What Determines Course Format Preferences in Business Analytics?

Course Format Preferences in Business Analytics
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Dr. Sinjini Mitra is a professor at the Information Systems and Decision Sciences Department at  California State University, Fullerton


There has been explosive growth in online and hybrid classes in higher education over the past few decades worldwide. Students tend to choose an online course or program primarily because of the flexibility they offer. Research suggests that the online format may not be equally suitable for all students, however. Student success and course format preferences are driven by several factors. Demographic and academic backgrounds play a role as well as motivational and cognitive factors. These factors inspired some of my colleagues and I to explore potential differences in what makes students successful in traditional face-to-face and online instruction approaches.


Online vs. Traditional Learning Course Format Preferences

Our study consisted of data collected from approximately 150 undergraduate students. They were enrolled in both traditional face-to-face and online sections of a Business Analytics course. Both formats of the course followed exactly the same structure in terms of content, assignments, and exams. They were also administered using the same learning management system (LMS). Data analysis using statistical methods and models yielded the following primary findings:

  • Students who are already more self-directed in their motivational profile—meaning they have intrinsic motivation to accomplish things due to inherent satisfaction rather than any external incentives—are more likely to both enroll in and succeed at online courses.
  • Conversely, students who seek a more structured learning environment and are less self-motivated are likely to excel in a traditional face-to-face course format.
  • Regardless of format, students with a more reflective learning style—meaning they are more intent on applying concepts to their experience—perform better than their peers in quantitative courses like the Business Analytics course.


It is thus extremely important for instructors at any educational institution to understand that students have different learning styles and motivational preferences. Instructors can utilize a wide variety of course design techniques and learning activities to engage and motivate all students. For example, an instructor can provide extra credit or other incentives (such as a raffle for a $5 gift card of $5) to motivate those students who are not necessarily intrinsically motivated to participate in a discussion forum in an online class format. Such students may not engage in this type of activity otherwise.


Student Backgrounds and Course Format Preferences

Finally, our research also discovered that minority students typically prefer to enroll in a traditional face-to-face class section. This group includes first-generation college students as well as Hispanic, African American, and Native American students. These students are also more likely to seek out additional help and resources to succeed in quantitative courses. Academic support programs like Supplemental Instruction (SI) and tutoring have proved to be beneficial to their performance in these courses. From previous research, we have observed a gap between 5 and 8% in the proportion of underserved and traditional students who attend SI sessions for Business Analytics. (This data is based on courses that took place between 2017 and 2019, prior to the pandemic.)


What do these insights tell us about online learning and its future?

Online learning is at the forefront now more than ever given the transition to virtual instruction following the COVID-19 pandemic. What the education landscape will look like after the pandemic is a common topic among higher education institutions and administrators. Will online course offerings increase? How will institutions decide on which course structures to offer to cater to students’ needs?

Faculty members across the country have also undergone training in online course design and adapted to this new mode of instruction. They may be more prepared and more inclined to teach online today than ever before. The advent of AI and mobile technology has also provided opportunities to devise innovative online course content and activities. Thus, research into student differences in various course format preferences for different disciplines (Mathematics, Engineering, History, Communications, etc.) will play an important role in planning course offerings in higher education institutions.

Ultimately, these findings will ensure continued success of students in all formats. We observed how motivational and learning styles impacted student preference and success in online vs. face-to-face classes in Business Analytics (and similar quantitative or technical courses). Other disciplines may have their own sets of cognitive and metacognitive factors in determining these preferences that are worth researching.


Looking for a new textbook to use in your Business Analytics course? Take a look at the one Dr. Mitra uses.