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Purpose The purpose of this study was to apply social exchange and organizational support theories to examine the relationship between mid-level strategic enrollment managers’ perceptions of managerial coaching behaviors enacted by their senior managers and their own reported job engagement, as mediated by perceived organizational support (POS) within the US higher education context. Design/methodology/approach A quantitative survey-based half-longitudinal design, which used the latent marker variable technique, was conducted with a sponsoring professional organization in the strategic enrollment management (SEM) field in the USA. A total of 301 usable surveys were analyzed using structural equation modeling. Findings The results of this study indicate that SEM managers’ job engagement and the perceived managerial coaching behaviors provided to them by their senior managers were positively correlated, and that POS fully mediated this relationship. These findings highlight how coaching behaviors may allow managers to elicit positive emotional responses and, by fostering enhanced POS, ultimately enhance job engagement among their team members. Originality/value This study addresses several calls for research on managerial coaching, job engagement and POS in an under-examined higher education context within the human resource development field.

International student education is an important part of the internationalization of Chinese higher education, and the promotion of “The Belt and Road Initiative” has put forward higher requirements for the enrollment of international students studying in China, and it is of great significance to improve the quality of enrollment. In this paper, we extracted the data related to the enrollment and academic performance of international students from the academic affairs management system of each school and then pre-processed the data through data cleaning, normalization and desensitization. Then, we use the Apriori and C4.5 decision tree algorithm to mine the association rules between different influencing factors and the enrollment quality of international students and apply the decision tree to assist the decision-making of enrollment. Subsequently, the enrollment management system is constructed to realize the path of artificial intelligence technology to help improve enrollment quality. The results of association rule mining show that there are multiple association rules between different influencing factors and enrollment quality (with a minimum confidence level of 80%) and that international students’ intercultural communication ability and academic performance should be considered in the enrollment process. The empirical application of the enrollment management system found that the ideological quality of international students at the enrollment survey increased from 4.017 scores in 2020 to 9.221 scores in 2022, which verified that the enrollment system is an effective path to improve the enrollment quality of international students. The enrollment management system proposed in this paper can effectively provide decision-making reference and help for the enrollment of international students coming to China, and provide an effective path to improve the quality of international student enrollment in each school.

Students filling out the FAFSA list colleges and universities where they wish their data, sent. Until recently, colleges were provided this list, and the practice was suspended, given concerns that colleges were using the list to strategically allocate aid. Using the, 2011–2012 NPSAS, we analyze student financial aid packages to determine if list position, affects aid. We find little evidence that it does.

The Director of Academic Advisement and Bar Success will assist J.D. and LL.M. students in the development of the critical skills necessary to succeed in law school, on the bar exam, and in practice.

College and university rankings have received considerable attention throughout the world. To date, very little inquiry has examined the role of these rankings in shaping international student enrollment, which is surprising given many institutions’ desire to recruit these students. The present study explores this issue by examining data from U.S. News and World Report ’s rankings of national universities and liberal arts colleges. Specifically, it explored how changes in each of these rankings over time were associated with changes in international student enrollment; as a comparison, it also considered these same relationships among domestic students, who comprise the vast majority of U.S. undergraduates. Within a total analytic sample of 4,698 observations from 502 institutions, improvements in national university rankings consistently predict increases in international student enrollment, and these relationships are stronger at universities that were ranked more favorably. Improved rankings are also sometimes associated with increases in international student enrollment at liberal arts colleges. Regardless of institutional type, the link between rankings and international student enrollment has become even stronger in recent years. In contrast, the corresponding patterns for rankings and domestic student enrollment are weaker, nonsignificant, or occasionally in the opposite direction.

Football teams draw the largest crowds of any American collegiate sport, and with them, both positive and negative attention for colleges and universities. Nearly 50 colleges have added the sport recently, but little research has examined the institutional effects of adding a team. Some of these institutions are regional research universities adding the sport as part of broad plans to transform campus identities, while at smaller public and private institutions, adding a football team (with approximately 100 members) appears to be an attempt to boost racial diversity and the number of male students. This study uses difference-in-difference models to find that adding a football team appears to have a significant, but short-term, effect on enrollment and tuition revenue. The long-term effects of adding the sport do not appear to be statistically significant. This raises questions about the costs and benefits of adding football at a time when higher education faces significant challenges attracting students.

University resources are limited, and strategic admission management is required in certain fields that have high application volumes but limited available study places. Student admission processes need to select an appropriate number of applicants to ensure the optimal enrollment while avoiding over- or underenrollment. The traditional approach often relies on the enrollment yields from previous years, assuming fixed admission probabilities for all applicants and ignoring statistical uncertainty, which can lead to suboptimal decisions. In this study, we propose a novel machine-learning-based approach to improving student admission decisions. Trained on historical application data, this approach predicts the number of enrolled applicants conditionally based on the number of admitted applicants, incorporates the statistical uncertainty of these predictions, and derives the probability of the number of enrolled applicants being larger or smaller than the available study places. The application of this approach is illustrated using empirical application data from a German university. In this illustration, first, several machine learning models were trained and compared. The best model was selected. This was then applied to applicant data for the next year to estimate the individual enrollment probabilities, which were aggregated to predict the number of applicants enrolled and the probability of this number being larger or smaller than the available study places. When this approach was compared with the traditional approach using fixed enrollment yields, the results showed that the proposed approach enables data-driven adjustments to the number of admitted applicants, ensuring controlled risk of over- and underenrollment.

Private nonprofit colleges are increasingly using tuition resets, or a decrease in sticker price by at least 5%, to attract new students and counter declining demand. While discounting tuition with institutional aid is a common practice to get accepted students to matriculate and to increase affordability, a tuition reset is a more transparent approach that moves colleges away from a high aid/high tuition model. The authors find minimal evidence that these policies increase student enrollment in the long run, but that there may be short-term impacts. As expected, institutional aid decreases and varies directly with the size of the sticker price reduction. The average net price students pay decreases, but this effect may be driven by changes in the estimated non-tuition elements of the total cost of attendance. Finally, net tuition revenue appears unrelated to tuition resets. These findings call into question the efficacy of this practice.

In this study, we develop and implement a text messaging re-enrollment campaign to encourage former community college students to return to college. Former students are randomly assigned to one of two treatment groups that either receives information to simplify the re-enrollment process or receives both information and a one-course tuition waiver. We find that providing information and a one-course tuition waiver to former students increases their likelihood of re-enrollment by 1.5 percentage points (21.1%), enrolling in multiple courses by 0.9 percentage points (16.4%), full-time enrollment by 0.5 percentage points (21.7%), and persistence by 0.6 percentage points (23.1%). This study highlights the importance of targeted interventions that address informational and financial barriers facing former students.