Project Activities
Researchers used statistical modeling to analyze student data from the Florida Virtual School (FLVS), a large urban school district in Florida (LUD), and the Florida Department of Education (FDOE) to compare outcomes for high school students taking courses in the same subjects online versus face-to-face (FtF). The researchers also conducted surveys with students and teachers in virtual and FtF schools to supplement the main analyses and aid in interpreting the findings.
Structured Abstract
Setting
This project took place in Florida, and data from three sources were linked for analysis: FLVS, LUD, and FDOE. Researchers also collected surveys from students and teachers in LUD. In addition to looking statewide, the researchers examined virtual course-taking and student outcomes separately for various subgroups, including for rural versus urban students, for students from different categories of economic disadvantage, and for students from different racial groups.
Sample
Secondary analyses relied on administrative data from all middle- and high-school students and teachers in Florida public schools (both virtual and FtF). This comprised over 15.3 million student-years and 850,000 teacher-years of observation. Surveys were collected from 800 teachers and 3000 students in in FLVS and LUD.
Intervention
The study examined virtual and FtF course taking. Virtual courses are offered through a number of providers across the state, most notably through the Florida Virtual School, a public school that provides online, self-paced courses that students can access from home, a computer lab, or school library.
Research design and methods
The research plan included primary data collection and analysis and secondary data analysis. Researchers first used a series of statistical models to describe who takes virtual courses and the differences in student outcomes associated with virtual course access and course-taking. Outcomes included student test outcomes, course grades, and course progression. The teacher and student surveys offered insights into motivations and processes that helped the researchers to generate hypotheses about the causes of the observed patterns.
Control condition
For the secondary data analysis, students in FLVS schools were compared with students taking courses in the same subjects in FtF schools. For the survey, researchers used matched comparison groups of students from FDOE and FLVS schools, and from FLVS and LUD schools, who are taking the same courses in different formats.
Key measures
The secondary data analysis relied on administrative data that had already been collected, including student scores on Florida's state standardized test, the FCAT, FCAT 2.0, and End-of-Course tests. Researchers developed the surveys based on well-validated questions from prior surveys.
Data analytic strategy
To characterize the student and school characteristics associated with virtual course-taking, the researchers used a variety of descriptive statistics. To examine the association between virtual course-taking and student outcomes, the researchers used multiple regression analysis, including models with home institution and course fixed effects. To test the robustness of the results to alternative model specifications and potential omitted factors, the researchers conducted several sensitivity analyses.
Key outcomes
The main findings of this exploratory study are as follows:
People and institutions involved
IES program contact(s)
Products and publications
ERIC Citations: Publications available in ERIC from this project are available here.
Select Publications:
Hart, C.M., Berger, D., Jacob, B., Loeb, S., & Hill, M. (2019). Online learning, offline outcomes: Online course taking and high school student performance. Aera Open, 5(1), 2332858419832852.
Hart, C.M., Linden, R., Jacob, B., & Loeb, S. (2023). Online Course-Taking and Expansion of Curricular Options in High Schools. Peabody Journal of Education, 98(1), 26-48.
Jacob, B., Berger, D., Hart, C., & Loeb, S. (2016). Can technology help promote equality of educational opportunities?. RSF: The Russell Sage Foundation Journal of the Social Sciences, 2(5), 242-271.
Supplemental information
Co-Principal Investigators: Loeb, Susanna; Hart, Cassandra
- Which students are most likely to take online courses? Which types of courses are students most likely to take online?
- How is access to online classes and taking of online classes associated with the course progression and academic achievement of students, and how does that differ across student groups?
- What mechanisms explain why some students enroll in online courses and some do not, and what mechanisms explain potentially different effects of online course-taking across students?
- Girls, students who are more economically advantaged, and students with higher prior achievement scores are more likely to take virtual courses (Jacob, et al., 2016).
- Students engage in virtual instruction for two distinct reasons: as an alternative method of taking a course for the first time, and as a method of retaking a previously failed course (Jacob, et al, 2016; Hart, et al., 2019).
- Students are more likely to pass a course when taking it virtually, whether for the first-time or as a retake (Hart, et al., 2019).
- Downstream outcomes associated with virtual course taking differ between those retaking the course versus those taking the course for the first time. For students taking a course for the first time, virtual instruction is associated with modestly negative outcomes. For those retaking a course, virtual instruction is associated with positive longer-term outcomes (Hart, et al., 2019).
- A small but growing share of students (7% of high school students by 2013–14) uses virtual offerings to take courses not offered in their brick-and-mortar schools. This use of courses was more common among higher-achieving students, in rural schools, and in schools with relatively few Advanced Placement/International Baccalaureate offerings (Hart et al, 2023).
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