Publications

Table of Contents

Wladis, C.W., Fay, M. & Hachey, A.C. (2024). The Holistic Capital Model: Time and Body Capital Sources of Inequity. AERA Open, 10. https://doi.org/10.1177/23328584241255626

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We present a model of capital that expands existing models to introduce two new forms of capital (time and body capital) as sources of inequity in education. The aim is to (a) make visible core resources that are relevant to educational outcomes and also (often hidden) sources of inequity, (b) identify commonalities across diverse empirical and theoretical research strands, and (c) reconceptualize existing research from an asset rather than deficit framework. We explain how time and physiological resources can be conceptualized as forms of capital and link this to extant empirical and theoretical research across fields. Then, we describe how students may have different amounts and types of time and body capital, as well as different drains on capital, and how this may lead to educational inequities. We close by describing the affordances of using this theory as a lens for analyzing existing educational structures, policies and practices.

Wladis, C.W., Hachey, A.C. & Conway, K.M. (2024).  It’s About Time: The Inequitable Distribution of Time as a Resource for College, by Gender and Race/Ethnicity. Research in Higher Education, 65(7), 1614-1646. https://doi.org/10.1007/s11162-024-09796-5 

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Existing qualitative research in higher education on students’ work and family commitments already suggests that time as a resource for college is likely not distributed equitably by race/ethnicity or gender. However, the relationship between race/ethnicity, gender, and time as a resource for college has yet to be quantitatively measured in large-scale higher education research. This study explored whether gender or race/ethnicity correlated with differences in time as a resource for college; and further, the extent to which differences in time as a resource for college may be explained by other factors such as age, number of children, and access to childcare. Retrospective survey responses (n = 41,579) on self-reported time use were merged with institutional data records from students at the City University of New York (CUNY), a large diverse public university in the U.S. Women, Black, and Hispanic students were all significantly more time poor than male, White, or Asian students. Age accounted for significant portions of these differences, perhaps because it correlates with increased work and family responsibilities. Having children as well as a student’s access to childcare also explained a significant portion of inequitable distributions of time as a resource for college.

Wladis, C., Manly, C. A., Hachey, A. C. & Conway, K. M. (2024). Life Stressors as Predictors of Community College Students’ Course Outcomes: The COVID-19 Pandemic as a Focusing Event. Teachers College Record, 126(6-7), 182-200. https://doi.org/10.1177/01614681241283258

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Background or Context:

The COVID-19 pandemic may be considered a focusing event that has drawn greater attention to the physical and mental health of community college students.

Purpose, Objective, Research Question, or Focus of Study:

This study examined community college students’ self-reported life stressors pre- and post-pandemic-onset to identify any reported differences, both in occurrence and in impact on course completion.

Research Design:

Surveys were collected after the COVID-19 pandemic onset at the City University of New York’s largest community college. The 529 students enrolled in STEM subjects were asked about potentially stressful life events experienced during spring 2020 and how strongly these impacted the time or energy they had for their studies (response rate 88.2%).
 

Conclusions or Recommendations:

Students’ reporting of the presence of life stressors, as well as their rating of the impact on their studies, were significantly predictive of subsequent course outcomes. However, stressors reported as beginning prior to the pandemic had a larger and more significant relationship with course outcomes than those reported as beginning after pandemic onset. Further, stressors were already highly prevalent prepandemic, with over three-quarters of students reporting them. Although the pandemic may have drawn attention to the existence and impact of stressors, it may simply be a focusing event that drew heightened attention to a pre-existing issue. Results from this study indicate that life stress may significantly impact the outcomes of community college students even outside of pandemic conditions, suggesting that this is a critical area for community colleges to address.

Wladis, C., Hachey, A.C., Conway, K.M. (2024). It’s about time, Part II: Does time poverty contribute to inequitable college outcomes by gender and race/ethnicity? AERA Open, 10(1), 1–20. https://doi.org/10.1177/23328584241237971

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Existing research demonstrates gender- and race/ethnicity-based inequities in college outcomes. Separately, recent research suggests a relationship between time poverty and college outcomes for student parents and online students. However, to date, no studies have empirically explored whether differential access to time as a resource for college may explain differential outcomes by gender or race/ethnicity. To address this, this study explored the relationship between time poverty, gender or race/ethnicity, and college outcomes at a large urban public university with two and four year campuses. Time poverty explained a significant proportion of differential outcomes (retention and credit accumulation) by gender and race/ethnicity. More time-poor groups also dedicated a larger proportion of their (relatively limited) discretionary time to their education, suggesting that inequitable distributions of time may contribute to other negative outcomes (e.g., reduced time for sleep, exercise, healthcare). This suggests that time poverty is a significant but understudied equity issue in higher education.
Wladis, C., Hachey, A. C., & Conway, K. (2024). Did Emergency Remote Teaching and the COVID-19 Pandemic Exacerbate Inequities? Considering Institution Type, Gender, and Race/Ethnicity. The Journal of Higher Education, 95(3), 313–349. https://doi.org/10.1080/00221546.2023.2250696
 
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This study explores the extent to which college context (two- vs. four-year), gender, and race/ethnicity correlated with worsening course outcomes during emergency remote teaching during the COVID-19 pandemic, by comparing outcomes within students between the fall 2019 pre-pandemic and spring 2020 pandemic terms. In particular, it explores the extent to which prior voluntary online course-taking is related to patterns among these groups. Results from this study suggest that students at two-year colleges, men, and Black and Hispanic students had worse outcomes during emergency remote teaching, if they had not previously voluntarily enrolled in online courses. However, these differential trends were not observed among students who had voluntarily enrolled in online courses prior to the pandemic.

Hachey, A. C., Wladis, C., & Conway, K. M. (2023). Investigating online versus face-to-face course dropout: Why do students say they are leaving? Education Sciences, 13(11), 1122. https://doi.org/10.3390/educsci13111122
 
Despite more focused attention in the wake of the COVID-19 pandemic, high online attrition remains both a concern and a mystery; gaps in our knowledge exist as to why students so often do not complete online courses. Pre-pandemic, and using a sample of 780 students who dropped out of fully online courses (or the same course face-to-face) from a large university system in the Northeast U.S., students were explicitly asked about their specific reasons for course withdrawal. All students enrolled in a fully online course (or a face-to-face section of the same course) at the City University of New York (CUNY) in fall 2015 were invited to take the online survey from which this study data was taken. Results indicate that there were distinct differences in the patterns of reasons given by online and face-to-face students: although the perceived quality of the instructor/instruction was deemed important to student persistence in both modalities, it seemed to be of greater importance face-to-face than online. Furthermore, issues related to time were found to be more prominent reasons for dropping for online learners than face-to-face learners. Findings from this study shed new light on the impetus for online attrition, with implications for online policy and course design in a post-pandemic era.
Wladis, C., Hachey, A. C., & Conway, K. (2023). Time Poverty: A Hidden Factor Connecting Online Enrollment and College Outcomes? The Journal of Higher Education, 94(5), 609–637. https://doi.org/10.1080/00221546.2022.2138385
 

This study explored the relationships between voluntary online course enrollment (pre-pandemic), time poverty, and college outcomes. Results indicate that students who enrolled in at least one fully online course were significantly more time poor than other students; these differences were largely explained by age, parental status, and paid work. Yet, despite being more time poor, students who enrolled in online courses were more likely to successfully complete their courses, especially after controlling for time poverty. While students who took at least one online course were less likely to be retained in college and accumulated on average fewer credits, outcomes in online courses did not explain these differences; rather, other factors that make students both more likely to enroll online and to drop out or take fewer credits likely play a role. In particular, time poverty fully mediated the relationship between online enrollment and credit accumulation.

Hachey, A. C., Wladis, C., Manly, C. A., & Conway, K. M. (2023). Health Challenges and Community College Student Outcomes Before and During the COVID-19 Pandemic. American Behavioral Scientist, 67(13), 1591–1610. https://doi.org/10.1177/00027642221118295
 
This study details the prevalence of community college students’ reports of serious health events both before and after the onset of the COVID-19 pandemic in spring 2020. Survey responses from a representative sample of students within the largest community college at the City University of New York highlighted serious health challenges. Findings indicated that serious health challenges (including illness/injury/disability/mental health) were a significant factor in predicting students’ outcomes during the spring 2020 term. However, health-related events that occurred prior to the onset of the pandemic had a substantially and significantly larger correlation with course outcomes than those that occurred after the onset of the pandemic. This suggests that serious health issues may be a major barrier to student progress at community colleges, even outside of the conditions of a global pandemic, and that the pandemic may have only exacerbated this significant but often overlooked preexisting issue.
Hachey, A. C., Conway, K. M., Wladis, C., & Karim, S. (2022). Post-secondary online learning in the U.S.: An integrative review of the literature on undergraduate student characteristics. Journal of Computing in Higher Education, 34(3), 708–768. https://doi.org/10.1007/s12528-022-09319-0
 

Even prior to the COVID-19 pandemic, online learning had become a fundamental part of post-secondary education. At the same time, empirical evidence from the last decade documents higher dropout online in comparison to face-to-face courses for some students. Thus, while online learning may provide students access to post-secondary education, concerns about academic momentum and degree attainment dominate the higher education online learning landscape. Because course completion is often used as a measure of effectiveness, there is a strong need for institutions to be able to predict the potential persistence of online students to direct efforts towards ameliorating dropout. Yet currently, a widely tested and validated archetypical predictive model of retention and success does not exist for undergraduate online learning. This integrative review of the literature examines evidence gathered over the last decade, organizing and summarizing major findings, to help identify potential undergraduate student characteristics for inclusion in such a model. The body of literature collected in this review suggests ten factors for consideration.

Conway, K. M., Wladis, C., & Hachey, A. C. (2021). Time Poverty and Parenthood: Who Has Time for College? AERA Open, 7, 23328584211011608. https://doi.org/10.1177/23328584211011608
 
Student parents are among the least likely student groups to complete college. Regression models were run using 2003–2019 American Time Use Survey data to explore time poverty among college students. Results indicate that students with children under 13 years had significantly less discretionary time and free time, spent significantly less time on their education, enrolled part-time at significantly higher rates, and spent significantly more time studying while simultaneously caring for children, compared with students without children under 13 years. The strength of these relationships was strongest when children were younger. Parents with children under 6 years, and mothers of children of all age-groups, had significantly higher time poverty than other groups, yet spent significantly more time on education after controlling for discretionary time, at the cost of significantly less free time for themselves. Results suggest that improving college outcomes for student parents may require consideration of time poverty.
Wladis, C., & Mesa, V. (2019). What can happen when community college practitioners lead research projects? The case of CUNY. The Review of Higher Education, 42(4), 1575–1606. https://doi.org/10.1353/rhe.2019.0076
 

Although the majority of college freshmen enroll at community colleges, very few research studies focus on this context. In addition, what research does exist often overlooks important practitioner concerns, such as instruction. In this article we argue that supporting generalizable education research conducted by community college practitioners can address this gap. We seek to start a conversation about the benefits of such research, to both the education research community and to educational practices at community colleges. We draw on findings from a large community college system where this kind of research has been systematically supported for the last 15 years.

Wladis, C., Hachey, A. C., & Conway, K. (2018). No Time for College? An Investigation of Time Poverty and Parenthood. The Journal of Higher Education, 89(6), 807–831. https://doi.org/10.1080/00221546.2018.1442983
 

Postsecondary outcomes are significantly worse for student parents even though they earn higher GPA’s on average. This study used institutional records and survey data from a large urban U.S. university to explore whether time poverty explains this trend. The results of regression and KHB decomposition analysis reveal that students with preschool-aged children have a significantly lower quantity and quality of time for college than comparable peers with older or no children, and that time spent on childcare is the primary reason for this difference. Both quantity and quality of time for education had a significant direct effect on college persistence and credit accumulation, even when controlling for other factors. Thus, greater availability of convenient and affordable childcare (e.g. increased on-campus childcare, revised financial aid formulas that include more accurate estimates of childcare costs) would likely lead to better college outcomes for students with young children.

Wladis, C., Conway, K., & Hachey, A. C. (2017). Using course-level factors as predictors of online course outcomes: A multi-level analysis at a US urban community college. Studies in Higher Education, 42(1), 184–200. https://doi.org/10.1080/03075079.2015.1045478
 

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Research has documented lower retention rates in online versus face-to-face courses. However, little research has focused on the impact of course-level characteristics (e.g. elective versus distributional versus major requirements; difficulty level; STEM status) on online course outcomes. Yet, focusing interventions at the course level versus the student level may be a more economical approach to reducing online attrition. This study used multi-level modeling, and controlled for the effects of both instructor-level and student characteristics, to measure the relationship of course-level characteristics with successful completion of online and face-to-face courses. Elective courses, and to a lesser extent distributional course requirements, were significantly more likely to have a larger gap in successful course completion rates online versus face-to-face, when compared with major course requirements. Upper level courses had better course completion rates overall, but a larger gap in online versus face-to-face course outcomes than lower level courses.

Wladis, C., Conway, K. M., & Hachey, A. C. (2016). Assessing readiness for online education–Research models for identifying students at risk. Online Learning [Special Section: Best Papers Presented at the OLC 21st International Conference on Online Learning and Innovate 2016], 20(3), 97–109.
 

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This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed was that native-born students were at greater risk online than foreign-born students, relative to their face-to-face outcomes. Having a child under 6 years of age also interacted with the online medium to predict lower rates of successful course completion online than would be expected based on face-to-face outcomes. In addition, while students enrolled in online courses were more likely to drop out of college, online course outcomes had no direct effect on college persistence; rather other characteristics seemed to make students simultaneously both more likely to enroll online and to drop out of college.
Wladis, C., & Samuels, J. (2016). Do online readiness surveys do what they claim? Validity, reliability, and subsequent student enrollment decisions. Computers & Education, 98, 39–56. https://doi.org/10.1016/j.compedu.2016.03.001
 

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Online readiness surveys are commonly administered to students who wish to enroll in online courses in college. However, there have been no well-controlled studies to confirm whether these instruments predict online outcomes specifically (as opposed to predicting course outcomes more generally). This study used a sample of 24,006 students to test the validity and reliability of an online readiness survey similar to those used in practice at a majority of U.S. colleges. Multilevel models were used to determine if it was a valid predictor of differential online versus face-to-face course outcomes while controlling for unobserved heterogeneity among courses taken by the same student. Student self-selection into online courses was also controlled using student-level covariates. The study also tested the extent to which survey score correlated with subsequent decisions to enroll in an online course. No aspect of the survey was a significant predictor of differential online versus face-to-face performance. In fact, student characteristics commonly collected by institutional research departments were better predictors of differential online versus face-to-face course outcomes than the survey. Furthermore, survey score was inversely related to subsequent online enrollment rates, suggesting that the use of online readiness surveys may discourage some students from enrolling in online courses even when they are not at elevated risk online. This suggests that institutions should be extremely cautious about implementing online readiness surveys before they have been rigorously tested for validity in predicting differential online versus face-to-face outcomes.
Wladis, C., Hachey, A. C., & Conway, K. (2015). Which STEM majors enroll in online courses, and why should we care? The impact of ethnicity, gender, and non-traditional student characteristics. Computers & Education, 87, 285–308. https://doi.org/10.1016/j.compedu.2015.06.010
 

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Using data from roughly 27,800 undergraduate STEM (science, technology, engineering and mathematics) majors in the National Postsecondary Student Aid Study (NPSAS), this research examines the relationship between race/ethnicity, gender and non-traditional student characteristics and online course enrollment. Hispanic and Black STEM majors were significantly less likely, and female STEM majors significantly more likely, to take online courses even when academic preparation, socioeconomic status (SES), citizenship and English-as-second-language (ESL) status were controlled. Furthermore, non-traditional student characteristics strongly increased the likelihood of enrolling in an online course, more so than any other characteristic, with online enrollment probability increasing steeply as the number of non-traditional factors increased. The impact of non-traditional factors on online enrollment was significantly stronger for STEM than non-STEM majors.
Wladis, C., Conway, K. M., & Hachey, A. C. (2015). The Online STEM Classroom—Who Succeeds? An Exploration of the Impact of Ethnicity, Gender, and Non-traditional Student Characteristics in the Community College Context. Community College Review, 43(2), 142–164. https://doi.org/10.1177/0091552115571729
 

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Objective:
This study analyzes how ethnicity, gender, and non-traditional student characteristics relate to differential online versus face-to-face outcomes in science, technology, engineering, and mathematics (STEM) courses at community colleges.

 
Method:
This study used a sample of 3,600 students in online and face-to-face courses matched by course, instructor, and semester from a large urban community college in the Northeast. Outcomes were measured using rates of successful course completion (with a “C−” or higher). Multilevel logistic regression and propensity score matching were utilized to control for unobserved heterogeneity between courses and for differences in student characteristics.
 
Results:
With respect to successful course completion, older students did significantly better online, and women did significantly worse (although no worse than men) online, than would be expected based on their outcomes in comparable face-to-face courses. There was no significant interaction between the online medium and ethnicity, suggesting that though Black and Hispanic students may do worse on average in STEM courses than their White and Asian peers both online and face-to-face, this gap was not increased by the online environment.
 
Contributions:
These findings suggest that both women and younger students in STEM courses may need extra support in the online environment. Future research is needed (a) to explore whether factors such as stereotype threat or child care responsibilities affect the outcomes of women in online STEM courses, and (b) to determine which characteristics (e.g., motivation, self-directed learning skills) of older students may make them particularly well suited to the online environment.

Wladis, C., Hachey, A. C., & Conway, K. M. (2015). The representation of minority, female, and non-Traditional STEM majors in the online environment at community colleges: A nationally representative study. Community College Review, 43(1), 89–114. https://doi.org/10.1177/0091552114555904

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Using data from more than 2,000 community college science, technology, engineering, and mathematics (STEM) majors in the National Postsecondary Student Aid Study, this research investigates how ethnicity, gender, non-traditional student risk factors, academic preparation, socio-economic status, and English-as-second-language/citizenship status relate to online course enrollment patterns. Even after controlling for other factors, Blacks and Hispanics (Black and Hispanic men, in particular) were significantly underrepresented in online courses, women were significantly overrepresented, and students with non-traditional student risk factors (delayed enrollment, no high school diploma, part-time enrollment, financially independent, have dependents, single-parent status, and working full-time) were significantly more likely to enroll online. However, although ethnicity, gender, and non-traditional factors were all important predictors for both 2- and 4-year STEM majors, at community colleges, ethnicity and gender were more important predictors of online enrollment than non-traditional characteristics, which is the opposite pattern observed at 4-year colleges.

Hachey, A. C., Wladis, C., & Conway, K. (2015). Prior online course experience and GPA as predictors of subsequent online STEM course outcomes. The Internet and Higher Education, 25, 11–17. https://doi.org/10.1016/j.iheduc.2014.10.003

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This study found that G.P.A. and prior online experience both predicted online STEM course outcomes. While students with higher G.P.A.s were also more likely to have successfully completed prior online courses, prior online course experience added significant information about likely future STEM online outcomes, even when controlling for G.P.A. Students who had successfully completed all prior online courses had significantly higher rates of successful online STEM course completion at all G.P.A. levels than students who had failed to complete even one prior online course successfully. Students who had dropped or earned a D or F grade in even one prior online course had significantly lower rates of successful online STEM course completion than students with no prior online experience, even when controlling for G.P.A. This suggests that prior online course outcomes should be combined with G.P.A. when attempting to identify community college students at highest risk in online STEM courses.
Wladis, C., Hachey, A. C., & Conway, K. (2014). An investigation of course-level factors as predictors of online STEM course outcomes. Computers & Education, 77, 145–150. https://doi.org/10.1016/j.compedu.2014.04.015
 
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This study analyzed students who took STEM courses online or face-to-face at a large urban community college in the Northeastern U.S. to determine which course-level characteristics most strongly predicted higher rates of dropout or D/F grades in online STEM courses than would be expected in comparable face-to-face courses. While career and elective STEM courses had significantly higher success rates face-to-face than liberal arts and major requirement STEM courses respectively, career STEM courses had significantly higher success rates online than would be expected, while elective STEM courses had significantly lower success rates online than would be expected given the face-to-face results. Once propensity score matching was used to generate a matched subsample which was balanced on a number of student characteristics, differences in course outcomes by course characteristics were no longer significant. This suggests that while certain types of STEM courses can be identified as higher or lower risk in the online environment, this appears not to be because of the courses themselves, but rather because of the particular characteristics of the students who choose to take these courses online. Findings suggests that one potential intervention for improving online STEM course outcomes could be to target students in specific courses which are at higher risk in the online environment; this may allow institutions to leverage interventions by focusing them on the STEM courses at greatest risk of lower online success rates, where the students who are at highest risk of online dropout seem to be concentrated.

Wladis, C., Hachey, A. C. and Conway, K., (2014). The Role of Enrollment Choice in Online Education: Course Selection Rationale and Course Difficulty as Factors Affecting Retention. Journal of Asynchronous Learning Networks, 18(3). https://doi.org/10.24059/olj.v18i3.391

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There is well-documented evidence that online retention rates are lower than face-to-face retention rates; however, most past research on online retention focuses on student characteristics, with little knowledge existing on the impact of course type. This study uses a matched sample of 2,330 students at a large urban community college to analyze two key course-level factors which may be impacting online retention: the student’s reason for taking the course (as an elective or a requirement) and course difficulty level. The results of this study indicate that the online modality increases dropout risk in courses that are taken as an elective or distributional requirement, particularly for lower-level courses. The findings suggest that in the online environment, the student’s reason for course enrollment may be considered a risk indicator and that focused learner support targeted at particular course types may be needed to increase online persistence and retention.
Hachey, A. C., Wladis, C. W., & Conway, K. M. (2014). Do prior online course outcomes provide more information than GPA alone in predicting subsequent online course grades and retention? An observational study at an urban community college. Computers & Education, 72, 59–67. https://doi.org/10.1016/j.compedu.2013.10.012
 

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In this study, prior online course outcomes and pre-course enrollment G.P.A. were used as predictors of subsequent online course outcomes, and the interaction between these two factors was assessed in order to determine the extent to which students with similar G.P.A.’s but with different prior online course outcomes may differ in their likelihood of successfully completing a subsequent online course. This study used a sample of 962 students who took an online course at a large urban community college from 2004 to 2010. Results indicate that prior online course experience is a very significant predictor of successful completion of subsequent online courses, even more so than G.P.A. For students with no prior online course experience, G.P.A. was a good predictor of future online course outcomes; but for students with previous online course experience prior online course outcomes was a more significant predictor of future online course grades and retention than G.P.A.
Mesa, V., Wladis, C., & Watkins, L. (2014). Research problems in community college mathematics education: Testing the boundaries of K-12 research. Journal for Research in Mathematics Education, 45(2), 173–192. https://doi.org/10.5951/jresematheduc.45.2.0173
 

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The purpose of this commentary is to articulate the need to investigate problems of mathematics instruction at community colleges. We briefly describe some features of this often-ignored institution and the current status of research. We also make an argument for how investigations of instruction in this setting can both advance our understanding of this particular context and give practitioners tools to deal with pressures from policymakers to show short-term results. This work is the result of a collaborative effort between community college practitioners and researchers, responding to the needs of their work in mathematics education.
Wladis, C., Offenholley, K., & George, M. (2014). Leveraging Technology to Improve Developmental Mathematics Course Completion: Evaluation of a Large-Scale Intervention. Community College Journal of Research and Practice, 38(12), 1083–1096. https://doi.org/10.1080/10668926.2012.745100
 

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This study hypothesizes that course passing rates in remedial mathematics classes can be improved through early identification of at-risk students using a department-wide midterm, followed by a mandated set of online intervention assignments incorporating immediate and elaborate feedback for all students identified as at-risk by their midterm score. A sample of over 20,000 students was used to evaluate the intervention, which was implemented department-wide over several semesters in all developmental mathematics courses at a large diverse urban community college. The intervention was assessed by evaluating course passing rates (a proxy for passing rates on standardized exit examinations) and student time spent in the intervention lab. Students from semesters prior to the intervention were used as a control, with fall semesters compared to fall semesters and spring to spring, to control for possible variation in student enrollment. Highly statistically significant differences were found between student passing rates pre- versus post-intervention, with passing rates improving by as much as 50%. The size of this study and the diversity of the student population involved suggests that results are likely widely applicable to other institutions across the country. In particular, the interventions tested were chosen specifically because they can reasonably be implemented even across relatively large and diffuse departments with limited resources.

Wladis, C., Hachey, A. C., & Conway, K. (2013). Are online students in STEM (science, technology, engineering and mathematics) courses at greater risk of non-success? American Journal of Educational Studies, 6(1). 65-84.

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Both online and STEM courses have been shown to have lower student retention; however, there is little research indicating what effect the online environment may have on retention in STEM courses specifically. This study compares retention rates for online and face-to-face STEM and non-STEM courses to determine if the online environment affects STEM courses differently than non-STEM courses. In addition, different subcategories of STEM courses are compared to see if the effects of the online environment are different for different course subtypes. Each online course is matched with the same course taught face-to-face by the same instructor in the same semester to control for possible confounding effects. This study found that retention rates in STEM courses were more strongly decreased by the online environment than in non-STEM courses. In particular, the course types which had significantly lower retention online were lower level STEM courses taken as electives or distributional requirements.

Hachey, A. C., Wladis, C. W., & Conway, K. M. (2013). Balancing Retention and Access in Online Courses: Restricting Enrollment … is it Worth the Cost? Journal of College Student Retention: Research, Theory & Practice, 15(1), 9–36. https://doi.org/10.2190/CS.15.1.b

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Open access is central to the Community College mission. For this reason, any restriction in online enrollments should not be undertaken lightly. This study uses institutional data gathered from a large, urban community college to examine a policy aimed at increasing student retention in online courses by restricting those eligible to enroll based on Grade Point Average (GPA) The data, counter to expectations, show that the policy did not significantly impact attrition rates. Further analysis reveals that a high GPA cut-off (3.0) is needed to significantly affect attrition rates; however, this would severely restrict those eligible to enroll. The data indicate that students in the middle GPA range (2.0–3.5) have the highest proportional difference in attrition between online and face-to-face courses. The results suggest that rather than focusing on GPA restrictions, community colleges may be better served by addressing research and interventions targeted toward other factors to increase student retention in online learning.
Hachey, A. C., Conway, K. M., & Wladis, C. W. (2013). Community colleges and underappreciated assets: Using institutional data to promote success in online learning. Online Journal of Distance Learning Administration, 16(1), 1–18. Spring.
 
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Adapting to the 21st century, community colleges are not adding brick and mortar to meet enrollment demands. Instead, they are expanding services through online learning, with at least 61% of all community college students taking online courses today (Pearson, 2011). As online learning is affording alternate pathways to education for students, it is facing difficulty in meeting outcome standards; attrition rates for the past decade have been found to be significantly higher for online courses than face-to-face courses (Carr, 2000; Hachey, Wladis & Conway, 2012a/b; Morris & Finnegan, 2008; Tyler-Smith, 2006). Yet, there is a lack of empirical investigation on community college online attrition, despite the fact that course and institutional management systems today are automatically collecting a wealth of data which are not being utilized but are readily available for study. This article presents a meta-review of one community college’s realization of their underappreciated asset… the use of institutional data to address the dearth of evidence on factors effecting attrition in online learning.

Hachey, A. C., Wladis, C. W., & Conway, K. M. (2012). Is the Second Time the Charm? Investigating Trends in Online Re-Enrollment, Retention and Success. Journal of Educators Online, 9(1), n1.
 
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Online education is becoming an increasingly important component of higher education. The Sloan Foundation 2010 Survey of Online Learning reports that more than 30% of all students take at least one online course during their college career. Because of this, attention is now turning to the quality of student outcomes that this instructional method provides. However, there is a huge gap in empirical investigations devoted to the link between technology and performance indicators such as grade performance, re-enrollment and course completion (Nora & Plazas Snyder, 2008). This study found that prior online course experience is strongly correlated with future online course success. In fact, knowing a student’s prior online course success explains 13.2% of the variation in retention and 24.8% of the variation in online success in our sample, a large effect size. Students who have not successfully completed any previous online courses have very low success and retention rates, and students who have successfully completed all prior online courses have fairly high success and retention rates. Therefore, this study suggests that additional support services need to be provided to previously unsuccessful online learners, while students who succeed online should be encouraged to enroll in additional online courses in order to increase retention and success rates in online learning. (Contains 3 figures, 13 tables, and 1 footnote.)
Wladis, C. (2012). The word problem and the metric for the Thompson–Stein groups. Journal of the London Mathematical Society, 85(2), 301–322. https://doi.org/10.1112/jlms/jdq060
 
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We consider the Thompson–Stein group F(n1,…,nk), where n1, …, nk∈{2, 3, 4, …} and k∈ℕ. We highlight several differences between the cases k=1 and k>1, including the fact that minimal tree-pair diagram representatives of elements may not be unique when k>1. We establish how to find minimal tree-pair diagram representatives of elements of F(n1,…,nk), and we prove several theorems describing the equivalence of trees and tree-pair diagrams. We introduce a unique normal form for elements of F(n1,…,nk) (with respect to the standard infinite generating set developed by Stein) which provides a solution to the word problem, and we give sharp upper and lower bounds on the metric with respect to the standard finite generating set, showing that, in the case k>1, the metric is not quasi-isometric to the number of leaves or caret in the minimal tree-pair diagram, as is the case when k=1.

Conway, K., Wladis, C., & Hachey, A. (2011). Minority Student Access in the Online Environment. HETS Online Journal, 2(1), Article 1. https://doi.org/10.55420/2693.9193.v2.n1.95
 
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Using registration and transcript data, the authors explored differences in online course enrollment across different student groups. This study revealed that minority students do not enroll in online courses to the same extent as their White student peers, but the effect size for the difference in participation rates was small. However, the actual difference between minority students online vs. face-to-face enrollment was five percentage points, a difference equivalent to about 150 minority students per year, given the College’s current enrollment rates, so the impact of this small difference is not insignificant. An even greater issue is that Black and Hispanic students, regardless of the course delivery medium, continue to have lower G.P.A. s than their White and Asian/Pacific Islander (PI) student peers. This finding reinforces prior research that suggests Black and Hispanic student groups need additional support in order to be successful in college, and that greater recruitment efforts for online courses are needed for all minority groups.

Conway, K., Hachey, A. C. and Wladis, C. (2011). Growth of online education in a community college. Academic Exchange Quarterly, 15(3), 96-101
 

This case study examines the evolution of online education at a large urban community college. It outlines issues related to course development, administration, student and faculty support. Online course enrollment, student and faculty perceptions and organizational issues were evaluated a decade after online education was introduced at the college. At both the inception of online education and in order to expand successfully, external funding was crucial for program success.

Wladis, C. (2011). Thompson’s group is distorted in the Thompson–Stein groups. Pacific Journal of Mathematics, 250(2), 473–485. https://doi.org/10.2140/pjm.2011.250.473
 
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We show that the inclusion map of the generalized Thompson groups F(ni) is exponentially distorted in the Thompson–Stein groups F(n1,…,nk) for k > 1. One consequence is that F is exponentially distorted in F(n1,…,nk) for k > 1 whenever ni = 2m for some m (whenever no i,m exist such that ni = 2m, there is no obviously “natural” inclusion map of F into F(n1,…,nk)). This is the first known example in which the natural embedding of one of the Thompson-type groups into another is not quasi-isometric.

Wladis, C. (2011). Cyclic subgroups are quasi-isometrically embedded in the Thompson-Stein groups. International Journal of Algebra and Computation, 21(01n02), 365–385. https://doi.org/10.1142/S0218196711006212
 
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We give criteria for determining the approximate length of elements in any given cyclic subgroup of the Thompson–Stein groups F(n1,…,nk) such that n1 – 1|ni – 1 ∀i ∈ {1,…,k} in terms of the number of leaves in the minimal tree-pair diagram representative. This leads directly to the result that cyclic subgroups are quasi-isometrically embedded in the Thompson–Stein groups. This result also leads to the corollaries that ℤn is also quasi-isometrically embedded in the Thompson–Stein groups for all n ∈ ℕ and that the Thompson–Stein groups have infinite dimensional asymptotic cone.

Wladis, C. (2009). Unusual geodesics in generalizations of Thompson’s group. Illinois Journal of Mathematics, 53(2), 483–514. https://doi.org/10.1215/ijm/1266934789

 
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We prove that seesaw words exist in Thompson’s group F(N) for N=2,3,4,… with respect to the standard finite generating set X. A seesaw word w with swing k has only geodesic representatives ending in gk or g−k (for given g∈X) and at least one geodesic representative of each type. The existence of seesaw words with arbitrarily large swing guarantees that F(N) is neither synchronously combable nor has a regular language of geodesics. Additionally, we prove that dead ends (or k-pockets) exist in F(N) with respect to X and all have depth 2. A dead end w is a word for which no geodesic path in the Cayley graph Γ which passes through w can continue past w, and the depth of w is the minimal m∈N such that a path of length m+1 exists beginning at w and leaving B|w|. We represent elements of F(N) by tree-pair diagrams so that we can use Fordham’s method for computing word length. This paper generalizes results by Cleary and Taback, who proved the case N=2.

Wladis, C. (2007). Thompson’s group F (n) is not minimally almost convex. New York J. Math, 13, 437–481.
 
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We prove that Thompson’s group F(n) is not minimally almost convex with respect to the standard finite generating set. A group G with Cayley graph Γ is not minimally almost convex if for arbitrarily large values of m there exist elements g,h ∈ Bm such that dΓ(g,h)=2anddBm (g,h)=2m. (Here Bm is the ball of radius m centered at the identity.) We use tree-pair diagrams to represent elements of F(n) and then use Fordham’s metric to calculate geodesic length of elements of F(n). Cleary and Taback have shown that F(2) is not almost convex and Belk and Bux have shown that F(2) is not minimally almost convex; we generalize these results to show that F(n)is not minimally almost convex for all n ∈{2,3,4,…}.

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