Seeking a comprehensive database that encompasses high school students, college attendees, young professionals, or individuals interested in continuing education opportunities?

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• College Bound HS Students
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We understand the challenges marketers face when reaching prospective students. Our solutions provide a data-driven, results-oriented roadmap to enrollment success. Accurate, demographics-rich student marketing data is critical to your school’s successful marketing plan, especially in today’s competitive environment. Our data alliances enable us to bring to market the most robust portfolio of data lists, including students and their parents, young adults, and working professionals for continuing education programs.

Why Buy Leads From Us? With McGRAW’s student leads, you can build a robust pipeline, drive enrollment growth, and achieve your institution's educational and financial objectives. Our education leads offer:

Targeted Outreach: Connect with students interested in specific programs and fields of study. Comprehensive Data: Gain insights into students' academic interests, career goals, and preferred locations. High Engagement Rates: Reach students who are actively exploring educational options, ensuring higher response rates. Scalable Solutions: Access a wide range of leads to match your institution's enrollment goals and capacity. Quick Integration: Seamlessly integrate leads into your CRM for efficient follow-up and management. Compliance and Accuracy: Ensure all leads are generated through compliant and ethical methods, providing accurate and reliable data. What other industries can utilize the data? There are obvious ways to utilize education data and leads, but there may be some additional industries that could benefit.

Book publishers Colleges Universities Religious Organizations Education Supply Companies Office Supply Companies Fundraising Product Companies

Private school (elementary, secondary, and combined*) enrolment numbers are organized by student gender and school level for each private school. The number captures the enrolment as of October 31st for the given school year. To be included, a student must be actively enrolled to attend the private school as their main school as of October 31. Data includes: * academic year * school number * school name * school level * elementary male enrolment * elementary female enrolment * secondary male enrolment * secondary female enrolment * total male enrolment * total female enrolment Source: As reported by private schools in the Ontario School Information System (OnSIS), October submission. Data includes private, First Nations, overseas, secondary and combined schools. *Combined schools offer both elementary and secondary education. Data does not include publicly funded elementary and secondary schools, hospital and provincial schools and care, treatment and correctional facilities. Small cells have been suppressed: * where fewer than 10 students are in a given category, the data is depicted with (<10) * suppressed totals are depicted with (SP) * the report may not be used in any way that could lead to the identification of an individual Note: * starting 2018-2019, enrolment numbers have been rounded to the nearest five. * where sum/totals are required, actual totals are calculated and then rounded to the nearest 5. As such, rounded numbers may not add up to the reported rounded totals.

Analysis of ‘2018 Diversity Report - Grades K-8 School’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/99274f14-8cee-464a-a077-8e305683e288 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Report on Demographic Data in New York City Public Schools, 2017-18 in response to Local Law No. 59. Test results, as provided in this report, only count students who were actively enrolled as of October 31, 2017. Therefore, they do not match numbers publicly available elsewhere, which include all test takers.

--- Original source retains full ownership of the source dataset ---

Report on Demographic Data in New York City Public Schools, 2017-18 in response to Local Law No. 59. Test results, as provided in this report, only count students who were actively enrolled as of October 31, 2017. Therefore, they do not match numbers publicly available elsewhere, which include all test takers.

Report on Demographic Data in New York City Public Schools, 2017-18 IN response to Local Law No. 59. Test results, as provided in this report, only count students who were actively enrolled as of October 31, 2017. Therefore, they do not match numbers publicly available elsewhere, which include all test takers.

Private school (elementary, secondary, and combined) enrolment numbers are organized by student gender and school level for each private school. The number captures the enrolment as of October 31st for the given school year. To be included, a student must be actively enrolled to attend the private school as their main school as of October 31. Data includes: * academic year * school number * school name * school level * elementary male enrolment * elementary female enrolment * secondary male enrolment * secondary female enrolment * total male enrolment * total female enrolment Source: As reported by private schools in the Ontario School Information System (OnSIS), October submission. Data includes private, First Nations, overseas, secondary and combined schools. Combined schools offer both elementary and secondary education. Data does not include publicly funded elementary and secondary schools, hospital and provincial schools and care, treatment and correctional facilities. Small cells have been suppressed: * where fewer than 10 students are in a given category, the data is depicted with (<10) * suppressed totals are depicted with (SP) * the report may not be used in any way that could lead to the identification of an individual Note: * starting 2018-2019, enrolment numbers have been rounded to the nearest five. * where sum/totals are required, actual totals are calculated and then rounded to the nearest 5. As such, rounded numbers may not add up to the reported rounded totals.

IntroductionPhysical activity (PA) has both short- and long-term importance. In this study we sought to assess the prevalence and correlates of PA among 1,542 Senior High School (SHS) students.MethodsA cross-sectional study was conducted in Ghana among SHS students using the 2012 version of the Ghana Global School-based Student Health Survey (GSHS) data, which utilised two-stage cluster sampling technique. The population for the study comprised SHS students. The outcome variable was physical activity. The data were analysed using STATA version 14.2 for Mac OS. Both bivariate and multivariate analyses were employed. At the bivariate level, Pearson chi-square test between each independent variable and PA was conducted and the level of statistical significance was set at 5%. All the significant variables from the chi-square test were selected for the multivariate analysis. In the multivariate analysis, Poisson regression with robust variance was performed to estimate crude and adjusted prevalence ratios (APR).ResultsIt was found that 25.0% (29.0% males and 21.9% females) of SHS students were physically active. Female students (APR = 0.78, 95% CI = 0.65, 0.94), students in SHS 2 (APR = 0.76, 95% CI = 0.577, 0.941) and SHS3 (APR = 0.79, 95% CI = 0.63, 0.93), and those who went hungry (APR = 0.77, 95% CI = 0.65, 0.92) were less likely to be physically active compared to males, those in SHS1 and those who did not go hungry respectively. On the other hand, students who actively commuted to school (APR = 2.40, 95% CI = 1.72, 2.42) and got support from their peers were more likely to be physically active (APR = 1.62, 95% CI = 1.09–2.41).ConclusionOnly a quarter of SHS students who participated in the 2012 version of the GSHS met the WHO’s recommended level of physical activity. Sex, grade/form and experience of hunger are associated with physical activity. Physical activity is a major component of any health promotion program. Policies and programmes targeting improvement in physical activity among SHS students should take these associated factors into consideration.

A dataset was created by collecting survey responses from University of Pretoria researchers who participated in a two-year FSNet-Africa researcher development programme as hosts (referred to as UP Hosts). The role of the UP Host was to expand fellows network within the University of Pretoria. Some Hosts were invited by research teams to actively participate in the research project. The survey specifically targeted researchers from the University of Pretoria with the aim of evaluating the impact of their participation in the FSNet-Africa development programme on their skills and experience. This evaluation was conducted by assessing the effects of being a host in the FSNet-Africa early career researcher development programme on the hosts' networks and visibility, skills development, performance improvement, and personal growth in eight areas of professional development. These areas included conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, and stakeholder engagement.