In recent years, the Australian tertiary education sector embraced the gradual adaption of the dual mode system in course delivery in universities and higher degree education providers. In such systems, students have the option, as well as the flexibility, to undertake the same course in a face-to-face (F2F) environment and/or an online environment. This article presents an evaluation of the dual mode design of a first-year business statistics course delivered at the Griffith University. In this article, we discuss the various aspects of the dual mode design in the course, emphasizing the use of consistent teaching strategies for the F2F and online student cohorts. Moreover, we present a comparative analysis of learning satisfaction and academic performance of the two cohorts within the dual mode system. Using
t-tests, nonparametric tests, and propensity score matching estimators we provide new insights into dual mode course design. Our results suggest no significant difference in student experiences and outcomes. Discussion and analysis presented in this article is useful as feedback for further improvement in teaching strategies in the delivery of dual mode courses
1 Introduction
Since its popularization in 1993, the internet has transformed many facets of human life. In particular, our ability to deliver education services to students has been revolutionized. Distance education was made possible, increasing ease and convenience for education to be accessed by anyone, from anywhere (Paulsen et al.
1998 Paulsen, K., Higgins, K., Miller, S., Strawser, S., and Boone, R. (1998), “Delivering Instruction via Interactive Television and Videotape: Student Achievement and Satisfaction,” Journal of Special Education Technology, 13, 59–77. DOI:10.1177/016264349801300401.[Crossref] , [Google Scholar]; Browning
1999 Browning, J. (1999), “Analysis of Concepts and Skills Acquisition Differences Between Web-delivered and Classroom-delivered Undergraduate Instructional Technology Courses,” North Carolina State University, ProQuest Dissertations Publishing. [Google Scholar]). Distance online education has emerged as a viable alternative to traditional face-to-face (F2F) classroom instruction, and has seen a significant worldwide increase in student enrollment over the past 20 years (Vioreanu 2018). For example, Allen and Seaman (
2008 Allen, I. E., and Seaman, J. (2008), Staying the Course: Online Education in the United States, 2008, Nedham, MA: Sloan Consortium. [Google Scholar]) reported that in 2008 online student enrollment in the United States experienced growth of approximately 13%, compared to a 1.2% increase in its overall higher education enrollments.
2 Course and Delivery
The course we discuss is a first-year business statistics course offered at the Griffith University for the Bachelor of Commerce and Business programs. Focusing on problem recognition and application to real-world settings, the course covers two key areas of business statistics; descriptive and inferential methods. The primary objective of this course, along with many other introductory statistics courses is the development of statistical literacy (Rumsey
2002 Rumsey, D. J. (2002), “Statistical Literacy as a Goal for Introductory Statistics Courses,” Journal of Statistics Education, 10, 6–13.[Taylor & Francis Online] , [Google Scholar]). By undertaking this module within their undergraduate curriculum, students develop the tools to effectively synthesize, analyze, and interpret data to make informed decisions in practice.
2.1 Course Duration and Content
Business statistics has been taught at the Griffith University for approximately 30 years. The course is delivered to students in F2F delivery mode at the two main campuses of the university, the Nathan campus and the Gold Coast campus, in Semester 1 and Semester 2 following a 13 week structure. The dual mode adaptation was first offered over the noncompulsory Summer Semester 2014/2015 which consists of a 10 week period between November and February. The dual mode offering has the same coverage of content to what is taught in Semester 1 and Semester 2. Students who chose to undertake their studies on-campus as a F2F student conducted their studies at the smaller campus of the university, the Logan campus. The Summer Semester attracts approximately a combined enrollment of 90–120 students in total in both the F2F and online cohorts. While flexibility is offered for students to switch between the F2F and online learning environment, we note that the majority of students remained in their enrolled mode of either F2F or online. Approximately only two online students per semester occasionally come to the F2F classes, while all of the F2F students stay with their on-campus enrollment.
2.2 Course Delivery
Contact with students includes weekly 2-hr lectures for the F2F students. The lectures emphasize various key statistical concepts and theories in the first hour, followed by relevant applications and worked examples.
2 There are two key pedagogical reasons for the use of this lecture structure in our statistics course. First, the presentation of concepts prior to their application provides a balance between theory and application which is desirable for development of analytical, quantitative statistical skills and computer literacy (Moore
1997 Moore, D. S. (1997), “New Pedagogy and New Content: The Case of Statistics,” International Statistical Review, 65, 123–137. DOI:10.1111/j.1751-5823.1997.tb00390.x.[Crossref], [Web of Science ®] , [Google Scholar]). Second, to achieve statistical literacy, the use of worked examples assists potential users of statistical information in the workplace (Gordon and Nicholas
2009 Gordon, S., and Nicholas, J. (2009), “Using Examples to Promote Statistical Literacy,” in 2009 UniServe Science Proceedings, pp. 58–64. [Google Scholar]). These weekly F2F lectures are recorded. Recordings are made available for online students within a few hours after the F2F lecture concludes. Online students who have queries regarding the lecture recordings send their questions to the instructor through email. These questions are then responded to promptly by the instructors. This approach is used to ensure that the content taught and the speed of delivery for the two cohorts of students is relatively consistent.
2.3 Assessment Structure
To promote consistency and fairness between the two cohorts, the F2F and online students complete the same assessment tasks. There are three components to the assessment; online quizzes (20%), computing assignment (20%), and final examination (60%). The design of the assessment structure aims to provide feedback on students’ learning throughout the semester, as well as providing a diverse range of assessment formats. This reflects the need for alternative approaches to student assessment to provide a broad evaluation regarding the ability and capacity of students’ critical thinking, communication, and reasoning skills (Gal and Garfield
1997 Gal, I., and Garfield, J. B. (1997), The Assessment Challenge in Statistics Education (Vol. 12), Amsterdam: IOS Press and International Statistical Institute. DOI:10.1111/j.1751-5823.1999.tb00377.x.[Crossref] , [Google Scholar]).
3 Analysis and Results
In this section, we present the results of the comparative analysis of learning satisfaction and academic performance of our F2F and online students. We hypothesize that the delivery strategy used in the course would provide an equitable learning experience for both the F2F and online students. Furthermore, the combination of the consistent teaching methods and the application of the same assessment structure should also translate to no significant difference in academic performance across the two cohorts after controlling for selection bias.
3.1 Data
The data utilized for the analysis comes from two sources. First, to analyze the difference in learning satisfaction we use data obtained from the student evaluation of course (SEC) survey and the student evaluation of teaching (SET) survey from Summer Semester 2014/2015 and Summer Semester 2015/2016. The same experienced instructor delivered the course across both semesters to both cohorts of students.
4 The SEC and SET surveys are completed by students toward the end of the teaching period, prior to the final assessment. The surveys are anonymous, and their timing is structured such that the impact of perceived performance is minimized. All enrolled students were invited to complete the surveys. The response rates across all courses in the university are typically less than 50% (see Nulty
2007 Nulty, D. (2007), “The Adequacy of Response Rates to Online and Paper Surveys: What Can be Done?” Assessment and Evaluation in Higher Education, 33, 1–13.[Web of Science ®] , [Google Scholar] for a discussion of this issue).
3.2 Learning Satisfaction
We begin by analyzing the difference in the student learning satisfaction. Students were asked a series of questions in the SEC and SET surveys. These questions are outlined in
Tables 2 and
3 for the SEC and SET, respectively. Students gave a rating between 1 and 5, where 1 is strongly disagree and 5 is strongly agree. We pooled the data for both years and conduct
t-tests comparing differences in means, assuming unequal variances. To test the robustness of the
t-tests results, we also conduct a Wilcoxon rank sum nonparametric test. The Wilcoxon rank sum test is useful to address situations where normality requirements necessary to perform
t-tests are not satisfied. The rank sum test is also appropriate as data obtained for this analysis are essentially ordinal in nature.
Tables 2 and
3 report the findings of the comparative analysis in terms of student satisfaction of the course and the teaching, respectively.
3.3 Academic Performance
Our analysis begins by testing for differences in academic performance.
Table 4 reports the
t-test of mean differences, assuming unequal variances for each assessment item individually and the total score of the students. Histogram of the semester total marks for F2F and online students is available in Appendix B. The results show that F2F students a
uny.ac.idchieve marginally higher average results than online students. However, the difference in the average results for each assessment item is not significant at the 5% level. As a robustness check, we also conduct an equivalence test using a two one-sided test (TOST)
t-test procedure (see for example Lakens,
2017 Lakens, D. (2017), “Equivalence Tests: A Practical Primer for t tests, Correlations, and Meta-analyses,” Social Psychological and Personality Science, 8, 355–362. DOI:10.1177/1948550617697177.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). We utilize a two-group unpaired mean-comparison test with unequal variances for the F2F and online student cohorts. The results of the TOST are reported in
Table C3 (Appendix C). Based on our hypothesis of a difference between F2F and online students, we would expect that both the upper and lower tail of the test is rejected to determine equivalence. The results show we reject the null hypothesis of a difference in outcomes for all four measures, suggesting that the two cohorts are equivalent across the academic performance indicators.
4 Conclusions
The adaption of dual mode systems enables education providers to deliver their courses concurrently for on-campus F2F students and off-campus online students. Pedagogical emphasis has shifted toward designing dual mode courses with consistent teaching strategies for both student cohorts. We evaluated the design of our recent delivery of dual mode introductory statistics course. Our delivery, incorporating an optimal utilization of the Blackboard Collaborate platform, was found effective in providing both our F2F and online students with a learning experience where there was no significant difference.
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