Table of Contents
E-Learning Research
About
Since 2009, a team at the Borough of Manhattan Community College-City University of New York (BMCC-CUNY) has been pursuing research on the factors influencing student retention and success in higher education online learning and further, how online learning may impact college access and degree attainment.
This research departs from previous investigations by utilizing large-scale national data alongside a large diverse college dataset pulled from nineteen different colleges; by using rigorous methodological and statistical techniques to adjust for a broad range of factors that influence selection bias simultaneously; and by focusing on online community college and STEM courses specifically.
This research builds on an ongoing interdisciplinary collaboration involving faculty with credentials in cognitive psychology, instructional technology, online learning, mathematics, and higher education.
Research Team
Primary Investigators:
Claire Wladis, Ph.D.
Dr. Claire Wladis has a Ph.D. in Mathematics from the CUNY Graduate Center. She is a professor of Mathematics at the Borough of Manhattan Community College and of Urban Education at the Graduate Center at the City University of New York. Her research focuses primarily on student retention and successful course completion, with a particular focus on remedial mathematics and online learning.Contact: cwladis@bmcc.cuny.edu
Katherine M. Conway, Ph.D.
Dr. Conway has a Ph.D. in Higher Education, Administration, Leadership and Technology from New York University. She is a professor of Business Management at the Borough of Manhattan Community College, City University of New York. Her research focuses on community college student access and persistence, with an emphasis on immigrant, minority and first-generation students.Contact: kconway@bmcc.cuny.edu
Alyse C. Hachey, Ph.D.
Dr. Hachey has a Ph.D. in Educational Psychology from Columbia University. She is a professor of Teacher Education at the Borough of Manhattan Community College, City University of New York and an adjunct associate professor at Teachers College, Columbia University. Her research interests focus on early childhood cognition and curriculum development and community college online learning and retention.Contact: ahachey@bmcc.cuny.edu
Reseach Associates:
- Anthony Picciano, Ph.D.
Professor and Executive Officer of the PhD Program in Urban Education at the CUNY Graduate Center Jason F. Samuels, Ph.D.
Professor of Mathematics at the Borough of Manhattan Community College
Research Assistant:
- Yi Tong
Advisory Board:
- Advisory Board:
- Frances K. Stage, Ph.d.
Professor of Administration, Leadership, and Technology at New York University Dr. Lin Lin, Ph.d.
Associate Professor of Learning Technologies at the University of North Texas
Funded Projects
Current Funding
- Grant: National Research Foundation EHR Core Research Award
Award: $719,108- Time Frame: 2015-2018
- Primary Investigators: Claire Wladis; Alyse C. Hachey and Katherine M. Conway
- Research Associate: Dr. Anthony Picciano- Professor of Urban Education at the CUNY Graduate Center
- Research Assistant: Diane McAllister
- Advisory Board: Dr. Frances K. Stage – Professor of Administration, Leadership, and Technology at New York University; Dr. Lin Lin – Associate Professor of Learning Technologies at the University of North Texas
- Title: Can Student Characteristics Be Used to Effectively Identify Students At-Risk in the Online STEM Environment?
This project addresses the EHR Core Research (ECR) program’s goal to build a research foundation in STEM learning environments by investigating which factors predict poorer outcomes online vs. face-toface for STEM students, with a particular focus on traditionally underrepresented groups in STEM fields. Specifically, this research is motivated by the following questions:
When controlling for differences in student characteristics, what differences exist between online and face-to-face STEM course and subsequent outcomes; and which student characteristics are the strongest predictors of such differences? In particular, does the online environment impact traditionally underrepresented groups in STEM disciplines differently than other students?
Do statistical models based on student characteristics have predictive validity in identifying which students are most likely to successfully complete online STEM courses, and which online STEM students are most likely persist in college afterwards?
The end product of this research will be a logistic regression equation (or a straightforward recipe for institutions to follow to create their own institution-specific equation) which can be used to pinpoint students at highest risk of dropping out of online STEM courses (or college subsequently), so that effective support services can be targeted at the most at-risk students. This research will not only advance STEM and higher education research, but it will also potentially transform educational practice and policy. These results will impact students considering online courses, faculty designing and teaching online courses, staff implementing online student support structures, administrators determining policies about student access to online courses, and policymakers determining how and when to include online courses in programs to increase student access to, and success in, STEM disciplines.
- Grant: Internal Research Award
- Award: $278,981
- Time Frame: 2015-2018
- Primary Investigators: Claire Wladis, Alyse C. Hachey and Katherine M. Conway
This project is concerned with assessing factors that impact the course and college completion rates of students at BMCC and CUNY in order to inform eLearning policy. The research will support the creation of a CUNY dataset specific to online courses at the university, with information about the percentage of instruction conducted online, as well as variables related to online programs at each campus. This project will also support analysis on CUNY-wide data and some more general NCES data in order to identify factors that may be influencing online enrollment and course outcomes at BMCC specifically and further, to compare patterns at BMCC to national and CUNY-wide trends. The research will use logistic and ordinary linear regression models, along with propensity score matching and sensitivity analysis, to analyze the impact of student characteristics and eLearning program structures and policies on online course and subsequent college outcomes.
Previous Funding
- Grant: CUNY Fellowship Award
- Award: $74,860
- Time Frame: 2014-2015
- Primary Investigators: Claire Wladis, Alyse C. Hachey and Katherine M. Conway
This project is concerned with assessing factors that impact the course and college completion rates of students at BMCC and CUNY in order to inform eLearning policy. The research will support the creation of a CUNY dataset specific to online courses at the university, with information about the percentage of instruction conducted online, as well as variables related to online programs at each campus. This project will also support analysis on CUNY-wide data and some more general NCES data in order to identify factors that may be influencing online enrollment and course outcomes at BMCC specifically and further, to compare patterns at BMCC to national and CUNY-wide trends. The research will use logistic and ordinary linear regression models, along with propensity score matching and sensitivity analysis, to analyze the impact of student characteristics and eLearning program structures and policies on online course and subsequent college outcomes.
- Grant: Deutscher Akademischer Austauschdienst/ German Academic Exchange Service (DAAD) Research Visit Grant for Faculty
- Award: $9,255
- Time Frame: Fall 2014
- Title: Online course-taking, access, and persistence in higher education in the U.S. and Germany
- Grant: American Educational Research Association (AERA) Research Award
- Award: $25,000
- Time Frame: 2012-2014
- Title: Online STEM Students At-Risk: Building a Model of Online STEM Student Retention at the Community College
- Grant: CUNY Community College Collaborative Incentive (C3IRG) Research Grant
- Award: $15,000
- Time Frame: 2012-2013
- Title: An Investigation of Prior Experience and Course Type as Factors Affecting Online STEM Student Retention and Success
- Grant: BMCC/CUNY Faculty Development Grant: Factors Determining Online Student Enrollment
- Award: $3000
- Time Frame: 2013
- Title: Evaluation of a Large-Scale National Dataset
- Grant: PSC CUNY Research Award, Traditional B
- Award: $5125
- Time Frame: 2013-2014
- Title: The Role of Self-Selection in Online Student Persistence at the Community College: Are Restrictive Enrollment Policies Justified?
- Grant: PSC CUNY Research Award, Traditional B
- Award: $5462
- Time Frame: 2012-2013
- Title: Using a Binary Logistic Regression Model to Identify Online Courses in Greatest Need of Supplemental Student Support
- Grant: PSC CUNY Research Award, Traditional B
- Award: $2800
- Time Frame: 2012-2013
- Title: Examining Minority Student Success in Online STEM (Science, Technology, Engineering and Mathematics) Courses
- Grant: PSC CUNY Research Award, Traditional B
- Award: $4512
- Time Frame: 2011-2012
- Title: Assessing Online Students at Risk: Building a Better Predictive Model for Online Course Attrition
- Grant: PSC CUNY Research Award, Traditional B
- Award: $4512
- Time Frame: 2011-2012
- Title: Investigating Trends in Online Attrition to Optimize Student Success
- Grant: PSC CUNY Research Award, Traditional B
- Award: $4000
- Time Frame: 2011
- Title: Assessing Online Students at Risk: Building a Better Predictive Model for Online Course Attrition
- Grant: BMCC/CUNY Title V Faculty Research Grant
- Award: $4000
- Time Frame: 2011
- Title: Investigating Trends in Online Re-enrollment, Retention and Success
- Grant: BMCC/CUNY Title V Faculty Research Grant
- Award: $4000
- Time Frame: 2011
- Title: Access & Success: The Traditionally Underrepresented Student in Online Learning
Publications
Wladis, C., & Mesa, V. (In Press). What Can Happen When Community College Practitioners Lead Research Projects? The Case of CUNY. Review of Higher Education.
Abstract: 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 essay 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.
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Wladis, C., Hachey, A.C. and Conway, K.M. (2018). No time for college? An investigation of time poverty and parenthood. Journal of Higher Education. doi: 10.1080/00221546.2018.1442983
Abstract: Postsecondary outcomes are significantly worse for student parents even though they earn higher GPAís 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.
full-text (first 50 downloads free) full-text of accepted version
Wladis, C., Smith, J., & Duranczyk, I. (2017). Research on Non-university Tertiary Mathematics. In G. Kaiser (Ed.), Proceedings of the 13th International Congress on Mathematical Education. Hamburg, Germany: Springer International Publishing, 693-694.
Abstract: This paper summarizes the research presented and discussed at the ICME Research on Non-university Tertiary Mathematics Research Group.
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Online Learning
Hachey, A. C., Wladis, C., & Conway, K. (2018). What factors influence student decisions to drop online courses? Comparing online and face-to-face sections. In A. Volungeviciene, A. Szűcs (Eds.), Proceedings of the EDEN 2018 Annual Conference, 99-107. Genoa, Italy: European Distance and E-Learning Network (EDEN).
Abstract: High online attrition is both a concern and a mystery; little data exists on why students so often do not complete online courses. Using a sample of 780 students who dropped fully online courses (or the same course face-to-face) from a large university system in the Northeast, students were asked about their specific reasons for dropping. Results indicate distinct differences in the patterns of reasons given by online and face-to-face students. While the quality of instruction/instructor was the most common reason cited by students in both mediums, face-to-face students cited this much more often than online students. In contrast, online students were much more likely to cite issues of time and workload as a reason for course dropout.
Wladis, C., Hachey, A. C., & Conway, K. (2017). Factors that Predict Differential Online Versus Face-to-Face Course Outcomes: Evidence From Germany and the United States. In A. Volungeviciene, A. Szűcs (Eds.), Diversity Matters! Proceedings of the EDEN 2017 Annual Conference, 296-305. Budapest, Hungary: European Distance and E-Learning Network (EDEN).
Abstract: This study uses data from the 2014-2015 fall/winter semester: from the 18 two- and four-year colleges in the City University of New York (CUNY) system in the U.S.; and from 30 colleges and universities in the German province of Bavaria. At the end of the semester, students were invited to participate in an online survey. Outcomes in online versus face-to-face courses taken by the same student were compared; propensity score matching and multi-level models were also used to control for differences in student characteristics. This research looked at three outcomes: course success, course failure and college persistence. The main independent variable (IV), course medium, was dichotomized to face-to-face or fully online, and covariates included a a wide range of student characteristics. The results varied by country. Native born students in the U.S. are at greater risk of online drop-out, whereas the reverse is true in Germany. Being the parent of a young child was also a risk factor in the U.S. but not in Germany. In both countries, higher course/credit loads contributed to increased drop out, as did lower grade point averages. Colleges wanting to target interventions to students at highest risk in the online environment may want to focus on students with lower grade point averages, student parents (in countries with less state support for parents of young children), and students who are enrolled in higher numbers of courses/credits. Whether native-born or foreign-born students are in need of targeted interventions depends on the national/cultural context, and more research is needed to understand how other factors explain the relationship between nationality and online outcomes.
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Online Learning (Community Colleges; Factors Effecting)
Wladis, C., Conway, K.M and 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.
Abstract: 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. and Samuels, J. (2016) Do online readiness surveys do what they claim? Validity, reliability, and subsequent student enrollment decisions. Computers & Education, 98, 39–56. doi:10.1016/j.compedu.2016.03.001
Abstract: 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. and Conway, K. (2016) Student characteristics and online retention: Preliminary investigation of factors relevant to mathematics course outcomes, In T. Fukawa-Connelly, N. Engelke Infante, M. Wawro, S. Brown (Eds.), Proceedings of the 19th Annual Conference on Research in Undergraduate Mathematics Education. Pittsburg, PA, 1442-1453.
Abstract: There is evidence that students drop out at higher rates from online than face-to-face courses, yet it is not well understood which students are particularly at risk online. In particular, online mathematics (and other STEM) courses have not been well-studied in the context of larger-scale analyses of online dropout. This study surveyed online and face-to-face students from a large U.S. university system. Results suggest that for online courses generally, student parents and native-born may be particularly vulnerable to poor online-versus-face-to-face course outcomes. The next stage of this research will be to analyze the factors that are relevant to online versus face-to-face retention in mathematics (and other STEM) courses specifically.
Wladis, C.W., Conway, K.M. & Hachey, A.C. (2015). Using course-level factors as predictors of online course outcomes: A multilevel analysis at an urban community college. Studies in Higher Education.
Abstract: Research has documented lower retention rates in online versus faceto-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., 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).
Abstract: Previous research supports that retention is significantly lower in online courses in comparison to face-to face courses; however, much of the past research on student retention in the online environment focuses on student characteristics, with little existing on the impact of course type. This study identifies and analyzes two key factors that may be impacting online retention: the student’s reason for taking the course (whether as an elective or a equirement) and course difficulty level. The results of this study indicate that a student’s reason for taking a lower level course drastically impacts the likelihood of withdrawal in the online environment, while having no effect in face-to-face classes. In particular, for lower level courses which students took as an elective or distributional requirement, the online environment seemed to make them much more likely to drop out. The findings suggest that in the online environment, the student’s reason for course enrollment (an elective versus a requirement) 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. and Conway, K. (2014). Do prior online course outcomes provide more information than G.P.A. alone in predicting subsequent online course grades and retention? An observational study at an urban community college, Computers & Education. 72, 59-67.
Abstract: 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.
Hachey, A.C., Wladis, C. & 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.
Abstract: 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 G.P.A. The data, counter to expectations, show that the policy did not significantly impact attrition rates. Further analysis reveals that a high G.P.A. 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 G.P.A. 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 G.P.A. 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. and Wladis, C. (2013). Community colleges and underappreciated assets: Using institutional data to promote success in online learning. Online Journal of Distance Learning Administration, 16(1), Spring.
Abstract: 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. 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. 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. and Conway, K. (2012) Is the second time the charm? Investigating trends in online re-enrollment, retention and success. The Journal of Educators Online, 9(1), 1-25.
Abstract: 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
Conway, K., Hachey, A. C. and Wladis, C. (2011). Growth of online education in a community college, Academic Exchange Quarterly, 15(3), 96-101.
Abstract: 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.
Online Stem Learning
Wladis, C., Hachey, A. C., & Conway, K. (2017). Online STEM and mathematics course-taking: Retention and Access. In T. Fukawa-Connelly, N. Engelke Infante, M. Wawro, S. Brown (Eds.), Proceedings of the 20th Annual Conference on Research in Undergraduate Mathematics Education, 1695-1697. San Diego, CA.
Abstract: Using survey data and interviews from a large urban university system, this study explores factors that impact student decisions to take math classes online. The results suggest that access to online math courses likely impacts student course taking patterns, with significantly more students taking a different course if their desired math course is not offered online, compared to non-math courses.
Wladis, C.W., Hachey, A.C. & Conway, K.M. (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.
Abstract: 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. W., Hachey, A. C. & Conway, K. M. (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.
Abstract: This study used a sample of about 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 to analyze how ethnicity, gender and non-traditional student characteristics related to STEM [Science, Technology, Engineering, Mathematics] course outcomes online versus face-toface. Multilevel logistic regression (with course/instructor as grouping factor) and propensity score matching were utilized. Results indicated that older students did significantly better in online STEM courses, and that women did significantly worse (although still no worse than men) online, than would be expected based on their outcomes in comparable face-to-face STEM courses. There was no significant interaction between the online medium and ethnicity, suggesting that while Black and Hispanic students may do worse than their White and Asian peers in both online and face-to-face STEM courses, this gap was not increased by 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.
Abstract: Using data from the more than 2,000 community college STEM majors in the National Postsecondary Student Aid Study, this research examines which groups may be underrepresented online and identifies characteristics which differ significantly between online and face-to-face students. It provides essential information on self-selection into online courses that is necessary for future observational studies of online versus face-to-face outcomes. The results show that Hispanic students were significantly less likely to enroll online, with Black and Hispanic male students particularly underrepresented. Women were significantly more likely to enroll online, as were students with non-traditional student characteristics (delayed enrollment; no high school diploma; part-time enrollment; financially independent; have dependents; single parent status; working full-time). At community colleges, ethnicity was a stronger predictor than non-traditional characteristics, whereas at 4-year colleges the reverse was true: each additional non-traditional risk factor increased the likelihood of online enrollment by two and five percentage points at 2-year and 4-year colleges respectively.
Hachey, A. C., Wladis, C. and Conway, K. (2014). Prior online course experience and G.P.A. as predictors of subsequent online STEM course outcomes, Internet and Higher Education, 25, 11-17.
Abstract: 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.M. (2014). An investigation of course-level factors as predictors of online STEM course outcomes. Computers & Education, 77, 145-150.
Abstract: 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., Conway, K.M. (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.
Abstract: 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 nonSTEM courses to determine if the online environment affects STEM courses differently than nonSTEM 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.
Wladis, C., Hachey, A. C. and Conway, K. (2012) An analysis of the effect of the online environment on STEM student success, In S. Brown, S. Larsen, K. Marrongelle, and M. Oehrtman (Eds.), Proceedings of the 15th Annual Conference on Research in Undergraduate Mathematics Education, (Vol.2). Portland, Oregon, 291-300.
Abstract: 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 faceto-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 negatively impacted 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.
Online Learning and Hispanic Students
Conway, K.L., Hachey, A.C. and Wladis, C.W. (2014). A new disapora: Latino(a)s in the online environment. In Y. Medina and A. D. Macaya (Eds.). Latinos on the East Coast: A critical reader. NY, NY: Peter Lang.
Abstract: The Latino/a diaspora from the Caribbean, Central and South America to the U.S. is well documented. Many of these immigrants have settled in communities where they now constitute a majority. As noted herein, the Latino/a population varies by region, in its ethnicity, immigration status and longevity in the U.S. In the Northeast, the Latino/a population grew at a rate ten times as fast as the rest of the population in the decade ending 2010. Overall, and specifically in higher education, Latino/a students are the largest minority group and the fastest growing. Many of these students begin at community colleges. But as Latino/a students succeed in college in greater numbers, a new migration is occurring in higher education: to the online environment. This chapter examines Northeast Latino/a student enrollments and persistence in online courses in comparison to the traditional face-to-face classroom and in comparison to other ethnicities. Latino/a students, while enrolling in college in large numbers, continue to lag other student groups in graduation rates, and it is critical to understand if an increase in online course offerings will help or hinder Latino/a student success
Conway, K., Wladis, C. and Hachey, A. C. (2011) Minority student access in the online environment, Hispanic Educational Technologies Services (HETs) Journal, II, retrieved from http://www.hets.org/journal/articles/68-minority-student-access-in-theonline-environment.
Abstract: 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. 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.
Prior research has also shown that students who enroll in online courses at the college have higher G.P.A.’s than students who enroll in face-to-face courses; however, this study reveals a notable exception to this pattern. In contrast to other ethnic groups, there is no significant difference between Asian/PI students who select face to face versus online courses, suggesting that there are differences in the factors that determine online enrollment in this group compared to others.
Policy Briefs
WHICH STUDENTS ARE AT HIGHEST RISK ONLINE? Online course outcomes and subsequent college attrition
Key Takeaways:
Students with children and native-born students were both significantly less likely to successfully complete an online course than would be expected based on face-to-face performance.
Students who enrolled in online courses were less likely to persist in college, but online course outcomes had no direct effect on college persistence. Thus, students didn’t drop out of college because of poorer outcomes in the online environment.
IS IT RISKIER TO TAKE A COURSE ONLINE? Differences in successful course completion online versus face-to-face, after controlling for student self-selection
Key Takeaways:
After controlling for the specific course taken and student characteristics, including environmental factors (e.g. work and family responsibilities) and non-cognitive factors (e.g. motivation, grit), there was no significant difference in successful course completion rates online versus face-to-face.
Institutions should be cautious in restricting access to online courses through restrictive enrollment or development policies, because this is likely to reduce access to college for non-traditional students (e.g. those with work or family responsibilities) without improving course or college outcomes.
On the other hand, students who do not currently elect to take online courses should not be forced to enroll online, as the results of this study can only be generalized to those students who currently choose to take courses online.
REVISING FINANCIAL AID TO IMPROVE THE OUTCOMES OF STUDENT PARENTS How insufficient childcare and extra work hours leads to poorer college outcomes
Key Takeaways:
Students with children are significantly less likely to persist in college, and accumulate fewer credits than non-parents, even after controlling for other factors.
Student parents, particularly women, have lower quantity and quality of time to devote to their studies, largely because of childcare responsibilities (and to a lesser extent because of the need to seek paid work).
The time poverty of student parents entirely explains their lower rates of credit completion, and explains a significant proportion of their lower college persistence rates.
Providing on-campus childcare for student parents, especially those with pre-school-aged children, is critical to improving educational outcomes for this group.
Revising federal financial formulas to better include the actual costs of childcare (and the living expenses of dependent children) is also critical to improving the outcomes of student parents.
SHOULD STUDENTS AVOID ONLINE STEM COURSES? Successful STEM course completion rates online versus face-to-face, after controlling for student self-selection
Key Takeaways:
After controlling for the specific course taken and student characteristics, including environmental factors (e.g. work and family responsibilities) and non-cognitive factors (e.g. motivation, grit), there was no significant difference in successful STEM course completion rates online versus face-to-face.
Institutions should be cautious in limiting access to online STEM courses through restrictive enrollment or development policies, because this is likely to reduce access to college for non-traditional students (e.g. those with work or family responsibilities) without improving course or college outcomes.
On the other hand, students who do not currently elect to take STEM courses online should not be forced to enroll online, as the results of this study can only be generalized to those students who currently choose to take STEM courses online.