Student Perceptions Going into an Undergraduate Business Analytics Course

With the rapidly expanding adoption of data-driven approaches in the world of business, there is no question that data analysis skills are in high demand [1]. It is critical for business programs around the world to provide students with courses that develop their skills in business analytics, and for educators to ensure that students derive positive experiences from them, as business analytics is being integrated into every field of business [2]. For example, accountants may use business analytics for fraud detection, a manager may use it for enhancing productivity and a marketer may use it to compute a reliable customer lifetime value (CLV) or accurately estimate customer retention rates. Therefore, not only do students need to be familiar with business analytics, but they also need to be prepared to utilize it in their day-to-day work.

The good news is that most business schools are incorporating some form of business analytics into their curricula, and a substantial number even have departments dedicated to the field [3]. However, we speculated that there was a stigma surrounding the required undergraduate courses designed to introduce students to statistics and analytics. Our primary concerns included a lack of interest in the subject, lack of perceived relevance to their career paths and an abnormal amount of stress and anxiety induced by the courses. Additionally, research has shown that course performance can increase when students have a positive perception of the course and feel they can achieve a high grade [4]. Overall, the goal of our project was to obtain a snapshot of the current landscape of student perceptions.

We developed a survey to measure various components of students’ perceptions going into an undergraduate business analytics course and used factor analysis to obtain overall findings on factors such as stress and anxiety levels, usefulness, self-efficacy, difficulty level, time commitment and prior knowledge. We also examined the impact of demographic factors such as ethnicity, gender and academic major on student perceptions going into the class. The survey consisted of 28 items using a 7-point Likert scale, seven items to collect demographic information and a free-response section for additional comments or concerns. A few example items are as follows:

• I expect that the course content will be useful in my future business courses.
• Compared to other business courses, how much effort do you think will spend on this course?
• Rate how nervous you feel to take this course.
• What grade do you expect to earn in this course?
• Rate your understanding of plotting linear inequalities.

Pessimistic Outlook

We implemented exploratory factor analysis for data reduction and used an oblimin rotation to generate factor loadings for each variable. The output consisted of eight total factors, summarized by (1) stress/anxiety, (2) probability skills, (3) algebra skills, (4) perceived usefulness, (5) self-efficacy, (6) difficulty, (7) control items and (8) expected outcomes.

There were several key takeaways from the results. Students experience a significant amount of stress regarding this course (item average = 5.62). Next, self-efficacy ratings indicate that students are not very confident that they are prepared for the course and they only feel slightly prepared (item average = 4.50). When asked about their probability skills (about one-third of the class consists of probability), students reported relatively low preparedness, even though an introductory statistics course is a prerequisite. Similarly, the expected grade outcomes were around a C+, indicating a pessimistic view of expected performance. The perceived difficulty was exceptionally high (item average = 6.50), denoting a stigma surrounding the course. Finally, students believed that the course would be moderately useful for their futures in the business world (item average = 5.46).

In addition to our core findings, there were discrepancies between certain demographic factors. First, there were significant differences when observing results between genders (completed responses only consisted of males and females). On average, female responses were significantly higher for the following topics: perceived difficulty, expected time commitment to the course, level of nervousness, stress level and worries about course performance. To summarize, female respondents were notably more worried about the course and believed it would be more difficult than male respondents.

Next, we observed differences in the control item responses between students of different academic majors. Accounting and finance majors were relatively less worried when asked about the general difficulty of quantitative courses, averaging 4.74 and 4.79, respectively. The scores of computer information systems majors were around the midpoint, with an average of 5.00. Marketing majors’ scores were slightly higher, averaging 5.32, and management majors had the highest scores, averaging 5.70. Overall, we can surmise that different majors perceive the course differently simply because of its quantitative nature.

A few individual items display valuable information that is pertinent to our research questions: Students feel that it is extremely important for them to perform well in this course, indicated by an item average of 6.71. They also are not looking forward to the course, with an average of 3.42, signaling the presence of an existing stigma. Finally, students feel they have the necessary support to be successful in the course, with the item averaging 4.98.

The descriptive results of the survey help us understand the gaps in the effectiveness of instruction and lay the groundwork for future research on how to improve students’ experiences in undergraduate business analytics courses. Two pertinent areas of research that would be beneficial to explore are perceptions based on ethnicity and performance outcomes based on gender and academic major.

In conclusion, our investigation revealed both challenges and opportunities to further develop business analytics education. Notably, students felt stressed about the course, expressed low confidence and reported high perceived difficulty, all of which contributed to a pessimistic outlook on expected performance. As we move forward, the relevance of these skills will only increase, and educators must be aware of the importance of students having positive experiences.

References

1. Bughin, J., 2016, “Big data: Getting a better read on performance,” The McKinsey Quarterly, Vol. 1, No. 8.
2. Gavin, M., 2019, “Business analytics: What it is & why it’s important,” Harvard Business School.
3. Mills, R.J., Fadel, K.J., Olsen, T., Chudoba, K.M. and Dupin-Bryant, P.A., 2022, “Examining trends in business analytics education from 2011 to 2020 in AACSB-Accredited Information Systems Programs,” Journal of Information Systems Education, Vol. 33, No. 3, pp. 232-244.
4. Al-Abyadh, M.H.A. and Abdel Azeem, H.A.H., 2022, “Academic achievement: Influences of university students’ self-management and perceived self-efficacy,” Journal of Intelligence, Vol. 10, No. 3, p. 55.