How Institutions Can Offer Students a Liberal Arts and Sciences Education

In a recent report, Ithaka S+R introduced a new methodological approach to defining and quantifying the pedagogical, curricular, and community-based features of a liberal education: the Liberal Arts and Sciences Educational Experience (LASEE) Framework. This framework is designed to measure, at the student level, the extent to which students are experiencing the features of a liberal arts and sciences education and how prevalent those experiences are. We applied the LASEE Framework to student-level longitudinal data from the College and Beyond II (CBII) dataset, consisting of more than 1.3 million students enrolled at public institutions. This allowed us to determine the extent to which individual students experience an education with liberal arts and sciences features. For each student, we assigned a LASEE index score, where lower scores mean less exposure and higher scores mean more. We then generated a LASEE index score for each student and compared those scores to students’ academic, labor market, and civic outcomes (see the report for more details).

Expanding access to liberal arts experiences can yield real benefits for academic success.

Overall, our findings suggest that expanding access to liberal arts experiences can yield real benefits for academic success. In this post, we describe how any college or university can use the LASEE Framework to identify students with low exposure to liberal arts experiences and direct resources to increase their exposure in ways that could improve their academic outcomes.

Benefits of a liberal arts education

Our research shows that pursuing liberal educational experiences pays off. On average, students with greater exposure to liberal arts features achieve better academic outcomes without experiencing negative labor market returns. Since our findings are based on students enrolled in large public institutions, many of which face increasing financial pressures, we sought to provide more targeted guidance on how to allocate their limited resources. To do so, we conducted additional analyses to examine whether the benefits of a liberal arts education vary across different groups of students.

Specifically, we split our sample into four quartile subgroups by ordering students’ LASEE index scores from lowest to highest:

• Bottom Quartile (0-25th percentile)
• Second Quartile (26th-50th percentile)
• Third Quartile (51st-75th percentile)
• Top Quartile (76th-100th percentile)

The table below presents descriptive data on LASEE index scores by quartile. Students in the top quartile scored an average of 40.6 points out of 60, or 68 percent of total available points. On the other end of the spectrum, students in the bottom quartile scored 29.6 points, on average, amounting to 49 percent of total available points. For reference, the average score across all students was 35.0 points, representing 58 percent of total available points.

To test whether some students benefitted more or less from exposure to a liberal arts education, we conducted separate regressions examining the relationship between LASEE index scores, GPA, and six-year graduation rates for students in each quartile. The table below presents the average effect of a one-point increase in LASEE score on both GPA and six-year graduation rate for each quartile.

For both GPA and six-year graduation rate, returns to additional liberal educational exposure are highest among students with the lowest LASEE scores and lowest among students with the highest LASEE scores (and even negative for the six-year graduation rate), an effect that was not evident in our primary analyses. These findings suggest that students with lower LASEE scores benefit more from marginal increases in exposure to a liberal education than their higher-scoring peers.

Implications for institutions

Institutions looking to improve students’ educational outcomes should consider the extent to which their students are experiencing liberal arts and sciences education. There are some global steps that institutional leaders can take that would cut across all students and disciplines. For example:

• Department chairs, working with deans when appropriate, might focus on reducing the size of the largest classes. They can also work with faculty to encourage the use of teaching practices that encourage active learning, such as reducing the number and share of courses that are lecture-based.
• Department leaders could focus on developing curricula that provide breadth and depth, exposing students to multiple disciplines and upper-level coursework. They might also create opportunities for student-guided learning through participation in research or independent study.
• Administrators in student affairs and student life divisions should aim to connect students to enriching experiences and activities outside their coursework. These might include service or community-based learning opportunities, academic organizations, or social clubs.

If, however, institutions have limited resources to increase exposure, boosting those experiences for students who are underexposed could be the most impactful step. Institutional leaders can apply the LASEE Framework to their own data to identify students who score lowest overall and across each dimension, and then target resources to boost their exposure, which has the potential to improve their academic outcomes.

As a diagnostic tool, the LASEE Framework allows higher education institutions to adopt a holistic, systematic, and evidence-based approach to expanding access to the core features of a liberal education and ultimately improving students’ academic and civic outcomes. This targeted allocation of resources is also far more cost-effective than offering additional liberal arts experiences across the entire institution.

If you’re interested in learning more about applying the LASEE Framework to your own student-level data, please reach out to Daniel Rossman (Daniel.Rossman@ithaka.org).

1. Out of 60. ↑
2. All effects are statistically significant at the 99.9 percent confidence level. ↑
3. All effects are statistically significant at the 99 percent confidence level. ↑