52 datasets found
  1. Number of undergraduates at Harvard University 2022, by race and ethnicity

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Number of undergraduates at Harvard University 2022, by race and ethnicity [Dataset]. https://www.statista.com/statistics/938029/ivy-league-undergrads-harvard-university-gender-ethnicity/
    Explore at:
    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 19, 2022
    Area covered
    United States
    Description

    In the fall of 2022, 852 undergraduate students at Harvard University were Hispanic or Latino. This compares to 2,436 White undergraduate students.

  2. Number of undergraduates at Harvard University 2022, by gender

    • statista.com
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    Statista, Number of undergraduates at Harvard University 2022, by gender [Dataset]. https://www.statista.com/statistics/1424317/ivy-league-undergrads-harvard-university-by-gender/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 19, 2022
    Area covered
    United States
    Description

    In the fall of 2022, there were ***** male undergraduate students at Harvard University in the United States compared to ***** female undergraduate students. In addition to the fact that there are more women than men attending Harvard University as undergraduates, the student body also reflects a diverse population, although White undergraduate students still outnumber students of other races.

  3. First-generation college students at Harvard University Class of 2025, by...

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). First-generation college students at Harvard University Class of 2025, by ethnicity [Dataset]. https://www.statista.com/statistics/938411/ivy-league-first-generation-students-ethnicity-harvard-university-class/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2021
    Area covered
    United States
    Description

    In Harvard University's Class of 2025, **** percent of Hispanic or Latinx students were first-generation college students. A further **** percent of South Asian students at Harvard in the Class of 2025 were first-generation students.

  4. Number of applicants to Harvard University Class of 2012-2027

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). Number of applicants to Harvard University Class of 2012-2027 [Dataset]. https://www.statista.com/statistics/936518/ivy-league-applicants-harvard-university-class/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Harvard University, one of the leading universities in the United States, receives thousands of applications each year. For the Class of 2027 (students beginning in the fall of 2023), Harvard received 56,937 applications.

  5. H

    E4 Data: Students: Processed Quantitative Demographic Dataset

    • dataverse.harvard.edu
    Updated Apr 27, 2020
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    Cathy Lachapelle (2020). E4 Data: Students: Processed Quantitative Demographic Dataset [Dataset]. http://doi.org/10.7910/DVN/FS5YD5
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 27, 2020
    Dataset provided by
    Harvard Dataverse
    Authors
    Cathy Lachapelle
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This dataset includes all anonymized quantitative student-level demographic data, and a codebook explaining the variables contained in the dataset.

  6. p

    Delmar Harvard Elementary School

    • publicschoolreview.com
    json, xml
    Updated Nov 13, 2022
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    Public School Review (2022). Delmar Harvard Elementary School [Dataset]. https://www.publicschoolreview.com/delmar-harvard-elementary-school-profile
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    xml, jsonAvailable download formats
    Dataset updated
    Nov 13, 2022
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1987 - Dec 31, 2025
    Description

    Historical Dataset of Delmar Harvard Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2011),Total Classroom Teachers Trends Over Years (1987-2011),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2011),Asian Student Percentage Comparison Over Years (1993-2011),Hispanic Student Percentage Comparison Over Years (1996-2011),Black Student Percentage Comparison Over Years (1993-2011),White Student Percentage Comparison Over Years (1993-2011),Diversity Score Comparison Over Years (1993-2011),Free Lunch Eligibility Comparison Over Years (1993-2011),Reduced-Price Lunch Eligibility Comparison Over Years (2001-2011),Reading and Language Arts Proficiency Comparison Over Years (2010-2011),Math Proficiency Comparison Over Years (2010-2011),Overall School Rank Trends Over Years (2010-2011)

  7. d

    Course enrollment stats

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
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    Mehta, Neel (2023). Course enrollment stats [Dataset]. http://doi.org/10.7910/DVN/9MWTYO
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Mehta, Neel
    Description

    Harvard College course enrollment statistics for the most recent semester including course, department, class number, and number of students (categorized by affiliation.)

  8. p

    Harvard Elementary School

    • publicschoolreview.com
    json, xml
    Updated Feb 9, 2025
    + more versions
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    Public School Review (2025). Harvard Elementary School [Dataset]. https://www.publicschoolreview.com/harvard-elementary-school-profile/98445
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    xml, jsonAvailable download formats
    Dataset updated
    Feb 9, 2025
    Dataset authored and provided by
    Public School Review
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1987 - Dec 31, 2025
    Description

    Historical Dataset of Harvard Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1990-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1990-2023),American Indian Student Percentage Comparison Over Years (1992-2021),Asian Student Percentage Comparison Over Years (1991-2023),Hispanic Student Percentage Comparison Over Years (1991-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Native Hawaiian or Pacific Islander Student Percentage Comparison Over Years (2013-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (2003-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2003-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2022),Math Proficiency Comparison Over Years (2010-2022),Overall School Rank Trends Over Years (2010-2022)

  9. H

    my.Harvard Operational Data Store

    • dataverse.harvard.edu
    tsv
    Updated Nov 17, 2016
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    Harvard Dataverse (2016). my.Harvard Operational Data Store [Dataset]. http://doi.org/10.7910/DVN/VX5Y9G
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    tsv(41)Available download formats
    Dataset updated
    Nov 17, 2016
    Dataset provided by
    Harvard Dataverse
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/VX5Y9Ghttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/VX5Y9G

    Description

    This entry provides access to the data elements available in the Operational Data Store (ODS) for my.Harvard Student Information System. These data are available through a request process. What are the goals of the Operational Data Store? Provide data in a more real-time environment than the Warehouse (refresh 1x a day) while not putting additional load on the transactional my.harvard system. Provide a single (university-wide) standard set of exports and then web-services for retrieving key Student data. Provide the ability to incrementally load the SIS Data warehouse star schemas, making it possible to refresh certain stars more than once a day. Provide Institutional Research and Registrar power-users the ability to investigate the Student data via direct SQL access. What is the SIS Operational Data Store (SIS ODS)? A database schema on the SIS Datawarehouse that will contain replicated core tables of the my.harvard transactional system along with standardized, simplified and performant views for extracting that data. We intend to make most data available through web services before the end of academic year 2015-2016. However, our first iteration will to be make data available via db views. The refresh schedule for the SIS ODS tables for this first release will be: Academic Class Data - 1x a day between 5:30am and 6:00am. What data will be available in the SIS ODS? ODS - Academic Class v SISODS_1.0.6.xlsx follow link to get to older versions ODS - Bio Demo v SISODS_1.0.5.xlsx follow link to get to older versions ODS - Class Enrollment.xlsx ODS - Student Career Program Plan v SISODS_1.0.6.xlsx ODS - Admissions v. SISODS_1.0.7 Document coming Snapshots - non-FAS. For FAS Snapshots, please contact Harvard College Institutional Research. How can I request access to the SIS ODS? Send an email to myharvard_support@harvard.edu to request access Please indicate what data you want to access through the ODS: School & Component Available components: Academic Class (course descriptors). Biographic - Demographic Class Enrollment Student Career Program Plan Please indicate whether the request is for a personal account or for an application integration account. For personal accounts, please provide the HUIDs of the individuals to be set up. How do I connect to the SIS ODS? SIS ODS connections are currently limited to ODBC/JDBC connections to a database. The attached instructions explain how to install SQL Developer and configure a connection.

  10. Distribution of legacy students in Harvard University Class of 2025

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Distribution of legacy students in Harvard University Class of 2025 [Dataset]. https://www.statista.com/statistics/938351/ivy-league-legacy-students-harvard-class/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2021
    Area covered
    United States
    Description

    In the Class of 2025, 5.1 percent of students had two parents who attended Harvard. Legacy students are students who have had a relative attend the same university, and are typically given preference during the admissions process.

  11. H

    Replication Data for: Race, Diversity, and the Development of Political...

    • dataverse.harvard.edu
    Updated Feb 28, 2025
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    Nathan Chan; Tanika Raychaudhuri (2025). Replication Data for: Race, Diversity, and the Development of Political Attitudes on College Campuses [Dataset]. http://doi.org/10.7910/DVN/2BBHZV
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 28, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Nathan Chan; Tanika Raychaudhuri
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Faced with demographic change, many colleges are offering courses on race and ethnicity. How does taking race-centered courses affect public opinion? We theorize that while White, Latino, and Asian American students develop inclusive political attitudes through race-centered coursework, Black Americans may already enter college with a deeper understanding about racial issues. We test these expectations using two longitudinal multi-racial datasets. First, using a national panel survey of college students, we find that ethnic studies coursework is associated with increased recognition of racial discrimination among Whites, Latinos, and even Black Americans. Second, using an original panel survey from a public university, we find reduced racial resentment and increased affirmative action support - albeit varied - among Whites, Latinos, and Asian Americans after completing race-centered political science classes but not in placebo politics classes that were not focused on race. Our findings have implications for conversations about race-centered coursework in higher education.

  12. d

    Replication Data for: Vietnamese students’ expectation and perception on...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Hoang, Anh-Duc (2023). Replication Data for: Vietnamese students’ expectation and perception on educational quality [Dataset]. http://doi.org/10.7910/DVN/9S1AX2
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Hoang, Anh-Duc
    Description

    “Quality education” is of great importance for any country globally, and it is also the fourth United Nations Sustainable Development Goal (SDG4) until 2030. Nevertheless, the ambiguous definitions, the infeasibility to measure, and the variant national contexts of education quality make it troublesome to create a shared education quality measurement framework. This dataset has its foundation in the EdQUAL framework, with 2239 responses collected from March to June 2020, covering a range of Vietnamese lower-secondary students. In this dataset, we focused on (i) Demographics of the partakers; (ii) Expectations of students on various dimensions of overall education quality; and (iii) Perceptions of students on multiple dimensions of overall education quality.

  13. f

    Participant demographics.

    • plos.figshare.com
    xls
    Updated Jul 7, 2023
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    Dominic Charles Henri; Kirra Coates; Katharine Hubbard (2023). Participant demographics. [Dataset]. http://doi.org/10.1371/journal.pone.0271010.t002
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    xlsAvailable download formats
    Dataset updated
    Jul 7, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Dominic Charles Henri; Kirra Coates; Katharine Hubbard
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The lack of diversity in Science, Technology, Engineering, and Mathematics (STEM) is a significant issue for the sector. Many organisations and educators have identified lack of representation of historically marginalised groups within teaching materials as a potential barrier to students feeling that a Science, Technology, Engineering, and Mathematics (STEM) career is something that they can aspire to. A key barrier to addressing the issue is providing accessible and effective evidence-based approaches for educators to implement. In this study, we explore the potential for adapting presentation slides within lectures to ‘humanise’ the scientists involved, presenting their full names and photographs alongside a Harvard style reference. The intervention stems from an initial assumption that many formal scientific referencing systems are demographic-neutral and exacerbate prevailing perceptions that STEM is not diverse. We adopt a questionnaire based methodology surveying 161 bioscience undergraduates and postgraduates at a UK civic university. We first establish that students project assumptions about the gender, location, and ethnicity of the author of a hypothetical reference, with over 50% of students assuming they are male and Western. We then explore what students think of the humanised slide design, concluding that many students see it as good pedagogical practice with some students positively changing their perceptions about diversity in science. We were unable to compare responses by participant ethnic group, but find preliminary evidence that female and non-binary students are more likely to see this as good pedagogical practice, perhaps reflecting white male fragility in being exposed to initiatives designed to highlight diversity. We conclude that humanised powerpoint slides are a potentially effective tool to highlight diversity of scientists within existing research-led teaching, but highlight that this is only a small intervention that needs to sit alongside more substantive work to address the lack of diversity in STEM.

  14. Understanding Graduate School Admissions, The Graduate Student Experience...

    • figshare.com
    Updated Jun 15, 2023
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    Ronald Jason Heustis; David Van Vactor (2023). Understanding Graduate School Admissions, The Graduate Student Experience and Post-PhD Trajectories: Bowdoin College 2016 [Dataset]. http://doi.org/10.6084/m9.figshare.12613415.v1
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    Dataset updated
    Jun 15, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Ronald Jason Heustis; David Van Vactor
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Introduction This STEM advising outreach program was developed for undergraduate students who are contemplating future applications to PhD programs in the life sciences. The audience of ~20 students ranged in academic stage, and was composed mostly of life sciences undergraduates enrolled at Bowdoin College.

    We have previously described two similar outreach events (ref. 1,2); this 90-minute combination of seminar and discussion built on that pilot program. This session at Bowdoin College was intended to complement the advising that students receive from their primary research mentors on campus. Although undergraduates at many excellent institutions have access to extensive pre-professional advising for careers in medicine, law and some other directions, the structure of advising for scientific research and the many career options that rely on PhD training is less consistent. Independent study or thesis research mentors are often a student’s primary source of advice. Career advisors have confirmed that reiteration and reinforcement of advising principles by professionals external to the school environment is helpful. Therefore, this outreach program’s content was developed with a goal of demystifying PhD programs and the benefits that they provide. The topics covered included (a) determining the key differences between programs, (b) understanding how PhD admissions works, (c) preparing an effective application, (d) proactive planning to strengthen one’s professional portfolio (internships, independent research, cultivating mentors), (e) key transferable skills that most students learn in graduate school, (f) what career streams are open to life science PhDs, and, (g) some national and institutional data on student career aspirations and outcomes (ref. 3). Methods The approach of bringing a faculty member and an administrative staff member who both have life science PhD training backgrounds was intentional. This allowed the program to portray different perspectives and experience to guide student career development, while offering credible witnesses to the types of experiences, skills and knowledge gained through PhD training. Central to the method of this outreach program is the willingness of graduate educators to meet the students on their own ground. The speakers guided students through a process of identifying national graduate programs that might best serve their individual interests and preferences. In addition to recruiting prospective applicants to Harvard Medical School (HMS) summer internships and PhD programs, the speakers made an explicit appeal to students to hone their professional portfolio proactively by discussing important skills that undergraduates need to be competitive in admissions and the career workplace including acquiring training in statistics and programming, soliciting diverse mentorship, acquiring authentic research experiences/internships, conducting thesis research, and obtaining fellowships). By reinforcing much of the anecdotal and formal advising content that is made available by faculty mentors and career counselors, our host saw the value of external experts to validate guidance.

    This event built off our most recent event (ref. 2); we delivered a presentation covering the relevant topics and transitioned into an open discussion featuring a third visitor in our team. In contrast to the aforementioned previous event, the time constraint at lunch time prevented us from doing a formal panel. Our third speaker was a HMS Curriculum Fellow (ref. 4) whose career goals included teaching at a comparable institution (primarily undergraduate institution, PUI).

    Students were encouraged to have lunch during the session, as the program was held at midday to avoid conflicts with other academic or extracurricular events. ResultsAs the principal goal of the session was to encourage and engage students, not to evaluate them, and the students ranged widely in stage and long-term career objectives, there were no assessment surveys of learning gains. Informally, student engagement was excellent as judged by the frequency and thoughtful nature of questions asked during the discussion phase of the session. Ad hoc student feedback directly following the event was extremely positive, as was our host’s follow up by email after the event. The success of the program was also evident by an invitation for a repeat of the program or other forms of collaboration in the future, including the possibility of reciprocal visits to HMS.DiscussionThis advising session was a continued refinement of our prototype, and thus served to prepare us for a series of similar events across a larger network of colleges. Our decision to incorporate a HMS Curriculum Fellow served three purposes: (1) to engage speaker who pursued doctoral training at three different institutions (UCLA, Tufts University, Harvard University), (2) to broaden the range of career trajectories presented as outcomes from doctoral programs, and (3) to provide networking and career development opportunities for the Curriculum Fellow.

  15. Share of international students in Ivy League schools Class of 2028

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Share of international students in Ivy League schools Class of 2028 [Dataset]. https://www.statista.com/statistics/941523/ivy-league-international-students-class/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In Columbia University's Class of 2028 (students beginning in the fall of 2024), ** percent of students were international students. This is compared to Harvard University, where ** percent of incoming students were international students.

  16. d

    Replication data for: Idaho Population Data 1960-1995 (20 Tables)

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
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    Harvard Dataverse (2023). Replication data for: Idaho Population Data 1960-1995 (20 Tables) [Dataset]. http://doi.org/10.7910/DVN/DKQHT3
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Time period covered
    Jan 1, 1960 - Jan 1, 1995
    Area covered
    Idaho
    Description

    The Idaho Statistics Update project is made possible by a 1997/98 Seed Grant from the University of Idaho Research Office. The grant was used to hire three student assistants to input the data and to convert the data to a usable format for the Web. The underta king of this project is possible to accomplish only with the assistance of several librarians at the University of Idaho. Some of the original chapters included here were published as volume one of the Idaho Statistical Abstract, 4th edition, by University of Idaho, Center for Business Development and Research. Efforts were made to use the sources listed in the original chapters to update the data when available. The chapters intended for volume 2 of Idaho Statistical Abstract, 4th edition, are new data collected from various sources by Lily Wai, the Compiler-in-Chief. The Idaho Department of Commerce also contributed some funds for this project. This is an on-going project with periodic updates planned when funding becomes available. In the interest of improving the quality and coverage of future updates, users of this site are encouraged to address suggestions to Lily Wai, Head of Government Documents, University of Idaho Library, Moscow, Idaho 83844-2353.

  17. H

    Predictive Factors of Parental Closeness in College Students

    • dataverse.harvard.edu
    Updated Jul 21, 2016
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    Amanda Ricca (2016). Predictive Factors of Parental Closeness in College Students [Dataset]. http://doi.org/10.7910/DVN/7XUHQY
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 21, 2016
    Dataset provided by
    Harvard Dataverse
    Authors
    Amanda Ricca
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This study examines demographic variables in an attempt to discern whether class year, gender, race, and socioeconomic status have an impact on parental closeness and support in college students. Using data from an original survey of Colgate sophomores and seniors, this study shows that gender of parent and socioeconomic status are salient factors in parental closeness. Students are more likely to be closer to their mothers than their fathers, and students of higher socioeconomic status report feeling closer to both parents as well as receiving higher levels of emotional, financial and networking support from their parents.

  18. f

    The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and...

    • plos.figshare.com
    zip
    Updated Jun 2, 2023
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    Melanie I. Stefan; Johanna L. Gutlerner; Richard T. Born; Michael Springer (2023). The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences [Dataset]. http://doi.org/10.1371/journal.pcbi.1004208
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS Computational Biology
    Authors
    Melanie I. Stefan; Johanna L. Gutlerner; Richard T. Born; Michael Springer
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.

  19. H

    Replication Data for: Learning from the Test: Raising Selective College...

    • dataverse.harvard.edu
    Updated Nov 16, 2016
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    Sarena Goodman (2016). Replication Data for: Learning from the Test: Raising Selective College Enrollment by Providing Information [Dataset]. http://doi.org/10.7910/DVN/GKJWUG
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 16, 2016
    Dataset provided by
    Harvard Dataverse
    Authors
    Sarena Goodman
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Goodman, Sarena, (2016) "Learning from the Test: Raising Selective College Enrollment by Providing Information." Review of Economics and Statistics 98:4, 671-684.

  20. H

    Transfronterizx College Students’ Perceptions of Campus Climate and Sense of...

    • dataverse.harvard.edu
    Updated Mar 27, 2025
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    Vannessa Falcón Orta (2025). Transfronterizx College Students’ Perceptions of Campus Climate and Sense of Belonging [Dataset]. http://doi.org/10.7910/DVN/YMGCMK
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 27, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Vannessa Falcón Orta
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    PURPOSE The purpose of this study was to investigate the variables that best predicted Transfronterizx college students’ sense of on-campus belonging in higher education at the San Diego-Tijuana borderlands. To identify the variables that predicted students’ on-campus sense of belonging, this study also examined their demographic characteristics, student characteristics, transborder interactions, and beliefs about their campus climate. A total of 100 Transfronterizx students (58% female and 42% male) from a four-year higher education institution in the Southwestern region of the United States participated in this study. PARTICIPANTS The data for this study was collected during the fall 2015 academic year. A total of 100 students (58% female, 42% male) from a four-year higher education institution located in a border town in the southwestern region of the United States participated in this study. Of these, 81 (81%) were undergraduates, and 19 (19%) were master's students. The mean age of participants was 23.66 years (SD = 5.19), with a range of 18 to 50 years. Overall, 9,000 undergraduate and 2,000 graduate Latinx students were contacted via email to participate in the study. A total of 130 participants completed the questionnaire. However, responses from students who had already graduated or were not living a transborder life during the study period were excluded from the analysis and findings. As a result, only 100 students were included in the final sample. SITE The recruitment site for this study was a Hispanic-serving, four-year public higher education institution located in a border town in the southwestern region of the United States. The campus is situated in close proximity to the U.S.-Mexico international border, and campus leaders have engaged in various binational collaboration efforts with non-profit organizations and higher education institutions in Mexico. This institution was selected as the recruitment site due to its proximity to the U.S.-Mexico international border. At the time of this study, the university served approximately 32,000 students. However, there is no record of the number of students who attend the campus and live a transborder life in the U.S.-Mexico region. Researchers explain that, due to the nature of the Transborder population—where many members have dual citizenships and dual domiciles—it is difficult to track the exact number of students who are part of the U.S.-Mexico Transfronterizx community (Chavez Montaño, 2006). PROCEDURES AND RECRUITMENT The methodological procedure for this study was descriptive in nature. The recommended sample size for a descriptive study is approximately 100 participants for each major subgroup (Mertens, 2015). In line with this recommendation, 100 students from the higher education institution mentioned above participated in the study. Upon receiving Institutional Review Board (IRB) approval, the consent form and data collection instruments were uploaded to the Qualtrics system for participants to access. A Qualtrics link to the consent form and data collection instruments was included in a recruitment email sent to students via social media outlets, student clubs, and campus organizations. A total of 130 students from the higher education institution completed the questionnaire; however, 30 responses were excluded because the students did not meet the participant requirements. As a result, only 100 students were included in this study. INSTRUMENT The researcher collected quantitative responses about the transborder experiences of college students who live a transborder life through a 30-item questionnaire to address the first and second sub-research questions of this study: (1) What are the demographic and student characteristics of Transfronterizx college students from the U.S.-Mexico Southwest Border Region? and (2) What are Transfronterizx college students’ transborder characteristics and belief levels about living a transborder life?To capture students’ demographic characteristics, the questionnaire included nominal questions about students’ age, race, ethnicity, cultural identification, and academic experiences. It also included nominal questions about students’ transborder interactions, the circumstances that led them to live a transborder life, and their current reasons for continuing to do so. Additionally, two ordinal items measured students’ beliefs about living a transborder life using a Likert scale ranging from 1 = strongly disagree to 4 = strongly agree. The researcher administered the following subscales from the National Survey of Hispanic Students (NSHS) (Hurtado & Carter, 1997) to address the third and fourth sub-research questions of this study: Sense of Belonging to Campus (SBC), Experienced Discrimination-Exclusion (EDE), and Perceptions of Campus Racial-Ethnic Tension (PCRET). These sub-research questions were: (3) What are Transfronterizx college students’ belief levels about their sense of belonging, experiences...

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Statista (2024). Number of undergraduates at Harvard University 2022, by race and ethnicity [Dataset]. https://www.statista.com/statistics/938029/ivy-league-undergrads-harvard-university-gender-ethnicity/
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Number of undergraduates at Harvard University 2022, by race and ethnicity

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Dataset updated
Jul 5, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Oct 19, 2022
Area covered
United States
Description

In the fall of 2022, 852 undergraduate students at Harvard University were Hispanic or Latino. This compares to 2,436 White undergraduate students.

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