Online Learning and Community Colleges

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.
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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.
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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 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.
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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 requirement) 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.
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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. doi
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.
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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.
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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.
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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.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.
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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-to- face. 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.
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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.
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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.
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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: 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.
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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: 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.