The review, conducted by Steve Springer Laryea of the GNAT Institute for Research and Industrial Relations Studies and Kumasi Technical University in Ghana, began with a Scopus search carried out on 1 April 2026 using predefined terms covering first-generation status, support, and higher education. That search returned 534 records. After applying limits to English-language journal articles published between 2000 and 2026, 400 records were retained. Title and abstract screening narrowed the pool to a focused, support-oriented core corpus, from which 76 studies were retrieved in full text. Ultimately, 56 empirical studies met the criteria for thematic synthesis. The methodological scaffolding followed established systematic review conventions, including the PRISMA 2020 reporting guideline and its PRISMA-S extension for literature searches, alongside the thematic synthesis approach developed by Thomas and Harden for aggregating qualitative findings.

Bibliometric profiling of the corpus revealed a field in rapid acceleration. Research output on first-generation student support has grown sharply since 2020, but it is also heavily concentrated in one national context: the United States dominates the evidence base to a striking degree. Studies from the United Kingdom, Germany, China, Chile, Ghana and other African contexts appear in the literature, but they remain comparatively rare. That geographic skew matters, the review argues, because the challenges facing a first-generation student at a selective American research university may differ in kind—not merely degree—from those facing a student who is the first in her family to attend university in rural Ghana, China, or Chile.

From the 56 studies, the thematic synthesis identified seven recurrent themes that together describe the support landscape: family and kin support; institutional programmes, mentoring and advising; psychosocial support, belonging and identity; social and cultural capital, information, and help-seeking; financial and structural supports or barriers; access and transition supports; and resilience and agency. These themes are not isolated silos. The review’s central conceptual claim is that effective support for first-generation students should be understood as a layered ecology, one that spans the family household, the secondary school, institutional agents within the university, financial structures, and the student’s own psychosocial validation. Pull any one layer out, and the whole structure weakens.

The family layer emerged as one of the most consistently documented in the corpus. Studies of Appalachian first-generation students in the United States, for example, traced how family involvement shaped postsecondary success, while research on Latino first-generation families examined the intragenerational bargains struck between siblings, in which one sibling’s college journey becomes a resource for the next. Other work has explored how parents’ memorable messages at graduation encode years of quiet sacrifice, and how the familial habitus—the accumulated dispositions of a household that has never navigated higher education—shapes aspirations long before an application form is ever filled in. Family support, the evidence suggests, is rarely a simple one-way transfer of encouragement; it is negotiated, sometimes strained, and often redefined as students become conduits of new knowledge back into their households.

Inside the university, the review found a rich literature on institutional programmes, mentoring and advising. Studies have documented how first-generation faculty and staff mentor first-generation students, how institutional agents at public urban universities promote success, and how mentoring relationships correlate with college enrollment through the social capital they transmit. Credit momentum policies such as the 15 to Finish initiative have been evaluated for their effects on low-income, first-generation students’ academic progression, while longitudinal work on technical college students has examined how financial aid interacts with first-generation status to shape academic performance. Accelerated learning combined with financial aid has been associated with reduced first-year outcome gaps between Hispanic first-generation students and their peers, pointing to the value of bundling interventions rather than deploying them piecemeal.

A third cluster of research concerns the psychosocial dimension: belonging, identity, and self-efficacy. Studies of first-generation students in honors talent programs have examined identity compatibility and its effects on belonging and confidence, while work on community college students of colour has shown that belongingness moderates the influence of student mindsets on outcomes. Research conducted during the COVID-19 pandemic documented the communicative resilience first-generation students deployed to stay enrolled under conditions of acute disruption. Help-seeking itself has come under scrutiny: qualitative analyses of first-generation students’ help-seeking attitudes, decisions, and behaviours reveal how deeply the decision to ask for help is entangled with questions of identity, pride, and the fear of confirming that one does not belong.

The social and cultural capital theme connects many of the others. First-generation students often arrive at university without the tacit knowledge—the unwritten rules of office hours, research opportunities, internships, and faculty relationships—that their continuing-generation peers absorb at home. Studies have examined how students develop social capital for the rigours of college-level research, how rural students navigate academic help-seeking, and how social networks shape career planning among first-generation and non-first-generation students in Germany. The review notes that across these themes, support was overwhelmingly relational in character: it flowed through people—parents, siblings, mentors, advisers, teachers—rather than through impersonal systems. Yet that relational support was frequently individualised, asking students to find, cultivate, and leverage relationships on their own, rather than being structurally transformative in ways that would redistribute advantage across the institution as a whole.

Financial and structural supports formed another critical layer, and the review is candid about the asymmetry in the evidence base. The corpus was weighted heavily towards post-entry persistence—what happens after students arrive on campus—with comparatively little attention to pre-entry support and the school-to-university transition, especially in the Global South. This is a significant gap. Studies of high school teachers’ awareness and preparedness in supporting first-generation students, of the high school–college disconnect in literacy preparation, and of college talk in rural economies all suggest that the decisive groundwork for first-generation success is laid years before matriculation. Research from Africa, including studies of what drives first-generation students’ resilience and what support systems exist in Ghanaian higher education, demonstrates both the feasibility and the urgency of extending the research agenda beyond the United States.

The review concludes with implications for policy, practice, and future research that follow directly from its layered-ecology framework. If support is relational but individualised, institutions should design structures that make supportive relationships systematic rather than accidental—embedding mentoring, advising, and belonging interventions into the architecture of the student experience rather than leaving them to chance encounters. If the evidence base is skewed towards post-entry persistence in one country, funders and researchers should prioritise intervention studies and geographic diversity, particularly pre-entry and transition research in the Global South where first-generation enrolment is expanding fastest. And if resilience and agency are repeatedly documented as student strengths, policy should build on those assets rather than framing first-generation students solely as deficits to be remediated. What emerges from 56 studies and a quarter-century of research is a picture of a field that has matured rapidly in volume but still needs to mature in reach—moving from cataloguing how remarkable individuals overcome the odds, to changing the odds themselves.

Subject of Research: Systematic review of support for first-generation students' access, transition, and success in higher education

Article Title: Supporting first-generation students’ access, transition, and success in higher education: a systematic review

Article References: Laryea, S. S. (2026). Supporting first-generation students’ access, transition, and success in higher education: a systematic review. Higher Education. https://doi.org/10.1007/s10734-026-01800-4

Image Credits: AI Generated

DOI: 10.1007/s10734-026-01800-4

Keywords: first-generation students, higher education, systematic review, thematic analysis, social capital, student persistence, mentoring, belonging, educational equity, transition support, Global South, education policy

The central finding is deceptively simple but consequential for how educators and policymakers think about diversity in higher education. In male-majority fields such as physics, engineering, computer science, business, and economics, straight cisgender men with lower-than-average high-school grades and test scores were substantially overrepresented compared with straight cisgender women who had similar levels of academic performance. Among students at the top of the achievement distribution, that gap narrowed dramatically. In other words, the familiar underrepresentation of women in quantitative and technical fields is driven disproportionately by what happens to students with weaker academic credentials, not by a uniform filtering process that operates equally at every level of preparation.

Lead author Joseph Cimpian, professor of economics and education policy at NYU Steinhardt and NYU Wagner, emphasized that this heterogeneity is easy to miss if researchers only examine overall representation rates. Across both datasets, he and his colleagues found that when a representation gap varied across the achievement distribution, that gap tended to favor the major’s historically dominant demographic group most strongly among students with lower pre-college grades and test scores, and least so at other points in the distribution. Those gaps narrowed considerably among students with the strongest pre-college performance. Cimpian argued that looking closely at how gaps differ by achievement level, rather than relying on aggregate statistics, is essential for understanding who is actually entering these different fields—and who is being screened out or discouraged before they ever arrive.

The methodological foundation of the study is one of its distinguishing strengths. The researchers analyzed the High School Longitudinal Study of 2009, which followed 6,340 students from their first year of high school in 2009-2010 through their junior year of college, capturing demographic information including sex and LGBTQ+ identity alongside measures of academic preparation, interests, and outcomes. They complemented this with the Baccalaureate and Beyond Longitudinal Study of 2016, which provided academic and demographic data for 12,950 students who earned a bachelor’s degree in 2016. Using two independent, nationally representative datasets allowed the team to test whether the same patterns emerged in different cohorts and at different stages of the college pipeline, from initial major selection through persistence to degree completion.

Crucially, the study is among the first to use nationally representative data to examine how LGBTQ+ students sort across the full range of college majors, not just the STEM disciplines that have dominated conversations about demographic disparities. The results showed that LGBTQ+ students, regardless of sex, were underrepresented in male-majority fields such as engineering, computer science, and business. LGBTQ+ men were also underrepresented in nursing and other health fields—a finding that mirrors, in reverse, the pattern of straight cisgender women being underrepresented in male-dominated technical majors. The consistency of these across-group patterns suggests that the dynamics shaping who enters and stays in a major operate along multiple demographic dimensions simultaneously, not solely along the lines of gender.

In female-majority fields, the evidence for a parallel pattern of overrepresentation among straight cisgender women was mixed, and the authors are careful not to overstate symmetry between the two directions of the analysis. However, some statistical models revealed a striking result: LGBTQ+ women tended to be overrepresented in female-majority fields among students with the highest pre-college achievement. The researchers interpret this cautiously, but it raises the possibility that LGBTQ+ women may need stronger academic credentials to gain a foothold even in fields that might superficially appear welcoming to them. If confirmed by future work, this would suggest that the barriers facing sexual and gender minority students are not confined to traditionally hostile environments but extend into disciplines where their demographic group holds numerical dominance.

What might explain why representation gaps are sharpest among students with weaker academic credentials? The researchers point toward social norms and institutional environments that subtly favor a field’s historically dominant demographic group. Students with lower grades and test scores may have less margin for error when navigating environments where they are demographically outnumbered: they may receive less encouragement, face harsher judgment when they struggle, or perceive fewer role models and fewer signals that people like them succeed in the field. High-achieving students, by contrast, may possess a kind of buffer—strong credentials, confidence, and external validation—that allows them to persist even in environments that are less than fully welcoming. The study is correlational, and the authors explicitly note that it cannot establish that these norms directly cause the observed gaps; it demonstrates only that individual academic and demographic factors on their own do not fully account for the patterns in the data.

That caveat matters, but it does not diminish the study’s practical implications. If prior performance alone cannot explain who stays in a major and who leaves, then interventions focused exclusively on academic preparation—tutoring, prerequisite pipelines, admissions criteria—are unlikely to close representation gaps on their own. The findings point instead toward the climate of departments and classrooms, particularly for students who arrive with less academic capital and therefore less resilience against discouragement. They also suggest that aggregate diversity statistics may mask the true geography of exclusion. A department that appears moderately diverse overall may, in fact, be nearly homogeneous among its less-prepared students, with demographic diversity concentrated only among those strong enough to overcome environmental headwinds.

Cimpian framed the results as a story of missed opportunity rather than simple loss. If talented students are leaving—or never entering—majors where they would do well and contribute, partly based on factors unrelated to their preparation or even their interest in those fields, that is a loss both for the students themselves and for the disciplines they might have enriched. The phrase ‘unrelated to their preparation or even interest’ is the study’s sharpest edge: it implies that the conventional explanations for demographic sorting, which center on ability and preference, are incomplete. Something in the environment surrounding a major appears to interact with a student’s demographic identity and achievement level to shape whether that student completes a degree in the field.

The research, co-authored by Zachary T. McDermott at Abt Global, Jo R. King at Boston University, Nathaniel Woznicki at the NYU Department of Psychology, and Taek H. Kim at the Korean Educational Development Institute, was supported by grants from the Institute of Education Sciences at the US Department of Education. Its publication in Nature Human Behaviour reflects growing scientific interest in moving beyond binary questions of whether demographic gaps exist toward more granular questions of where, for whom, and under what conditions those gaps emerge. For universities seeking to diversify engineering, computer science, nursing, education, and every field in between, the message is that the students most at risk of exclusion are not the strongest performers but those with the least academic cushion—and that the environments those students encounter, not just the students themselves, may be the most promising target for change.

Subject of Research: Demographic representation and persistence across college majors by achievement level

Article Title: Students with lower grades and test scores earn degrees more often when they belong to an academic major’s majority group

Article References: Students with lower grades and test scores earn degrees more often when they belong to an academic major’s majority group. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: higher education, college majors, gender representation, LGBTQ+ students, STEM diversity, academic achievement, degree completion, Nature Human Behaviour, longitudinal study, education policy, student persistence, NYU

The research was conducted by fellows and scholars affiliated with the University’s Center for Educational and Instructional Technology Research, known as CEITR, which is housed within the University of Phoenix College of Doctoral Studies. The author team includes Melinda Kulick, Jessica Sylvester, Chunfu Cheng, Christina Bergren and Jim Croushore, each of whom brings a practitioner background in assessment, higher education operations, research methodology, counseling and school leadership. Their article, titled “Designing for Persistence in Online Higher Education: A Trauma-Informed, GenAI-Integrated Model for Non-Traditional Learners,” introduces a conceptual framework intended to translate qualitative findings into actionable institutional design principles.

Methodologically, the study is a descriptive phenomenological investigation of 45 undergraduate students enrolled in six bachelor’s programs within the College of Social and Behavioral Sciences at a large U.S. online university. Participants ranged in age from 18 to 51 and older, with most between 36 and 50, and represented the varied employment, caregiving and prior educational experiences commonly associated with non-traditional online learners. The researchers used purposive sampling to recruit participants and collected data through an anonymous online questionnaire with open-ended prompts exploring stress, self-regulation, resilience, belonging, psychological safety and GenAI use. Respondents could answer in writing or by audio, an accommodation that itself reflects attention to accessibility.

Analysis followed Colaizzi’s descriptive phenomenological method, a structured qualitative approach in which researchers identify significant statements, extract their meanings and organize them into thematic clusters. Five themes emerged from the data, and these themes informed the development of the study’s central contribution, the Trauma-Informed AI Persistence Model, abbreviated as TIAIP. Importantly, the study did not assess specific trauma histories or clinical diagnoses. Instead, it examined participant experiences involving stresses such as financial pressure, caregiving responsibilities, employment instability and competing life demands, treating trauma-informed practice as a design lens rather than a clinical category.

The findings paint a vivid picture of how chronic stress reshapes cognitive capacity. Participants described how ongoing stress and competing responsibilities eroded concentration, problem-solving and their ability to engage fully in academic work. One participant explained that stress creates significant brain fog, noting that when stressed, the ability to problem solve diminishes incredibly. Another described the strain of managing school, work and a household simultaneously, saying it detracts from the ability to fully engage in academic work. These accounts align with established research on cognitive load, which holds that working memory is a limited resource and that regulatory demands from chronic stress consume capacity that would otherwise support learning tasks.

Course design emerged as a decisive factor in whether that limited capacity was spent learning or merely coping. Participants reported that unclear instructions, inconsistent course organization and difficulty knowing where to begin increased cognitive strain and made task initiation harder. Conversely, small acts of instructional acknowledgment carried outsized weight. One participant recalled that when an instructor acknowledged how hard it is to juggle everything, they felt seen, and it made them want to stay engaged. The researchers found that trauma-related regulatory strain intensified the cognitive demands associated with course navigation, pacing expectations and limited instructional presence, while belonging and psychological safety consistently supported engagement. In other words, the emotional climate of a course and its structural clarity are not separate concerns but intertwined determinants of whether students persist.

Generative artificial intelligence occupied a nuanced position in the findings. Participants described GenAI as a situational support that could reduce overwhelm and help them initiate academic tasks during periods of acute stress. One student said that when their brain is overloaded, AI helps them get started and takes away the panic of a blank page. Another explained that when feeling overwhelmed by an assignment or unsure where to start, AI helps break things down into smaller, manageable steps, providing structure that reduces stress and yields a clearer plan of action. These accounts position GenAI as a kind of cognitive scaffold for task initiation, the phase of academic work that participants identified as most vulnerable to regulatory strain.

Yet the same participants raised pointed concerns about AI dependency and unclear ethical boundaries around its use for learning. The study does not present GenAI as a replacement for human support or student thinking. As co-author Jessica Sylvester, a senior manager of College Operations, associate faculty and CEITR research fellow, put it, the more useful question is how institutions can create the conditions in which technology serves as an intentional scaffold alongside clear expectations, thoughtful course design and meaningful human connection. That, she noted, requires helping students understand both what these tools can support and where their limitations and ethical boundaries lie. The framing treats GenAI as a conditional support whose benefits depend on institutional guidance rather than an autonomous solution.

Building on the five themes, the authors introduce the TIAIP Model as a conceptual framework integrating trauma science, online learning design and guided GenAI use. The model positions student persistence in online higher education as an institutional outcome shaped by the interaction of trauma-related demands, digital course architecture and structured AI integration. It addresses how regulatory strain can intensify the cognitive demands of course navigation, pacing and limited instructional presence, while belonging and psychological safety influence engagement. In practice, TIAIP encourages institutions to reduce unnecessary barriers to persistence through clearer course structures, supportive instructional presence, deliberate attention to belonging and psychological safety, and purposeful guidance for GenAI use. Kulick, an assessment manager, associate faculty in the College of Doctoral Studies and CEITR research fellow, summarized the implication: for students managing work, family responsibilities and other pressures alongside their education, persistence cannot be understood simply as a matter of motivation or individual resilience. The findings, she said, point to the importance of designing online learning environments that reduce unnecessary cognitive demands, strengthen students’ sense of connection and give learners appropriate support for navigating moments when demands become especially high.

The authors are candid about the study’s limits. The findings provide context-specific qualitative insights from students at one online university and should not be generalized to all higher education populations. The research relied on self-reported experiences, and the open-ended questionnaire offered less opportunity for follow-up probing than interviews would have. Findings were not analyzed by intersecting demographic identities, and the TIAIP Model is a preliminary conceptual framework derived from the qualitative findings that requires further study and validation across institutions and learner populations. Even so, the study arrives at a moment when universities are simultaneously confronting rising numbers of non-traditional learners and the rapid, often unregulated arrival of generative AI in classrooms. By connecting trauma-informed pedagogy, digital course architecture and guided AI use within a single model, the researchers offer institutions a testable hypothesis: that persistence is designed, not merely demanded, and that technology, when bounded by clear ethical and instructional guardrails, can help students begin the work that stress once made impossible.

Subject of Research: Trauma-informed online learning design and generative AI support for non-traditional student persistence

Article Title: Study on trauma-informed online learning and GenAI support for student persistence published by University of Phoenix researchers

Article References: Study on trauma-informed online learning and GenAI support for student persistence published by University of Phoenix researchers. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: online learning, student persistence, trauma-informed pedagogy, generative AI, cognitive load, psychological safety, belonging, non-traditional learners, higher education, qualitative research, instructional design, self-regulation

The study, led by Joel R. Sintos and Kristian B. Macabenta of Samar State University, used a sequential explanatory mixed-methods design that combined a near-complete census of the department’s undergraduates with open-ended narrative feedback. The response rate was an exceptional 98.5 percent, giving the team an unusually complete picture of a single institutional population. Their central finding is what they call the “Senior Year Surge”: fourth-year students reported significantly higher academic engagement, motivation, self-efficacy, and career confidence than underclassmen, and this surge occurred regardless of whether a student had originally wanted to study statistics at all.

Statistically, the evidence for the surge is robust. A one-way Multivariate Analysis of Variance across the four year levels produced a highly significant omnibus effect on the combined experiential dimensions, with Pillai’s Trace equal to 0.15, F(12, 771) = 3.48, p < .001. The researchers deliberately selected Pillai’s Trace because of its resilience to minor violations of homogeneity of variance-covariance matrices, which Box’s M test flagged as marginally problematic. A follow-up 4 × 2 factorial analysis of variance then delivered the study’s most consequential result: while year level had a significant main effect on engagement, F(3, 254) = 6.81, p < .001, the main effect of enrollment status was essentially zero, F(1, 254) = 0.05, p = .821, and the interaction between the two was non-significant, F(3, 254) = 1.31, p = .272. In plain terms, the trajectory of commitment across the degree was parallel for voluntary and involuntary entrants alike.

The descriptive data also revealed a non-linear path that the authors describe as a “Third-Year Dip.” Mean scores for engagement, motivation and self-efficacy, and institutional belongingness all declined from first year through third year, bottoming out as students confronted the program’s most demanding coursework, before rising sharply in the fourth year. Career perception was the lone exception, remaining comparatively stable across the middle years before climbing in the final stage. This pattern suggests that the middle of the program is where the psychological cost of the curriculum peaks, and that the recovery is driven less by growing affection for the department than by the approaching finish line.

That interpretation is supported by the correlation structure of the data. Using Spearman’s rank correlations, the team found that motivation and self-efficacy shared the strongest association with active engagement (ρ = 0.45), followed by career perception (ρ = 0.34), with all inter-dimensional relationships positive and significant at p < .001. Institutional belongingness, the construct that dominates much of the Western persistence literature, ranked lowest. This is a pointed challenge to models derived from Vincent Tinto’s institutional integration framework and Alexander Astin’s involvement theory, which position social belonging as the primary engine of retention. In this resource-constrained setting, belonging appeared to be a secondary concern rather than a survival mechanism.

The qualitative phase, drawing on 122 respondents who provided open-ended feedback until conceptual saturation was reached, explains why. The first major theme was what students themselves called “math pain.” Calculus, integral calculus, and mathematical statistics were repeatedly named as sources of acute cognitive and emotional distress. One freshman reported feeling constant pressure in mathematics classes because the topics presented were unfamiliar, while another admitted that succeeding academically depended on being given the chance to shift to a preferred program. This localized anxiety aligns with prior Philippine research showing that mathematics-specific fear suppresses engagement unless buffered by deliberate instructional intervention.

The second theme was material precarity, and it may be the study’s most distinctive contribution. Upper-level students described an acute shortage of laptops and reliable computational hardware just as the curriculum shifted into statistical software environments such as R and Python. For these students, the lack of a functioning machine transformed academic stress from a cognitive problem into an infrastructure crisis. One third-year student described difficulties producing presentations and documented outputs without a personal gadget, and a graduating senior framed college survival as inseparable from surviving poverty. The authors argue that when hardware access gates every laboratory requirement, the desire for institutional connection is logically displaced by what they term “pragmatic survival,” which helps explain why belongingness failed to predict engagement in the quantitative models.

The third theme, career-driven resilience, provides the mechanism behind the Senior Year Surge. As graduation approached, students reframed the entire degree as a calculated investment in socio-economic mobility. Seniors cited the demand for data scientists and analysts, the prospect of higher earnings, and the versatility of statistical skills across working environments as the forces that carried them through. One fourth-year respondent explicitly connected the profession’s market demand to personal motivation, while another anchored persistence in family sacrifice and diligence despite self-perceived weakness in mathematics. The authors interpret this through the goal-gradient hypothesis: as the temporal distance to a high-value goal shrinks, motivation intensifies, converting external regulation into identified, autonomous drive in the language of Self-Determination Theory.

From these converging strands the researchers built the Statistics Student Success Framework, a three-pillar institutional model. Pedagogical scaffolding addresses math anxiety through sequential instruction and early computational successes; technical-financial equity targets direct access to laptops, software licenses, and laboratory infrastructure; and career-value integration introduces discipline-specific career pathing and industry mentorship in the very first semester, so that involuntary enrollees can reconstruct their academic identity years before the natural senior-year pivot. Institutional belongingness and social support remain as a foundational base, redefined less as social integration than as a structural safety net.

The practical implications are direct. The authors recommend that educators pair abstract proofs with immediate software application to lower anxiety, that departments showcase lucrative data-career trajectories from the freshman semester onward, and that administrators shift funding from social programming toward laptop lending schemes and campus-wide statistical software access, since material equity, not community feeling, proved to be the binding constraint. The study’s limitations are acknowledged: it is cross-sectional, single-institution, and situated in the Eastern Visayas, so longitudinal tracking from involuntary enrollment through professional employment and comparative studies in data science, actuarial mathematics, and applied economics are the logical next steps. Even so, the core message stands out as genuinely counterintuitive. Initial interest, the factor that admissions systems and families agonize over, turned out to be nearly irrelevant to long-term commitment. What mattered was whether the institution could manage the pain of the curriculum, supply the tools of the trade, and keep the professional prize visibly in sight. An accidental enrollment, the authors conclude, can be structurally transformed into an intentional professional victory.

Subject of Research: Academic engagement and persistence among involuntarily enrolled undergraduate statistics students in the Philippines

Article Title: Academic engagement and resilience in undergraduate statistics programs with high involuntary enrollment

Article References: Sintos, J. R., & Macabenta, K. B. (2026). Academic engagement and resilience in undergraduate statistics programs with high involuntary enrollment. Discover Education, 5(1), Article 1144. https://doi.org/10.1007/s44217-026-02255-6

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02255-6

Keywords: statistics education, academic engagement, involuntary enrollment, math anxiety, self-efficacy, career perception, student persistence, higher education, Philippines, mixed methods, resilience, self-determination theory

RACE21, funded by the National Cancer Institute through its Youth Enjoy Science initiative, was designed to fill a well-documented gap. Historically, cancer workforce development has concentrated on graduate and professional students, leaving undergraduates with little exposure to oncology research before they commit to a career path. The program, run through UAB’s Center for Community OutReach Development in partnership with the O’Neal Comprehensive Cancer Center and the university’s Cancer Biology undergraduate major, set out to change that by offering year-round, multi-year mentored research experiences rather than the short summer internships that dominate the field.

The numbers from the program’s first five years are striking. RACE21 recruited 78 undergraduate students, of whom 51 have already graduated, achieving a 98.5 percent graduation rate that far exceeds the national four-year institutional average of roughly 52 percent. Scholars worked across 43 faculty-led laboratories spanning 23 clinical and research departments, delivered more than 100 presentations at local, national, and international scientific meetings, and co-authored 53 peer-reviewed publications. Approximately 80 percent of alumni are now continuing their education in graduate school, medical training, or positions in cancer research or healthcare.

Recruitment itself became a lesson in how scientific talent finds its way into the pipeline. The program cast a wide net through academic advisors, honors college directors, student organizations such as the Minority Association of Pre-Health Students and the Black Undergraduate Medical Association, campus flyers, and social media. Yet by the second year, word-of-mouth referrals from current participants had emerged as the single most effective recruitment strategy, a finding consistent with research showing that peer relatedness and social support shape persistence in STEM. Applicants submitted transcripts, recommendation letters, and personal statements describing their goals in areas ranging from basic cancer mechanisms to epidemiology and clinical oncology.

Selection favored students with a GPA of 3.5 or higher, clear professional goals, and evidence of community engagement, though prior research experience was not required. Once admitted, trainees were matched individually with mentors based on their stated interests, and mentors were vetted for active funding, recent publications, and mentoring track records. Trainees could reapply annually for up to four years, with each year building on the last: foundational engagement during the pandemic-constrained first year, introduction to research culture and the BioBridge outreach camp in year two, financial literacy and scientific communication in year three, and leadership, entrepreneurship, and advanced research in years four and five.

The technical skills students acquired read like a syllabus for modern cancer biology. Participants described hands-on experience with cell culture, animal models, flow cytometry, immunohistochemistry, Western blotting, gel electrophoresis, and computational and bioinformatics approaches. Just as importantly, they learned that science is iterative. One scholar noted that repeating Western blot experiments helped them get better results after each attempt, while another reflected that even when projects fail, they still love research enough to keep trying. That resilience, the evaluation found, is as much a workforce competency as any laboratory technique.

The program’s quantitative evaluation relied on a mixed-methods design with careful statistical treatment. Attitudes toward cancer biology research were measured with a ten-item scale adapted from a validated survey, and because the scores were ordinal and non-normally distributed, the analysts used Wilcoxon signed-rank tests with rank-biserial correlations as effect sizes and bias-corrected bootstrap confidence intervals. Among 27 matched pre-post pairs, total attitude scores rose significantly, with a large effect size of 0.51. When items were grouped by construct, the strongest gains appeared in Interest, with moderate-to-large shifts in perceived Value and Self-Efficacy, while Commitment changed least, largely because students arrived already deeply committed, producing ceiling effects that limited measurable growth.

Community outreach proved to be an unexpected engine of professional development. RACE21 scholars facilitated BioBridge, Alabama’s first summer STEM camp focused on cancer biology for rising ninth-grade students, reaching more than 170 teenagers. An analysis of 50 open-ended reflections from four cohorts, summarized in a word cloud of the most frequent terms, revealed seven dominant themes: student engagement, teaching and learning, mentorship and leadership, STEM content, communication skills, impact, and program identity. Scholars reported that explaining cancer biology to fourteen-year-olds sharpened their ability to translate complex science for public audiences, a competency the program’s leaders now consider important enough to make mandatory for future trainees.

Mentorship operated at multiple levels simultaneously. Faculty research mentors guided experimental design and career development, program staff provided advising, and a near-peer structure allowed senior undergraduates to support newer ones, a culture students described as tight-knit and uplifting. All surveyed scholars from the third and fourth cohorts reported enjoying their work with faculty mentors, and 97 percent agreed they had sufficient mentor support to accomplish their research goals. Alumni have gone on to medical school, doctoral programs, NIH post-baccalaureate fellowships, dental and optometry schools, and research positions, with several earning Goldwater and Fulbright awards along the way.

The authors are candid about limitations. Selection bias is inherent in a program admitting high-GPA applicants who often arrive with strong science identities, and the adapted attitude scale, while internally consistent, has not undergone full psychometric validation; ceiling effects constrained what the rating scales could detect. Non-significant findings, they caution, should not be read as absence of program influence but as a sign that highly motivated students leave little room on the scale. The deeper lesson may be that for students already inclined toward science, the decisive ingredient is sustained, authentic exposure: longitudinal mentorship, real publications, real conferences, and the chance to teach the next generation. As a scalable model for building the cancer workforce of 2035 and beyond, RACE21 makes a compelling case that the pipeline should begin far earlier than graduate school.

Subject of Research: Evaluation of the RACE21 undergraduate cancer research and education training program at the University of Alabama at Birmingham

Article Title: Building the cancer research workforce through implementation of the RACE21 undergraduate cancer research and education program

Article References: Johnson, M. S., Haynie, K. C., Shevde, L. A., & Wyss, J. M. (2026). Building the cancer research workforce through implementation of the RACE21 undergraduate cancer research and education program. Discover Education, 5(1), Article 1127. https://doi.org/10.1007/s44217-026-02251-w

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02251-w

Keywords: cancer research, RACE21, undergraduate education, STEM workforce, mentorship, Youth Enjoy Science, National Cancer Institute, science communication, BioBridge, health disparities, student persistence, UAB