Online Learning Efficacy Research Database

In this research, we investigated whether business students enrolled in a statistics course gained more by engaging in traditional face-to-face (FTF) learning or online learning. Empirical evidence suggested that students learned statistics more effectively when engaged with an instructor in a traditional FTF classroom versus through online learning; however, when the option of teaching virtually in fully online (ONL) classes was available, students successfully learned about statistics whether in a traditional FTF classroom or a ONL learning experience. In addition, evidence suggested that students’ overall satisfaction with the course and the instructor was higher in the FTF setting than in the ONL setting. Evidence also suggested that offering online zoom lecture meetings in the ONL setting remarkably enhanced students’ satisfaction with the course and the instructor and, importantly, reduced the gap in effective instruction between traditional FTF and ONL settings. 
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Our study compared the performance of students enrolled in a graduate-level introductory biostatistics course in an online versus a traditional in-person learning environment at a school of public health in the United States. We extracted data for students enrolled in the course online and in person from 2013 to 2018. We compared average quiz and final exam scores between students in the two learning environments adjusting for demographic characteristics and prior academic performance using linear mixed models. Data were available for 1461 (83.1%) students learning online and 298 (16.9%) students learning in person. After adjusting for sex, race/ethnicity, age, quantitative GRE score, undergraduate GPA, and math refresher score, we found quiz scores for students learning online were about 2.5% lower than those for students learning in person, on average, with a 95% confidence interval ranging from 4.9% lower to 0.02% higher. Differential performance was even closer to equality for the final exam where scores for students learning online were about 0.9% higher with a 95% confidence interval ranging from a 3.9% reduction to 5.8% improvement. These estimates suggest comparable student performance can be achieved in a graduate-level introductory biostatistics course among students learning online and in person. Supplementary materials for this article are available online. 
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This study compared the achievement of male and female students who were enrolled in an online univariate statistics course to students enrolled in a traditional face-to-face univariate statistics course. The subjects, 47 graduate students enrolled in univariate statistics classes at a public, comprehensive university, were randomly assigned to groups that used either online instruction or traditional face-to-face instruction. The effects of the independent variables of online univariate statistics instruction versus traditional face-to-face instruction on the dependent variable of statistics achievement were analyzed with a two-way analysis of variance. There was a significant difference between the achievement of students who used online univariate statistics instruction and those who used traditional face-to-face instruction (p=.001). The traditional face-to-face group scored higher with an effect size of 0.979, indicating that, on the average, those who were enrolled in a traditional face-to-face univariate statistics class outperformed 83.4% of those enrolled in the online statistics course. Moreover, females using online instruction out-performed males using online instruction and males enrolled in a traditional face-to-face course scored higher than females, with an effect size of 0.651, indicating that, on the average, those males outperformed 74.22% of the females enrolled in a traditional face-to-face statistics course. 
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With the dramatic increase of online business degree programs, the question of the effectiveness of online courses has been front and center. Do these once primarily face-to-face courses successfully transfer to online-only formats without losing student productivity? Do the new formats still reach students, and is it reflected in final grades? Research was focused on evaluating the efficacy, measured by student performance, of undergraduate business statistics courses taught online classes, as compared to traditional, face-to-face classes and web- enhanced courses. Are there differences in how male and female students perform in both class formats?

Performance in the classroom is traditionally measured by the grades, namely the final grade. This study looked at the impact of online learning facilities in a course with traditionally difficult content for undergraduates with regard to gender. Results found that students overall performed better in face-to-face business statistics courses than in online. When gender was analyzed, the final grade for female students were significantly decreased from face-to-face to online courses, as compared to male students, whose grades were not significantly different in the two course formats. 
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Web-augmented traditional lecture, fully online, and flipped sections, all taught by the same instructor with the same course schedule, assignments, and exams in the same semester, were compared with regards to student attitudes; statistical reasoning; performance on common exams, homework, and projects; and perceptions of the course and instructor. The Survey of Attitudes Toward Statistics-36 (SATS-36) instrument and eight questions from the Statistical Reasoning Assessment (SRA) were given both at the beginning and end of the semester to measure change. The students selected their own sections, but the students in the sections were similar demographically, with similar pre-course college grade point averages. The SATS-36 showed increases in affect, cognitive competence, and perceived easiness and decreases in value, interest, and effort from beginning to end of the semester for all sections. Only affect and perceived easiness showed any differences for section, with traditional higher than online on average for both. Results from the SRA questions showed an increase in correct statistical reasoning skills and decrease in misconceptions for all sections over the semester. Traditional students scored higher on average on all three exams, but there were no significant differences between sections on homework, the project, or on university evaluations of the course or instructor. Results are contextualized with prior educational research on course modalities, and proposals for future research are provided. 
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This paper assesses quantitatively the impact on student performance of a blended learning experiment within a large undergraduate first-year course in statistics for business and economics students. We employ a difference-in-differences method, which controls for differences in student characteristics and course delivery method, to evaluate the impact of blended learning on student performance. Our results suggest that the impact of blended learning on student performance depends on whether the effect of blended learning is cumulative or not. Blended learning has no impact on student performance if learning is non-cumulative and only affects the performance on the quizzes associated with the material covered by blended learning. However, if learning is cumulative and impacts the performance for the whole course, then our results strongly suggest a strong, negative effect. Taken as a whole, these results provide a possible explanation for why most of the existing studies focusing on short online courses have obtained neutral or even positive results while nearly all the studies focusing on semester-length course tend to observe negative impacts from online learning. 
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Online instruction is quickly gaining in importance in U.S. higher education, but little rigorous evidence exists as to its effect on student learning. We measure the effect on learning outcomes of a prototypical interactive learning online statistics course by randomly assigning students on six public university campuses to take the course in a hybrid format (with machine-guided instruction accompanied by one hour of face-to-face instruction each week) or a traditional format (as it is usually offered by their campus, typically with about three hours of face-to-face instruction each week). We find that learning outcomes are essentially the same—that students in the hybrid format are not harmed by this mode of instruction in terms of pass rates, final exam scores, and performance on a standardized assessment of statistical literacy. We also conduct speculative cost simulations and find that adopting hybrid models of instruction in large introductory courses has the potential to significantly reduce instructor compensation costs in the long run. 
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This paper investigates the performance of students enrolled in traditional versus hybrid Elementary Statistics courses at Georgia Gwinnett College (GGC). For this study, we collected and analyzed student performance data for the course goals over the spring semester of 2011. GGC is unique as it is an open access undergraduate institution, which has experienced rapid growth since its recent foundation in 2006. This presents a distinct challenge because there is a diverse student population, with various degrees of mathematical knowledge and learning capabilities. Based on the results of our findings, we have discovered that there is no significant difference between the performances of the two groups. 
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Technology-based instruction represents a new recent pedagogical paradigm that is rooted in the realization that new generations are much more comfortable with, and excited about, new technologies. The rapid technological advancement over the past decade has fueled an enormous demand for the integration of modern networking, informational and computational tools with classical pedagogical instruments. Consequently, teaching with technology typically involves utilizing a variety of IT and multimedia resources for online learning, course management, electronic course materials, and novel tools of communication, engagement, experimental, critical thinking, and assessment.

The NSF-funded Statistics Online Computational Resource (SOCR) provides a number of interactive tools for enhancing instruction in various undergraduate and graduate courses in probability and statistics. These resources include online instructional materials, statistical calculators, interactive graphical user interfaces, computational and simulation applets, tools for data analysis and visualization. The tools provided as part of SOCR include conceptual simulations and statistical computing interfaces, which are designed to bridge between the introductory and the more advanced computational and applied probability and statistics courses. In this manuscript, we describe our designs for utilizing SOCR technology in instruction in a recent study. In addition, present the results of the effectiveness of using SOCR tools at two different course intensity levels on three outcome measures: exam scores, student satisfaction and choice of technology to complete assignments. Learning styles assessment was completed at baseline. We have used three very different designs for three different undergraduate classes. Each course included a treatment group, using the SOCR resources, and a control group, using classical instruction techniques. Our findings include marginal effects of the SOCR treatment per individual classes; however, pooling the results across all courses and sections, SOCR effects on the treatment groups were exceptionally robust and significant. Coupling these findings with a clear decrease in the variance of the quantitative examination measures in the treatment groups indicates that employing technology, like SOCR, in a sound pedagogical and scientific manner enhances overall the students’ understanding and suggests better long-term knowledge retention. 
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In a series of 5 experiments in 2000 and 2001, several hundred students at two different universities with three different professors and six different teaching assistants took a semester long course on causal and statistical reasoning in either traditional lecture/recitation or online/recitation format. In this article we compare the pre-post test gains of these students, we identify features of the online experience that were helpful and features that were not, and we identify student learning strategies that were effective and those that were not. Students who entirely replaced going to lecture with doing online modules did as well and usually better than those who went to lecture. Simple strategies like incorporating frequent interactive comprehension checks into the online material (something that is difficult to do in lecture) proved effective, but online students attended face-to-face recitations less often than lecture students and suffered because of it. Supporting the idea that small, interactive recitations are more effective than large, passive lectures, recitation attendance was three times as important as lecture attendance for predicting pre-test to post-test gains. For the online student, embracing the online environment as opposed to trying to convert it into a traditional print-based one was an important strategy, but simple diligence in attempting “voluntary” exercises was by far the most important factor in student success. 
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