The share of first-generation students (those who are the first in their family to attend college) in Ivy League schools varied from school to school. For the Class of 2028 (students beginning university in the Fall of 2024), **** percent of Cornell University's freshman class were first-generation college students.

This statistic shows the percentage of students identifying as first-generation in the United States in 2016, by gender and ethnicity. As of 2016, about ** percent of the first-generation American students, broken down by gender, were female. Almost ** percent of the first-generation students identified themselves as Native Americans in the United States in 2016.

According to a survey conducted in 2024, ** percent of Generation Z students reported that they would be the first in their family to attend college in the United States.

This qualitative longitudinal study aims to explore the well-being and academic readiness of first-generation undergraduates over time. The study involves two rounds of 1-hour Zoom interviews, conducted at two different time points (e.g., first and second semester of an academic year). The sampling procedure will ensure a diverse and representative sample of first-generation students while maintaining feasibility and ethical considerations.Target population is defined with an inclusion criteria: First-generation undergraduate students (defined as students whose parents/guardians did not complete a bachelor’s degree); and enrolled full-time in a degree program at the participating institution(s). Exclusion criteria includes students who do not identify as first-generation.Sampling strategy is by purposive sampling and snowball sampling. Purposive sampling ensures a diverse sample that reflects the heterogeneity of first-generation students in terms of, gender, ethnicity/race, socioeconomic background, academic major, year of study (e.g., freshmen, sophomores), and student status as local, mainland, or international. Snowball sampling invites participants to refer other first-generation students who meet the inclusion criteria. This will help expand the sample and include students who may not be easily reachable through institutional channels.Since the population of first-generation students is minor in a university, sample size was aimed at 30 participants for the interviews and fifty students were recruited to join round 1 interviews. This sample size is manageable for in-depth qualitative analysis and allows for attrition in the second round. Round 1 interviews were conducted at the beginning of the academic year (e.g., September–October). Round 2 interviews were conducted at the end of the academic year (e.g., April–May). A 10% attrition rate was anticipated between the two rounds due to scheduling conflicts or withdrawal from the study. Forty-five students from round 1 continued the interview in round 2. The data files are transcripts form both round 1 and round 2 interviews.

In 2020, ** percent of students at Brown University in the United States were first-generation college students. This is an increase from the previous year, when ** percent of students at Brown were first-generation college students.

This reflective paper explores the intersectionality of social identity, trauma, and education through the lens of a first-generation college student (FGCS) who is a neurodivergent Army veteran. I share my personal journey and experiences, highlighting marginalized communities’ challenges in the education system. I delve into the impact of cultural invasion, the transmission of trauma across generations, and the importance of critical consciousness in addressing educational inequality. I also discuss the role of spatial thinking and language in shaping learning experiences. I emphasize the need for cultural awareness, inclusivity, and equity in educational spaces and highlight the transformative power of embracing one’s differences. Overall, I explain the complex dynamics of social identity, trauma, and education and call for a deeper understanding and critical examination of these issues.

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.

IntroductionWe investigated differences in domain-general expectancy, value, and engagement in school by generation status and how the relationship among these constructs and academic performance differ by generation status.MethodsA total of 573 college students enrolled in introductory psychology courses participated in the study. We collected data on generation status, expectancy-value beliefs, school engagement, and official GPA data from participants, tested measurement invariance of expectancy-value beliefs and engagement between first-generation college students (FGCS) and continuing generation college students (CGCS), and conducted multigroup modeling to understand the differential relations of expectancy-value, engagement, and GPA between the two groups.ResultsWe discovered that the latent mean of expectancy beliefs differed significantly by generation status, with FGCS reporting higher expectancy than CGCS. There were no differences in the latent mean of task value. Multigroup structural equation modeling revealed that the effect of expectancy-value motivation on behavioral engagement was similar across groups, but its effect on cognitive engagement was greater for the FGCS than for the CGCS. For both groups, expectancy impacted academic performance via behavioral engagement. Finally, neither expectancy-value motivation nor cognitive engagement directly predicted academic performance for either group.DiscussionThe findings have important theoretical implications for understanding motivation and achievement of FGCS and CGCS and critical practical implications regarding undergraduate education.

Data on student success and retention-in-major (DVs) for a sample of science and mathematics majors before and after a required peer-cooperative learning program was implemented. IVs include student major, course taken, SAT scores, and demographic data including gender, low-income student status, student-of-color status, and first-generation college student status.

This statistic shows the acceptance and attendance rates of freshmen at first-choice colleges in the United States in 2016, by student generation. In 2016, about ** percent of the first-generation students were accepted to their first-choice college; however, the attendance rate of first-choice college by first-generation students was **** percent in the United States.

Data for this study were collected at the University of California – Irvine (UCI) as part of the UCI-MUST (Measuring Undergraduate Success Trajectories) Project, a larger longitudinal measurement project aimed at improving understanding of undergraduate experience, trajectories and outcomes, while supporting campus efforts to improve institutional performance and enhance educational equity (Arum et. al. 2021). The project is focused on student educational experience at a selective large, research-oriented public university on the quarter system with half of its students first-generation and 85 percent Hispanic, Asian, African-American, Pacific Islander or Native American. Since Fall 2019, the project has tracked annually new cohorts of freshmen and juniors with longitudinal surveys administered at the end of every academic quarter. Data from the Winter 2023 end of term assessment, administered in the first week of April, was pooled for four longitudinal study cohorts for this study (i.e., Fall 2019-2022 cohorts). There was an overall response rate of 42.5 percent for the Winter 2023 end of term assessment. This allowed us to consider student responses from freshmen through senior years enrolled in courses throughout the university. Students completed questionnaire items about their knowledge and use of ChatGPT in and out of the classroom during the winter 2023 academic term. In total 1,129 students completed the questionnaire, which asked questions about: knowledge of ChatGPT (“Do you know what ChatGPT is?”); general use (“Have you used ChatGPT before?”); and instructor attitude (“What was the attitude of the instructor for [a specific course students enrolled in] regarding the use of ChatGPT?”). Of those 1,129 students, 191 had missing data for at least one variable of interest and were subsequently dropped from analysis, resulting in a final sample of 938 students. In addition, for this study we merged our survey data with administrative data from campus that encompasses details on student background, including gender, race, first-generation college-going, and international student status. Campus administrative data also provides course-level characteristics, including whether a particular class is a lower- or upper-division course as well as the academic unit on campus offering the course. In addition, we used administrative data on all students enrolled at the university to generate classroom composition measures for every individual course taken by students in our sample – specifically the proportion of underrepresented minority students in the class, the proportion of international students in the class and the proportion of female students in the class. For our student-level analysis [R1], we used binary logistic regressions to examine the association between individual characteristics and (1) individual awareness and (2) individual academic use of ChatGPT utilizing the student-level data of 938 students. Individual characteristics include gender, underrepresented minority student status, international student status, first generation college-going student status, student standing (i.e. lower or upper classmen), cumulative grade point average and field of study. Field of study was based on student major assigned to the broad categories of physical sciences (i.e. physical sciences, engineering, and information and computer science), health sciences (i.e. pharmacy, biological sciences, public health, and nursing), humanities, social sciences (i.e. business, education, and social sciences), the arts, or undeclared. We defined awareness of ChatGPT as an affirmative response to the question “Do you know what ChatGPT is?” Regarding ChatGPT use, we focused on academic use which was defined as an affirmative response of either “Yes, for academic use” or “Yes, for academic and personal use” to the question “Have you used ChatGPT before?” For our course-level analysis [R2], we constructed a measure – course-level instructor encouragement for ChatGPT use – based on student responses to the end of the term survey conducted at the completion of the Winter 2023 term. In the survey, students were asked to indicate the extent to which their instructors encouraged them to use ChatGPT in each of their enrolled courses. The response

ObjectiveThe objective of this study is to explore the influence of family capital (including family economic capital, family cultural capital and family social capital) on the academic achievement (including ability development, academic performance and self-concept) of first-generation college students.MethodsThe questionnaires are based on the CFPS (China Family Panel Studies) database and tailored to the specific circumstances. Data was collected from 1524 first-generation college students from five universities in Liaoning Province. SPSS 23.0 and AMOS 24.0 were used to analyze the data.ResultsFamily economic capital significantly predicted ability development (standardized regression coefficient = 0.198, P < 0.001) and academic performance (standardized regression coefficient = 0.220, P < 0.001); Family cultural capital significantly predicted ability development (standardized regression coefficient = .114, P < 0.001), academic performance (standardized regression coefficient = 0.217, P < 0.001) and self-concept (standardized regression coefficient = 0.160, P < 0.001); Family social capital significantly predicted academic performance (standardized regression coefficient=0.084, P < 0.01) and self-concept (standardized regression coefficient = 0.156, P < 0.001).ConclusionFamily capital can significantly affect the academic achievement of first-generation college students. To bridge the gap of academic achievement caused by family capital for first-generation college students and promote class mobility, special attention should be paid to the internal actions of students in higher education fields, the connection between different fields should be strengthened, and humanistic care for disadvantaged groups should be implemented.

This dataset consists of a selection of variables extracted from the U.S. Department of Education's College Scorecard 2015/2016. For the original, raw data visit the College Scorecard webpage. This dataset includes variables about institution types, proportion of degree types awarded, student enrollments and demographics, and a number of price and revenue variables. For 2005-2006 data, see here.Note: Data is not uniformly available for all schools on all variables. Variables for which there is no data (NULL), or where data is suppressed for reasons of privacy, are indicated by 999999999.

ATTRIBUTE DESCRIPTION EXAMPLE

ID2 1

UNITIDUnit ID for institution 100654

OPEID 8-digit OPE ID for institution 100200

OPEID6 6-digit OPE ID for institution 1002

State FIPS

1

State

AL

Zip

35762

City

Normal

Institution Name

Alabama A & M University

Institution Type 1 Public 2 Private nonprofit 3 Private for-profit 1

Institution Level 1 4-year 2 2-year 3 Less-than-2-year 1

In Operation 1 true 0 false 1

Main Campus 1 true 0 false 1

Branches Count of the number of branches 1

Popular Degree 1 Predominantly certificate-degree granting 2 Predominantly associate's-degree granting 3 Predominantly bachelor's-degree granting 4 Entirely graduate-degree granting 3

Highest Degree 0 Non-degree-granting 1 Certificate degree 2 Associate degree 3 Bachelor's degree 4 Graduate degree 4

PCIP01 Percentage of degrees awarded in Agriculture, Agriculture Operations, And Related Sciences. 0.0446

PCIP03 Percentage of degrees awarded in Natural Resources And Conservation. 0.0023

PCIP04 Percentage of degrees awarded in Architecture And Related Services. 0.0094

PCIP05 Percentage of degrees awarded in Area, Ethnic, Cultural, Gender, And Group Studies. 0

PCIP09 Percentage of degrees awarded in Communication, Journalism, And Related Programs. 0

PCIP10 Percentage of degrees awarded in Communications Technologies/Technicians And Support Services. 0.0164

PCIP11 Percentage of degrees awarded in Computer And Information Sciences And Support Services. 0.0634

PCIP12 Percentage of degrees awarded in Personal And Culinary Services. 0

PCIP13 Percentage of degrees awarded in Education. 0.1268

PCIP14 Percentage of degrees awarded in Engineering. 0.1432

PCIP15 Percentage of degrees awarded in Engineering Technologies And Engineering-Related Fields. 0.0587

PCIP16 Percentage of degrees awarded in Foreign Languages, Literatures, And Linguistics. 0

PCIP19 Percentage of degrees awarded in Family And Consumer Sciences/Human Sciences. 0.0188

PCIP22 Percentage of degrees awarded in Legal Professions And Studies. 0

PCIP23 Percentage of degrees awarded in English Language And Literature/Letters. 0.0235

PCIP24 Percentage of degrees awarded in Liberal Arts And Sciences, General Studies And Humanities. 0.0423

PCIP25 Percentage of degrees awarded in Library Science. 0

PCIP26 Percentage of degrees awarded in Biological And Biomedical Sciences. 0.1009

PCIP27 Percentage of degrees awarded in Mathematics And Statistics. 0.0094

PCIP29 Percentage of degrees awarded in Military Technologies And Applied Sciences. 0

PCIP30 Percentage of degrees awarded in Multi/Interdisciplinary Studies. 0

PCIP31 Percentage of degrees awarded in Parks, Recreation, Leisure, And Fitness Studies. 0

PCIP38 Percentage of degrees awarded in Philosophy And Religious Studies. 0

PCIP39 Percentage of degrees awarded in Theology And Religious Vocations. 0

PCIP40 Percentage of degrees awarded in Physical Sciences. 0.0188

PCIP41 Percentage of degrees awarded in Science Technologies/Technicians. 0

PCIP42 Percentage of degrees awarded in Psychology. 0.0282

PCIP43 Percentage of degrees awarded in Homeland Security, Law Enforcement, Firefighting And Related Protective Services. 0.0282

PCIP44 Percentage of degrees awarded in Public Administration And Social Service Professions. 0.0516

PCIP45 Percentage of degrees awarded in Social Sciences. 0.0399

PCIP46 Percentage of degrees awarded in Construction Trades. 0

PCIP47 Percentage of degrees awarded in Mechanic And Repair Technologies/Technicians. 0

PCIP48 Percentage of degrees awarded in Precision Production. 0

PCIP49 Percentage of degrees awarded in Transportation And Materials Moving. 0

PCIP50 Percentage of degrees awarded in Visual And Performing Arts. 0.0258

PCIP51 Percentage of degrees awarded in Health Professions And Related Programs. 0

PCIP52 Percentage of degrees awarded in Business, Management, Marketing, And Related Support Services. 0.1479

PCIP54 Percentage of degrees awarded in History. 0

Admission Rate

0.6538

Average RetentionRate of retention averaged between full-time and part-time students. 0.4428

Retention, Full-Time Students

0.5779

Retention, Part-Time Students

0.3077

Completion Rate

0.1104

Enrollment Number of enrolled students 4505

Male Students Percentage of the student body that is male. 0.4617

Female Students Percentage of the student body that is female. 0.5383

White Percentage of the student body that identifies as white. 0.034

Black Percentage of the student body that identifies as African American. 0.9216

Hispanic Percentage of the student body that identifies as Hispanic or Latino. 0.0058

Asian Percentage of the student body that identifies as Asian. 0.0018

American Indian and Alaskan Native Percentage of the student body that identifies as American Indian or Alaskan Native. 0.0022

Native Hawaiian and Pacific Islander Percentage of the student body that identifies as Native Hawaiian or Pacific islander. 0.0018

Two or More Races Percentage of the student body that identifies as two or more races. 0

Non-Resident Aliens Percentage of the student body that are non-resident aliens. 0.0062

Race Unknown Percentage of the student body for whom racial identity is unknown. 0.0266

Percent Parents no HS Diploma Percentage of parents of students whose highest level of education is less than high school. 0.019298937

Percent Parents HS Diploma Percentage of parents of students whose highest level of education is high school 0.369436786

Percent Parents Post-Secondary Ed. Percentage of parents of students whose highest level of education is college or above. 0.611264277

Title IV Students Percentage of student body identified as Title IV 743

HCM2 Cash Monitoring Schools identified by the Department of Ed for Higher Cash Monitoring Level 2 0

Net Price

13435

Cost of Attendance

20809

In-State Tuition and Fees

9366

Out-of-State Tuition and Fees

17136

Tuition and Fees (Program) Tuition and fees for program-year schools NULL

Tution Revenue per Full-Time Student

9657

Expenditures per Full-Time Student

7941

Average Faculty Salary

7017

Percent of Students with Federal Loan

0.8159

Share of Students with Federal Loan

0.896382157

Share of Students with Pell Grant

0.860906217

Median Loan Principal Amount upon Entering Repayment

14600

Median Debt for Completed Students Median debt for student who completed a course of study 35000

Median Debt for Incompleted Students Median debt for student who did not complete a course of study 9500

Median Debt for Family Income $0K-$30K Median debt for students of families with less thank $30,000 income 14457

Median Debt for Family Income $30K-$75K Median debt for students of families with $30,000-$75,000 income 15000

Median Debt for Family Income over $75K Median debt for students of families with over $75,000 income 14250

Median Debt Female Students

16000

Median Debt Male Students

13750

Median Debt 1st Gen. Students Median debt for first generation college student 14307.5

Median Debt Not 1st Gen. Students Median debt for not first generation college students 14953

Cumulative Loan Debt Greater than 90% of Students (90th Percentile)

48750

Cumulative Loan Debt Greater than 75% of Students (75th Percentile)

32704

Cumulative Loan Debt Greater than 25% of Students (25th Percentile)

5500

Cumulative Loan Debt Greater than 10% of Students (10th Percentile)

3935.5

Accrediting Agency

Southern Association of Colleges and Schools Commission on Colleges

Website

www.aamu.edu/

Price Calculator

www2.aamu.edu/scripts/netpricecalc/npcalc.htm

Latitude

34.783368

Longitude

-86.568502

In the context of continued equity gaps in student success within and beyond STEM, this paper explored the extent to which the representation of underrepresented racial minority (URM) and first-generation college students predict grades in postsecondary STEM courses. The analyses examined 87,027 grades received by 11,868 STEM-interested students within 8,468 STEM courses at 20 institutions. Cross-classified multilevel models and student fixed effect analyses of these data both support the same conclusion: the proportion of URM and first-generation students within a class is positively associated with STEM grades among all students, and these relationships are stronger among students who are members of the minoritized group. Thus, promoting the representation of students with minoritized identities in STEM courses may lead to greater equity in college outcomes.

This study details the mentored research component of a program intended to recruit, retain, and transfer students attending a two-year college (2YC) to four-year geosciences programs. Eighteen of 20 students who started the program were from minoritized backgrounds: 12 women, six racial/ethnic minorities, 12 low-income, and 13 first-generation college attendees. During a calendar year, students engaged in faculty-mentored research at a 4-year university (4YU), coursework at the 2YC, and a paid six-week internship in geoscience education. Students were to spend at least five hours weekly on research February-June and make a public presentation of results in December. Of 11 students who completed their research projects, 10 were minoritized students. Eight of 11 transferred into a science major. Students progressed the most in research when working together on a project designed for them and regularly meeting in-person with their mentors. Student exit interviews indicated that they valued the research experience and the skills gained. However, less progress occurred in the summer than planned, and students cited challenges in commuting to the 4YU due to jobs and personal commitments. Mentor-student matching produced mixed success. Based on the findings, we recommend incorporating a mini-internship with each mentor into the spring course, then pairing the students with one project and mentor for the summer and fall. Funding the research hours in addition to the internship would help alleviate financial burdens on students. Finally, all mentors would benefit from training together to better understand the mindsets of 2YC students and effectively accommodate individual needs.

Disparities remain in the representation of marginalized students in STEM. Classroom-based experiential learning opportunities can increase student confidence and academic success; however, the effectiveness of extending learning to outdoor settings is unknown. Our objectives were to examine 1) demographic gaps in ecology and evolutionary biology (EEB) major completion, college graduation, and GPAs for students who did and did not enroll in field courses, 2) whether under-represented demographic groups were less likely to enroll in field courses, and 3) whether under-represented demographic groups were more likely to feel increased competency in science-related tasks (hereafter, self-efficacy) after participating in field courses. We compared the relationships among academic success measures and demographic data (race/ethnicity, socioeconomic status, first-generation, and gender) for UC Santa Cruz undergraduate students admitted between 2008 and 2019 who participated in field courses (N=941 students) and who did not (N=28,215 students). Additionally, we administered longitudinal surveys to evaluate self-efficacy gains during field-based versus classroom-based courses (N=570 students). We found no differences in the proportion of students matriculating at the university as undecided, proposed EEB, or proposed other majors across demographic groups. However, five years later, under-represented students were significantly less likely to graduate with EEB degrees, indicating retention rather than recruitment drives disparities in representation. This retention gap is partly due to a lower rate of college completion and partly through attrition to other majors. Although under-represented students were less likely to enroll in field courses, field courses were associated with higher self-efficacy gains, higher college graduation rates, higher EEB major retention, and higher GPAs at graduation. All demographic groups experienced significant increases in self-efficacy during field-based but not lecture-based courses. Together, our findings suggest that increasing the number of field courses and actively facilitating access to students from under-represented groups can be a powerful tool for increasing STEM diversity.

Methods To evaluate self-efficacy gains during field courses, we administered longitudinal surveys in a subset of three courses between Fall 2016 and Spring 2019: (a) BIOE 20C, a gateway ecology and evolutionary biology lecture course (N=81); (b) BIOE 82, a 2-unit, lower-division field course that is intended to provide early field immersion and introduce natural history information and field research opportunities to students (N=194), and (c) CEC, an immersive 19-unit upper division field course that engages students in student-directed research projects (N=295). While BIOE 20C and BIOE 82 are courses offered at UCSC, CEC is a UC system-wide course that enrolls students from all UC campuses. We administered paired pre- (first week of the academic quarter) and post- (last week of the academic quarter) surveys. Each student was asked to rate their confidence on a 5-point Likert scale (1=Strongly Disagree, 2=Disagree, 3=Neither Agree Nor Disagree, 4=Agree, 5=Strongly Agree) for each of six questions: i) I am familiar with the flora, fauna, and ecosystems of California; ii) I have strong experimental design skills; iii) I have strong oral presentation skills; iv) I know how to conduct field research projects from start to finish; v) I am interested in pursuing a career in science; vi) I am interested in pursuing a graduate degree.

To quantify how the demographics of field courses have changed over time, we extracted historical demographic composition data from field courses taught between 2008 and 2019 (N=1,239 students; courses BIO75, BIO82, BIO128L, BIO151, BIO159, BIO161), and the gateway lecture course for EEB majors (N=11,589 students; BIO20C). Field courses were included if more than 50% of course hours were spent in the field rather than in the classroom and if the course had been taught for at least 4 years.

Academic success is not solely the result of cognitive ability. There is evidence that traits such as students' need for cognition (NFC) and self-efficacy beliefs influence academic success. Beyond cognitive ability and personal traits, social background constitutes an important factor. Students from academic households are (still) much more likely to pursue an academic degree than their peers from non-academic households. Past research on traits and beliefs relevant in (higher) education has focused on academic success, but only to a limited extent on its direct precursor: the decision to pursue an academic degree. This study aims to investigate NFC and academic self-efficacy (ASE) as positive predictors of students' intentions to go to college, with consideration of students' generational status regarding academic education. Results based on survey data from 1,389 German high school students provide evidence for positive relationships between NFC, ASE, and study intention, with ASE acting as a mediator of NFC's effect. Our analyses also investigate the effects of NFC and ASE on study intentions for students from academic as compared to students from non-academic households via multigroup analyses.

The aim of the research is to provide an empirically based understanding of the Net Generation as they enter university. The research uses a mixture of survey methods, interview and observation to achieve the following objectives: (1)To explore their attitudes, expectations and experience of e-learning at university; (2)To explore any linkages between their prior exposure to gaming and digital networked technology and their expressed attitudes towards and experience of e-learning; (3)To investigate the use of social software;(4)To develop the theoretical basis for understanding any generational changes; (5)To provide timely evidence based advice for policy makers, teaching staff and administrators. This research will aim to explore students coming from the Net generation as they first encounter e-learning at university. The Net Generation are distinct as they grew up with games and digital technologies. They are distinct in ways that have a relevance to teaching and learning, including questions related to attention span and information searching patterns. At the same time universities in the UK have been exploring a more extensive use of e-learning. The policy direction emphasizes learners’ needs and aspirations but we have little empirical evidence of the changing student population. The collection consists of Electronic/paper surveys (3), telephone interviews (80 interviewees, 79 interviews), cultural probe (involving 19 students) and 4 focus groups(4). Combination of one-time (Survey 1) and repeated study (Surveys 2 and 3). The collection contains both qualitative and quantitative data. Quantitative Data: Number of survey databases: 3. Survey 1 Database: 256 variables; 596 cases. Survey 2 Database: 124 variables; 1099 cases. Survey 3 Database: 127 variables; 716 cases. Qualitative Data: Interview transcripts: 79 documents (transcripts from 3 interviews attached); interview questions: 3 documents; cultural probe: 19 documents containing transcripts of videos and notebook entries; focus group transcripts: 4 documents. The studied population were 1st year students at 5 English universities and their staff. Number of students taking courses surveyed: 2415. Number of students interviewed: 68. Number of staff interviewed: 12.

This study is a qualitative research following a case studies design. I am using arts-informed methods such as drawings and photovoice (photographs) complemented by in-depth individual semi-structured interviews and field-notes from observations. I developed two stages of the data construction process which was conducted between May to October 2017.

I conducted my analysis on two levels considering the two research questions. In the case of the first research question, after using various coding methods of analysis, the data was examined to define codes, categories, themes (first generation), thematic categories (second generation of themes) and major themes to discuss. In the case of the second research question, a similar process was conducted as well as to define meta codes, outcomes, thematic categories and propose main themes to discuss the findings based on the two research questions. In the data constructed of both research questions, I followed a crystallization process.

This study used ATLAS.ti 8™ software and the following general research methods for data analysis: member reflections, reflecting with supervisor, denotation and connotation of drawings, and photovoice techniques.

BackgroundDespite decades of calls for increased diversity in the health research workforce, disparities exist for many populations, including Black, Indigenous, and People of Color individuals, those from low-income families, and first-generation college students. To increase representation of historically marginalized populations, there is a critical need to develop programs that strengthen their path toward health research careers. High school is a critically important time to catalyze interest and rebuild engagement among youth who may have previously felt excluded from science, technology, engineering, and mathematics (STEM) and health research careers.MethodsThe overall objective of the MYHealth program is to engage high school students in a community-based participatory research program focused on adolescent health. Investigators will work alongside community partners to recruit 9th through 12th graders who self-identify as a member of a group underrepresented in STEM or health research careers (e.g., based on race and ethnicity, socioeconomic status, first generation college student, disability, etc.). MYHealth students are trained to be co-researchers who work alongside academic researchers, which will help them to envision themselves as scientists capable of positively impacting their communities through research. Implemented in three phases, the MYHealth program aims to foster a continuing interest in health research careers by developing: 1) researcher identities, 2) scientific literacy, 3) scientific self-efficacy, and 4) teamwork and leadership self-efficacy. In each phase, students will build knowledge and skills in research, ethics, data collection, data analysis, and dissemination. Students will directly collaborate with and be mentored by a team that includes investigators, community advisors, scientific advisors, and youth peers.DiscussionEach year, a new cohort of up to 70 high school students will be enrolled in MYHealth. We anticipate the MYHealth program will increase interest and persistence in STEM and health research among groups that have been historically excluded in health research careers.