consensus on the importance of student well-being, a clear definition continues to be lacking. This study qualitatively examined the student perspective on the topic through semi-structured interviews at a university of applied sciences in the Netherlands (n = 27). A major recurring theme was well-being as a balance in the interplay between efforts directed towards studies and life beyond studies. This method of perceiving well-being deviates from theoretical definitions. Students mentioned various factors that influence their well-being. Responses ranged from personal and university related factors to external factors beyond their educational institution. This study contributes to the body of knowledge on the well-being of students in higher education and provides suggestions for educational institutions, such as incorporating a holistic perspective on students and learning; and focus points for the development of policies and practices.

This study examined the demographic, pre-college, environmental, and college factors that impact students' interests in and decisions to earn a science, technology, engineering, or mathematics (STEM) degree among students attending a Hispanic Serving Institution (HSI). Results indicated that Hispanic students were well represented among STEM majors, and students' decisions to declare a STEM major and earn a STEM degree were uniquely influenced by students' gender, ethnicity, SAT math score, and high school percentile. Earning a STEM degree was related to students' first-semester GPA and enrollment in mathematics and science \"gatekeeper\" courses. Findings indicate that HSIs may be an important point of access for students in STEM fields and may also provide opportunity for more equitable outcomes for Hispanic students.

This study examines the relationship between student perceptions and their intention to use generative artificial intelligence (GenAI) in higher education. With a sample of 405 students participating in the study, their knowledge, perceived value, and perceived cost of using the technology were measured by an Expectancy-Value Theory (EVT) instrument. The scales were first validated and the correlations between the different components were subsequently estimated. The results indicate a strong positive correlation between perceived value and intention to use generative AI, and a weak negative correlation between perceived cost and intention to use. As we continue to explore the implications of GenAI in education and other domains, it is crucial to carefully consider the potential long-term consequences and the ethical dilemmas that may arise from widespread adoption.

Total student loan debt rose to over$800 billion in June 2010, overtaking total credit card debt outstanding for the first time. By the time this article sees print, the continually updated Student Loan Debt Clock will show an accumulated total of roughly $ 1 trillion. Borrowing to finance educational expenditures has been increasing—more than quadrupling in real dollars since the early 1990s. The sheer magnitude of these figures has led to increased public commentary on the level of student borrowing. We move the discussion of student loans away from anecdote by establishing a framework for considering the use of student loans in the optimal financing of collegiate investments. From a financial perspective, enrolling in college is equivalent to signing up for a lottery with large expected gains—indeed, the figures presented here suggest that college is, on average, a better investment today than it was a generation ago—but it is also a lottery with significant probabilities of both larger positive, and smaller or even negative, returns. We look to available—albeit limited—evidence to assess which types of students are likely to be borrowing too much or too little.

Promise programs are proliferating across the United States, with wide variation in their design. Using national data on 33 Promise programs affecting single, 2-year colleges, this study examines program effects on first-time, full-time college enrollments of students by race/ethnicity and gender classification. Results suggest Promise programs are associated with large percent increases in enrollments of Black and Hispanic students, especially students classified as females, at eligible colleges. Promise programs with merit requirements are associated with higher enrollment of White and Asian, Native Hawaiian, or Pacific Islander female students; those with income requirements are negatively associated with enrollment of most demographic groups. More generous Promise programs are associated with greater enrollment increases among demographic groups with historically higher levels of postsecondary attainment.

Using multiple data sets from different time periods, we document declines in academic time investment by full-time college students in the United States between 1961 and 2003. Full-time students allocated 40 hours per week toward class and studying in 1961, whereas by 2003, they were investing about 27 hours per week. Declines were extremely broad based and are not easily accounted for by framing effects, work or major choices, or compositional changes in students or schools. We conclude that there have been substantial changes over time in the quantity or manner of human capital production on college campuses.

This article explores the patterning of student im/mobility internally within the United Kingdom, using exceptionally detailed student records data on full-time undergraduate entrants from 2014. For this cohort of students, geographic mobility was clearly the preserve of the most socio-economically advantaged, and was less common for Pakistani and Bangladeshi ethnic groups. Significantly, the student's 'home' region emerges as the most important factor driving im/mobility even when social, ethnic and educational differences are held constant. The concept 'structures of feeling' can help make sense of immobility in areas of the North-East, North-West and Wales, where students are likely to look on higher education choice through a different lens of accumulated and contemporary, inter-generational cultural experience. Exploring exceptions to the dominant trends, we also find a more complex patterning of im/mobility that is likely to reflect the deep historical and structural framing of young people's socio-spatial horizons.

Online education has the potential to remove barriers and increase access to higher education, but previous studies have revealed mixed results regarding the effect of online enrollment on college students’ academic outcomes. This study leverages novel administrative data and a fuzzy regression discontinuity design to examine the impact of online enrollment in introductory STEM coursework on students’ probability of STEM success. We find that taking the online version of a required introductory Chemistry course increases students’ time-to-degree, with starker increases when focusing on the number of semesters needed to complete a STEM degree.

This study analyzed the relationships among factors predicting online university students' actual usage of a mobile learning management system (m-LMS) through a structural model. Data from 222 students in a Korean online university were collected to investigate integrated relationships among their perceived ease of use, perceived usefulness, expectation-confirmation, satisfaction, continuance intention and actual usage of m-LMS. Results showed that perceived ease of use predicted perceived usefulness, but expectation-confirmation was not related to perceived usefulness. Perceived usefulness and expectation-confirmation predicted satisfaction. Perceived usefulness and satisfaction predicted continuance intention, but perceived ease of use was not related to continuance intention. Continuance intention predicted actual usage of m-LMS.

Students' time expenditures influence their learning and development. This study used latent profile analysis to identify a taxonomy of how first-year students spend their time using a large multi-institution sample. We identified four time usage patterns by first-year students titled Balanced, Involved, Partiers, and Parents. Sex, expected major field, on-campus residency, age, Greek-life membership, and standardized test scores were predictive of students' time use patterns. Holding a range of student and institutional factors constant, members of the involved group, on average, reported higher levels of engagement than the Balanced group, while Partiers reported lower levels of engagement. Implications for policy and practice are discussed.