Study: Job Earnings Data Does Not Impact Students' Choice of Major

miniature people standing on stacks of coins

In an era where people are demanding that institutions of higher education justify the return on investment of a college education, two researchers have long sought to understand how labor market outcomes influence student decision-making. The latest issue brief by this pair, published by Rutgers University, specifically examined whether access to labor market data changed the choice of major or perceptions of earnings or job security, as well as how that might vary based on whether the student is first-generation or low-income. The bottom line: When students didn't know any better, they expected to earn more than they should, especially in business and STEM fields; yet having access to earning data didn't sway students to consider changing majors.

Michelle Van Noy, assistant research professor and associate director of Rutgers' Education & Employment Research Center, and Alex Ruder, senior community economic development adviser at the Federal Reserve Bank of Atlanta and visiting scholar at the Heldrich Center for Workforce Development at Rutgers, began examining the role of labor market outcomes for student decision-making in 2014. Their newest brief, "Adjusting Expectations: The Impact of Labor Market Information on How Undergraduates View Majors and Careers," relied on data generated in an online survey of undergraduate Rutgers students given during 2015. In total, 4,916 students across all grade levels and majors completed the survey out of an initial panel size of 48,139.

The students were randomly assigned to one of three conditions:

  • They were given no labor market outcomes information;
  • They were given information on median earnings based on employment five years after college; or
  • They were given information on the variation in earnings and job security.

Also, to limit the number of choices students had to work through, the survey focused on six "broad" fields of study: computer, engineering, and physical/ biosciences; healthcare; business; social sciences; education; and humanities. Students were told to pick one of those for their responses. Then everybody was asked to address the same three topics:

  • What they thought they'd earn for fulltime employment five years after graduation;
  • Based on a scale of one to nine, how secure they thought their jobs would be; and
  • The percentage likelihood they'd complete a degree in the field of study.

What did the researchers discover?

First, students who received no earnings information had the highest expectations. Those who received earnings data had lower expectations, though those who received median earnings data only had somewhat lower earnings expectations than those who saw variations in earnings. The differences, according to the researchers, were "sizable and significant" — especially among those in business and STEM. As the report noted, "Students may have formed perceptions of potential earnings in these fields that were driven by this attention and then were adjusted by the earnings data they observed." For example, for those in STEM majors, students supplied with no data estimated an annual salary of $86,720, compared to $76,953 for those outfitted with the median earning information and $80,000 for those given information about the variation in earnings. (The median salary students were supplied with was $60,000; the variation showed a low percentile of $43,000 and a high percentile of $75,000.)

Students who viewed median earnings had lower earnings expectations relative to those with no information, regardless of the students' low-income or first-generation status.

Information didn't influence students' perceptions of job security, no matter what field of study.

Finally, the earnings data didn't change the students' choices of major. "Students' choice of major is a highly complex process influenced by many factors, and this information on earnings alone is likely to be insufficient to substantially sway students' decisions," the report explained.

Overall, suggested the researchers, earnings information can help students better understand their potential earning power as they make decisions about majors or develop expectations for their job searches. "More information on the types of skills and experiences that would help students move to the higher end of the earnings distribution across a range of majors may better inform students in their preparation for a career," they concluded.

The full issue brief is openly available on the Rutgers website.

About the Author

Dian Schaffhauser is a former senior contributing editor for 1105 Media's education publications THE Journal, Campus Technology and Spaces4Learning.

Featured

  • abstract pattern with interconnected blue nodes and lines forming neural network shapes, overlaid with semi-transparent bars and circular data points

    Data, AI Lead Educause Top 10 List for 2025

    Educause recently released its annual Top 10 list of the most important technology issues facing colleges and universities in the coming year, with a familiar trio leading the bunch: data, analytics, and AI. But the report presents these critical technologies through a new lens: restoring trust in higher education.

  • digital brain made of blue circuitry on the left and a shield with a glowing lock on the right, set against a dark background with fading binary code

    AI Dominates Key Technologies and Practices in Cybersecurity and Privacy

    AI governance, AI-enabled workforce expansion, and AI-supported cybersecurity training are three of the six key technologies and practices anticipated to have a significant impact on the future of cybersecurity and privacy in higher education, according to the latest Cybersecurity and Privacy edition of the Educause Horizon Report.

  • Campus Technology Product Award

    Call for Entries: 2024 Campus Technology Product Awards

    The entry period for the 2024 Campus Technology Product Awards is now open.

  • open laptop with screen depicting a glowing, holographic figure surrounded by floating symbols of knowledge like books, equations, and lightbulbs

    Cengage Intros Gen AI Student Assistant Beta

    Ed tech company Cengage has announced the beta launch of Student Assistant, a generative AI tool designed to guide students through the learning process with personalized resources and feedback.