Benefits of additional online practice opportunities in higher education
Introduction
E-learning practice opportunities can mitigate challenges of teaching higher education courses (Ardac & Sezen, 2002; Dusi & Huisman, 2021). When instructors design their courses, they can offer only a limited set of study materials that promote a selected set of study techniques; including too many materials will overwhelm students. Instructors face particularly narrow limitations when teaching heterogenous first-year introductory courses with a large number of students. E-learning allows instructors to offer practice materials that indirectly promote a variety of study techniques. These techniques have different effects on students' learning gains, but students (and instructors) might not know which techniques are most effective (Dunlosky, Rawson, Marsh, Nathan, & Willingham, 2013; Karpicke, 2016). Dunlosky et al. (2013) review articles on evidence-based study techniques and points out the minimal learning gains of rereading, highlighting, and summarizing. However, these are the study techniques that most students use most frequently (Karpicke, 2016). Teaching students how to use other study techniques takes time and resources; furthermore, this instruction might not reach all students in courses where attendance is not mandatory. Therefore, it is essential to know whether e-learning practice can be used to augment a course so that students can apply more effective study techniques without explicit instruction in those techniques. Furthermore, while intrinsically motivated students will take on additional tasks (Walker, Greene, & Mansell, 2006), the additional e-learning materials should be designed to help all students in a course, particularly underperforming students. Therefore, the general objective of the present study is to analyze whether and which students benefit from additional e-learning opportunities that are based on effective study techniques.
A rich body of literature highlights the study techniques of self-testing (also called active recall) and spacing (also called spaced learning), which outperform rereading, highlighting, and summarizing (Dunlosky et al., 2013; Hartwig & Dunlosky, 2012; Rawson & Dunlosky, 2012; Rodriguez, Fischer, Zhou, Warschauer, & Massimelli, 2021; Roediger & Pyc, 2012). Moreover, additional e-learning practice opportunities could be designed to provide students with immediate feedback about the correct response. Especially in classes that are too large for instructors to provide individual feedback, automated feedback is helpful (Butler, Karpicke, & Roediger III, 2008; Finn, Thomas, & Rawson, 2018). However, previous studies have mixed findings on whether additional practice opportunities incorporated within the design of a course can improve students' course achievement (B. W. Brown & Liedholm, 2002; Panus, Stewart, Hagemeier, Thigpen, & Brooks, 2014). Therefore, more research on blended learning is needed to see if there are effective ways to provide students with practice opportunities and whether previous findings on study techniques and feedback can be translated into real-life higher education settings.
In this paper, we analyze the effect of a course augmented with e-learning practice opportunities. We observed a first-year college mathematics course with 280 undergraduate students. Students enrolled in the course were either majoring or minoring in business administration or economics at a large public German university. Therefore, we used a real-life educational setting, which is important to establish the external validity of laboratory results (Morrison & Anglin, 2005; Ross & Morrison, 1989). In addition, the study goes beyond existing results by identifying which students benefitted the most from e-learning practice opportunities. In particular, we seek to determine whether e-learning practice only helps students who are already doing well or whether additional digital practice opportunities can help underperforming students catch up.
Section snippets
Literature review
The study relates to three strands of existing literature: study techniques (self-testing and spacing), knowledge of correct response feedback, and blended learning. In addition, to select an appropriate set of control variables, we surveyed the literature in these areas, which identifies essential predictors/drivers of students' learning and achievement.
Aims of the study
Most literature on blended learning compares students who are taught in different formats, but few previous studies have explicitly studied the effects of specific features in a blended format. Though the objective of Panus et al. (2014) is similar to that of our study, their analysis focuses on multiple-choice quizzes. Our study aimed to test the effectiveness of two different e-learning practice opportunities on high-level learning in a higher education mathematics course. In addition, we
Design of online exercises and participants
Mathematics for Economics and Business Administration is a compulsory module in the first semester of all bachelor's degree programs in economics and business administration (majors and minors) at the German public university where the study was conducted. The course has three voluntary practice tests, which are offered through the built-in test feature in the university's open-source online learning management system (ILIAS). These practice tests are designed primarily to give students the
Regression results
Table 3 presents the regression results for the baseline and full model presented in Eq. (1). The full model includes the covariates identified via double selection OLS using the LASSO, random forest, xgBoost, or all available covariates. The outcome variable is the standardized final exam score without the extra credit points students received for completing the practice tests. While the complete model might have too many control variables to allow sufficient degrees of freedom for making
Discussion
In this section, we discuss the mechanisms and channels through which students might have benefited from the practice options. We also explore the effect of including control variables when measuring the effect of practice. In addition, we discuss potential reasons for the differences between submissions on the MAD app and practice exam attempts. Finally, we comment on the results of the quantile regressions.
Conclusion
We evaluated two types of voluntary e-learning opportunities offered to students taking a mathematics lecture course designed for first-year business administration and economics students. The first practice option consisted of three online practice tests with repeated access and extra credit for the first attempt on a specific date; the second consisted of the “Matrix a Day” app. We find that students who took the optional practice tests in the e-learning environment generally improved their
Author note
Jakob Schwerter is an affiliate at the LEAD Graduate School & Research Network [GSC1028], funded by the Excellence Initiative of the German federal and state governments.
This work was partly funded by Jacobs Foundation Advanced Research Fellowship to Kou Murayama. This research was partly supported by JSPS KAKENHI (Grant Numbers 16H06406)” and the “Alexander von Humboldt Foundation (the Alexander von Humboldt Professorship endowed by the German Federal Ministry of Education and Research)“
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