Abstract

Student enrollment continues to increase in online programs, but there is concern surrounding the reportedly high rates of attrition in online classes compared to face-to-face classes. Undergraduate students are poorly prepared and lack the human agency necessary for success in the online learning environment. To address the lack of persistence of undergraduate online students, universities must create and implement interventions that prepare students for the online learning environment and help them develop as autonomous learners. This study examined whether differences in self-regulation, self-direction, and online learning self-efficacy exist between students participating in an experimental high-impact First-Semester Seminar (FSS) class and a traditional FSS class while controlling for pre-existing factors. A quantitative, quasi-experimental, pretest-posttest research design was used for this study with nonequivalent control groups, and multivariate analysis of covariance (MANCOVA) and follow up analyses of covariances (ANCOVA) were used to analyze the data. MANCOVA results revealed a statistically significant difference between groups. Follow-up ANCOVAs revealed differences between the posttest scores of the traditional FSS class and the high-impact FSS class on the measurements for self-directed learning and self-regulated learning.

Highlights

  • IntroductionPrior to the onset of the COVID-19 pandemic in the United States in March 2020, student enrollment in online programs was already on the rise

  • Prior to the onset of the COVID-19 pandemic in the United States in March 2020, student enrollment in online programs was already on the rise (Friedman, 2018; NationalCenter for Education Statistics, 2017; Seaman, Allen, & Seaman, 2018), and this growth was projected to continue into 2026 (Hussar & Bailey, 2018)

  • Given the significance of the multivariate analysis of covariance (MANCOVA), the univariate main effects were examined using a series of one-way analyses of covariances (ANCOVA) for each of the three dependent variables separately

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Summary

Introduction

Prior to the onset of the COVID-19 pandemic in the United States in March 2020, student enrollment in online programs was already on the rise Attrition rates in online classes have been documented as 10% to 20% higher than traditional face-to-face classes (Bawa, 2016; Kauffman, 2015), and online persistence rates are low, as well. If students are to continue enrolling in online programs and universities plan to increase their undergraduate online program offerings, the high rates of attrition in online classes must not be overlooked. Interventions aimed at promoting factors associated with online student persistence are essential to student success and, university success as persistence rates are vital to accreditation, funding, and reputation (Tinto, 2017; Yang, Baldwin, & Snelson, 2017)

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