Student Attrition Research Articles

Characterizing the Identity Formation and Sense of Belonging of the Students Enrolled in a Data Science Learning Community

Student attrition is a challenge experienced by higher education institutions. One of the key reasons for student attrition is the inability of students to develop an identity and a sense of belonging. This study aims to understand the role of a data science learning community in helping students to develop identity and a sense of belonging. The study used a mixed-methods approach to collect and analyze the data. The study used a pre–post survey to understand students’ perceptions regarding identity formation and sense of belonging. The results of the survey study indicated that the perception of identity formation and sense of belonging increased as students progressed through the semester. To further investigate the reasons for the increase in the perception of identity formation and sense of belonging, in-depth semi-structured interviews were conducted. The results of the interview revealed that living in the data science learning community, participating in various events and interacting with faculty, staff and working with peers of similar interest helped students to develop a data science identity and leader identity, as well as experience sense of belonging.

Predicting Student Attrition in Higher Education through the Determinants of Learning Progress: A Structural Equation Modelling Approach

Higher education policies are designed to facilitate students’ learning progression and academic success. Following Tinto’s integration theory and Bean’s attrition model, this study proposes a research model to investigate whether students prone to attrition can be pre-emptively identified through self-evaluating academic factors contributing to their learning progress. Theoretically, the learning progress is identified with student success, represented by factors amenable to intervention including the interaction with peers and instructors, teaching effectiveness, exam scores, absenteeism, students’ effort, and academic course-related variables. An exploratory and confirmatory factor analysis of 530 undergraduate students revealed that the indicators of learning progress in such students were channeled into two constructs. The results indicated that the teacher effectiveness and learning materials contributed most to the learning progress. Structural equation modelling revealed that the learning progress variables have a significant impact on students’ attrition status. A multi-group analysis confirmed the academic semesters to be a moderator in the mediating effects of the students’ grade point average (GPA). This model functions as a framework to design a student-oriented learning system promoting students’ learning experience and academic success.

Identifying Prerequisite Courses in Undergraduate Biology Using Machine Learning

Many undergraduate students who matriculated in Science, Technology, Engineering and Mathematics (STEM) degree programs drop out or switch their major. Previous studies indicate that performance of students in prerequisite courses is important for attrition of students in STEM. This study analyzed demographic information, ACT/SAT score, and performance of students in freshman year courses to develop machine learning models predicting their success in earning a bachelor’s degree in biology. The predictive model based on Random Forest (RF) and Extreme Gradient Boosting (XGBoost) showed a better performance in terms of AUC (Area Under the Curve) with more balanced sensitivity and specificity than Logistic Regression (LR), K-Nearest Neighbor (KNN), and Neural Network (NN) models. An explainable machine learning approach called break-down was employed to identify important freshman year courses that could have a larger impact on student success at the biology degree program and student levels. More important courses identified at the program level can help program coordinators to prioritize their effort in addressing student attrition while more important courses identified at the student level can help academic advisors to provide more personalized, data-driven guidance to students.

“They Helped Me to Get Through”: Investigating Institutional Sources of Support at Two-Year Colleges that Facilitate the Transfer and Persistence of Black Engineering Students

Introduction: While a considerable amount of extant scholarship describes the importance of and strategies for improving the postsecondary pathways of Black engineering students, most literature is contextualized within 4-year institutions. Objectives: The purpose of this article is to illuminate Black engineering students’ experiences at community colleges in order to understand ways in which they engage different types of 2-year institutional support. Methods: We draw from data obtained through a series of focus groups and interviews facilitated between fall 2018 and fall 2019 with 13 engineering undergraduates. Results: Findings include evidence of important connections with faculty at 2-year colleges, such as positive engagement with them inside the classroom, as well as during office hours and general advising. In addition, we describe support from academic advisors regarding transfer pathways, as well as from campus staff who helped identify scholarships or other valuable resources on campus. Conclusion: We offer implications and conclusions that highlight the tremendous capacity of community colleges to support and educate future Black engineers. We also discuss the significance of underrepresented students of color working closely with faculty, adding that research to date notes that these interactions often tenuous for underrepresented racial and ethnic minorities. Finally, we discuss ways in which our results can inform the broader landscape of undergraduate engineering education, which—like other STEM fields—has often created unwelcoming and competitive environments that lead to student attrition for students from all demographic backgrounds.

Ten simple rules for creating and sustaining antiracist graduate programs.

In 2020, the combination of police killings of unarmed Black people, including George Floyd, Breonna Taylor, and Ahmaud Arbery, and the Coronavirus Disease 2019 (COVID-19) pandemic brought about public outrage over long-standing inequalities in society. The events of 2020 ignited global attention to systemic racism and racial inequalities, including the lack of diversity, equity, and inclusion in the academy and especially in science, technology, engineering, mathematics, and medicine (STEMM) fields. Racial and ethnic diversity in graduate programs in particular warrants special attention as graduate students of color report experiencing alarming rates of racism, discrimination, microaggressions, and other exclusionary behaviors. As part of the Graduate Dean’s Advisory Council on Diversity (GDACD) at the University of California Merced, the authors of this manuscript held a year-long discussion on these issues and ways to take meaningful action to address these persistent issues of injustices. We have outlined 10 rules to help graduate programs develop antiracist practices to promote racial and ethnic justice, equity, diversity, and inclusion (JEDI) in the academy. We focus on efforts to address systemic causes of the underrepresentation and attrition of students from minoritized communities. The 10 rules are developed to allow graduate groups to formulate and implement rules and policies to address root causes of underrepresentation of minoritized students in graduate education.

Student attrition: what’s happening with the COVID-19 cohort?

A Nursing Standard investigation shows 33% of those who began degree courses in 2018 did not graduate in 2021, as the pandemic and cost of living added to pressures

Visualizing and predicting the path to an undergraduate physics degree at two different institutions

Student attrition from a physics degree occurs differently at different types of institutions; each physics department needs to explore their own data to understand the points where there is an opportunity to improve retention.

At the intersection of human and algorithmic decision-making in distributed learning

This article seeks to explore different combinations of human and Artificial Intelligence (AI) decision-making in the context of distributed learning. Distributed learning institutions face specific challenges such as high levels of student attrition and ensuring quality, cost-effective student support at scale using a range of technologies, such as AI. While there is an expanding body of research on AI in education (AIEd), this conceptual article proposes that combinations of human-algorithmic decision-making systems need careful and critical consideration, not only for their potential, but also for their appropriateness and ethical considerations. We operationalize a framework designed to consider robot autonomy at four key events in students’ learning journeys, namely (1) admission and registration; (2) student advising and support; (3) augmenting pedagogy; and (4) formative and summative assessment. We conclude the article by providing pointers for operationalizing options in human-algorithmic decision-making in distributed learning contexts.

Contextualization of an Introductory Physiology Course to Address Student Disengagement during Remote Learning in Aotearoa

Extended periods of population lockdown during the Covid-19 pandemic required many university courses to be delivered completely online, and for a student, this can lead to feelings of isolation, disconnectedness, and disengagement. This article proposes a hypothetical modification to an undergraduate course in physiology to address possible student disengagement when studying remotely. Through contextualisation, the delivery of course content is made relevant to everyday life experiences in Aotearoa (New Zealand)—this approach may improve retention of material and sustain interest in the course. Four scenarios are presented which align physiology content with information sources that present a context relevant to the lived experience in Aotearoa. Each scenario’s learning outcomes, course content, and assessment are constructively aligned, consistent with current pedagogical practices in course design. It is suggested that adopting this contextualisation approach may increase the likelihood of student course completion, reduce student attrition, and increase student engagement during periods of extended remote learning. Further, it is suggested that using contextualisation presents an opportunity to redesign a higher education course to focus more on the relevance of academic material to the real-world lived experiences of students.

Peer-mentoring and doctoral student retention: a longitudinal investigation

ABSTRACT Many doctoral students do not finish their studies. Social support has been shown to lower the likelihood of student withdrawal. I propose peer-mentoring as one of the practices that makes a significant difference in doctoral student attrition. In this longitudinal study, I investigated the influence of peer-mentoring on students’ motivation and retention. Data were collected four times from 35 participants (a total of 140 surveys) in a Canadian university, where senior doctoral candidates mentored first year doctoral students. Data analysis indicates that students who received high levels of peer-mentoring experienced both steady and high autonomous motivation for their studies and low intention to leave. Implications for theory and practice are discussed.

Rethinking Higher Education Unit Design: Embedding Universal Design for Learning in Online Studies

Inclusive education in Australia has resulted in a concerted push for the differentiation of pedagogical teaching approaches by educators across Kindergarten to Year 12 (K-12) learning environments. Such approaches have been shown to meet a diverse range of learner needs found in today's classrooms. While progress is evident at the primary and secondary levels of education, implementing effective inclusive practices in higher education appears stagnant. Utilising the principles of Universal Design for Learning (UDL) in a fully online pre-service teacher training unit, multiple means of representation of the learning content and multiple means of engagement were explicitly incorporated into the online unit design. This approach aimed to proactively support the engagement of all students in an online teaching and learning environment. This study provides preliminary evidence that the application of UDL principles resulted in higher levels of student engagement and lower rates of student attrition.

Exploring support strategies for improving nursing student retention.

Nursing student attrition is a significant concern in many countries, including the UK. Higher education institutions (HEIs) are seeking creative ways of improving retention and it is crucial to understand which support strategies encourage students to persist with their studies. This article describes a systematic review of the literature exploring nursing students' experiences and perceptions of support strategies used by HEIs to reduce attrition and improve retention. Having a sense of belonging, a connection with the university, self-confidence, self-efficacy and motivation appeared to make students more likely to stay on their course. Several support strategies appeared to enhance retention, including an automated text messaging system, an Academic, Personal and Professional Learning (APPL) support mechanism, a pastoral care support adviser service and an extracurricular student support group. Developing a holistic and multifaceted approach to retention involves working collaboratively with students to enhance the understanding of their needs.

Association of Sociodemographic Characteristics With US Medical Student Attrition

Diversity in the medical workforce is critical to improve health care access and achieve equity for resource-limited communities. Despite increased efforts to recruit diverse medical trainees, there remains a large chasm between the racial and ethnic and socioeconomic composition of the patient population and that of the physician workforce. To analyze student attrition from medical school by sociodemographic identities. This retrospective cohort study included allopathic doctor of medicine (MD)-only US medical school matriculants in academic years 2014-2015 and 2015-2016. The analysis was performed from July to September 2021. The main outcome was attrition, defined as withdrawal or dismissal from medical school for any reason. Attrition rate was explored across 3 self-reported marginalized identities: underrepresented in medicine (URiM) race and ethnicity, low income, and underresourced neighborhood status. Logistic regression was assessed for each marginalized identity and intersections across the 3 identities. Among 33 389 allopathic MD-only medical school matriculants (51.8% male), 938 (2.8%) experienced attrition from medical school within 5 years. Compared with non-Hispanic White students (423 of 18 213 [2.3%]), those without low income (593 of 25 205 [2.3%]), and those who did not grow up in an underresourced neighborhood (661 of 27 487 [2.4%]), students who were URiM (Hispanic [110 of 2096 (5.2%); adjusted odds ratio (aOR), 1.41; 95% CI, 1.13-1.77], non-Hispanic American Indian/Alaska Native/Native Hawaiian/Pacific Islander [13 of 118 (11.0%); aOR, 3.20; 95% CI, 1.76-5.80], and non-Hispanic Black/African American [120 of 2104 (5.7%); aOR, 1.41; 95% CI, 1.13-1.77]), those who had low income (345 of 8184 [4.2%]; aOR, 1.33; 95% CI, 1.15-1.54), and those from an underresourced neighborhood (277 of 5902 [4.6%]; aOR, 1.35; 95% CI, 1.16-1.58) were more likely to experience attrition from medical school. The rate of attrition from medical school was greatest among students with all 3 marginalized identities (ie, URiM, low income, and from an underresourced neighborhood), with an attrition rate 3.7 times higher than that among students who were not URiM, did not have low income, and were not from an underresourced neighborhood (7.3% [79 of 1086] vs 1.9% [397 of 20 353]; P < .001). This retrospective cohort study demonstrated a significant association of medical student attrition with individual (race and ethnicity and family income) and structural (growing up in an underresourced neighborhood) measures of marginalization. The findings highlight a need to retain students from marginalized groups in medical school.

Repaving the Pathway to Prevent the Loss of Students With Marginalized Identities—Medical Student Attrition

Repaving the Pathway to Prevent the Loss of Students With Marginalized Identities—Medical Student Attrition

Psychological Distress, Burnout, and Business Student Turnover: The Role of Resilience as a Coping Mechanism.

This study’s purpose is to examine whether resilience, conceptualized by Connor and Davidson (2003) as one’s capacity to persevere and rebound under adversity, was a potential mitigating and/or moderating factor in the dynamic between both psychological distress and academic burnout, and student attrition. We concurrently distributed a survey containing a series of psychometric instruments to a convenience sample of 1,119 students pursuing various business majors at four geographically diverse U.S. universities. Via structural equations modeling analysis, we measured the associations between psychological distress, academic burnout, and departure intentions, and investigated whether student resilience levels are associated with lower distress, burnout, and departure intentions levels. The results indicated significant positive associations between psychological distress and each of the elements of academic burnout, and significant positive associations between the academic burnout elements and departure intentions. However, while resilience did not moderate those associations, it did attenuate them through its direct negative associations with both psychological distress and the cynicism and academic inefficacy elements of academic burnout. Based on these findings, we discuss implications for business educators seeking to enhance individual resilience levels as a coping strategy to combat voluntary student turnover, and better prepare students for the demands of the workplace.

The cost of academic dismissal and attrition from students on academic probation

AbstractPolicies on academic probation and dismissal have existed in the American higher education system for decades to maintain academic quality and encourage students to improve their performance. Research has aimed to clarify the relationship between academic probation, dismissal, and retention, yet differing results emerge. Furthermore, the literature is sparse on the financial implications incurred as a result of academic dismissal or student attrition once on academic probation. The aim of this study explores financial implications experienced by one college as a result of academic dismissal or dropout from 136 academic probation students among 5 years of student cohorts. Findings show a loss of $842,650 in revenue to be earned due to these 136 students not completing their baccalaureate degrees after being on academic probation. The author provides recommendations to support students on academic probation to avoid further attrition and thus loss of revenue.

Restitution Through Equity-Focused Mentoring: A Solution to Diversify the Physician Workforce.

Minoritized and marginalized physicians who identify as Black, Latino/a/x and Native American (BLNA) remain unacceptably underrepresented in medicine. Multiple studies provide a compelling argument for prioritizing racial/ethnic diversification of the physician workforce to improve racial/ethnic physician-patient concordance and assist in achieving more equitable health outcomes. Despite a growing awareness for the tangible benefits of a diversified physician workforce, the number of physicians from minoritized and marginalized groups remains relatively stagnant or worsening in certain demographics. The 5:1 ratio of Black students and trainees to Black faculty exemplifies and exacerbates the increased risk for harmful isolation particularly experienced by many BLNA mentees. They too need and deserve the benefits produced by concordant racial/ethnic faculty mentoring and support. However, these demands on time, resources and bandwidth can lead to negative consequences for BLNA faculty engaged in these efforts by contributing to their emotional, mental and physical exhaustion. Given the perpetual paucity of BLNA physicians in academic medicine, immediate interventions to prevent attrition of BLNA faculty, trainees and students journeying along the physician career pathway are urgently needed. Requiring the implementation of mentoring programs explicitly focused on increasing the number of physicians from groups underrepresented in medicine must happen at every point of the education and training process.

Online Graduate Student Retention: Integrative Review With a Theoretically Framed Case Exemplar.

Retention of online nursing students in graduate education is essential as the need for nurses exceeds the current supply. The factors contributing to student attrition are reviewed, and a real-world case exemplar is presented to demonstrate the theoretical design and implementation of an orientation to support retention. Knowles' theory of adult learning and Cooper's PECS (purpose, expectations, connections, and support) model for an evidence-based orientation framework guided the design of the orientation. Knowles' theory was aligned with the PECS model to further describe how student and environmental factors can be addressed in an orientation framework and provide strategies for implementation. Additionally, these PECS definitions were applied to specific activities within a conceptual, theoretical, and empirical framework for development of orientations. This case exemplar demonstrated an orientation framework for a feasible application of theory and evidence-based strategies for graduate online nursing programs. [J Nurs Educ. 2022;61(6):314-321.].

Theory to Practice: Reducing Student Attrition in Online Undergraduate Math

Researchers have developed numerous effective theory-based practices for teaching undergraduate general education mathematics (UGEM); however, many universities have struggled for decades to close the gap from theory to practice. This gap contributes to the national lack of skilled STEM workers. Recently, an all-online university closed the gap by shifting their philosophical framework for UGEM from traditionalist methodology to a synthesis of seminal theories and practices. This paper disseminates the implementation of theory-based practices in UGEM toward reducing student attrition (withdraw or fail), including: Rationale for theory identification, construction of a philosophical framework, collection of stakeholder input, implementation, evaluation, post-implementation maintenance and communication, and institutional socialization of the new paradigmatic shift. These efforts yielded an attrition reduction from 17.5% to 4.7% in Quantitative Reasoning 1 (QR1) and from 13.9% to 4.0% in QR2. A key reported outcome is a blueprint for an institution to similarly close the gap.

Quantification of Learning Gains in a Science CURE: Leveraging Learning Objectives to Substantiate and Validate the Benefits of Experiential Education

Course‐based Undergraduate Research Experiences (CURE) aim to provide college students with hands‐on experiences to develop research skills and complex thinking. Development of these abilities is invaluable as students undertake further education and begin critical professions. Regardless of eventual career aspirations, CUREs make it possible for every student to experience the enchantment of science in its authentic form. Performing research serves to galvanize inquiring minds that serve as role models for future generations of scientists. Science, Technology, Engineering and Math (STEM) disciplines as a whole suffer from high rates of student attrition. Notably, students from underrepresented groups enter STEM disciplines at similar rates and with similar interest levels as White students, but do not persist at the same rates. CUREs have proven to be an indispensable model to expose every student, regardless of race, socioeconomic status or family obligations, to the process of science first hand. While many CURE curricula are freely available online, faculty are hesitant to adopt this new style of teaching. Using established anticipated learning outcomes (ALO) designed specifically for the Biochemistry Authentic Student Inquiry Laboratory (BASIL) CURE, this study aims to gauge student learning objective mastery quantitatively. Likert scale‐based analysis is employed to evaluate the level of content mastery student responses demonstrate. Assignment questions were designed to correspond to the most critical learning objectives, as identified by BASIL faculty. Researchers spent significant effort designing and refining laboratory assignment questions that correspond to and can reliability and consistently to gage mastery of the ALOs.Data of student mastery spanning 4 semesters will be discussed. Students showed significant learning gains in all four semesters/modalities. Greater mastery of bioinformatic ALOs during remote learning shows quality education can be enhanced and improved by technology. The student’s mastery of wet‐lab ALOs coincided with our findings that lab courses need enhanced strategies to teach critical STEM lab‐research skills in an online setting. Novel assessment and instruction strategies targeted to learning mastery gaps identified as part of this work will pave the way for wider CURE adoption. Ultimately, serving as a platform to expose every undergraduate student to vital STEM research experiences.