Working Papers

Identifying the STEM Learning Technology: Evidence from Online Learning (2023)

The number of annual graduates with STEM degrees has grown dramatically over the past decade. Despite this growth, many students enrolled in STEM struggle to complete their program. An inherent feature of STEM education is that it has a natural cumulative learning structure which makes learning advanced skills in STEM quite challenging. This paper is the first to credibly estimate the cumulative learning technology in a foundational STEM course. Doing so is incredibly challenging as precise measures of effort inputs are typically unavailable and are also dynamic endogenous choice variables. To overcome such challenges, I first gather rich data covering 3,700 undergraduates at a large public university taking an online introductory programming course that has a cumulative structure. The online learning environment serves to monitor students' effort allocation and knowledge accumulation at each stage of the learning process. Then I carry out a field experiment that generates period-by-period exogenous variation in effort allocation, enabling me to identify dynamic interactions across effort inputs in the learning technology. I find evidence of dynamic learning complementarities as the marginal benefit to studying in each learning period is increasing in prior knowledge accumulated. Additionally, I find that effort investment in earlier learning periods results in larger productivity gains for future effort exertion. These results have implications for effective learning strategies and approaches to course design which are further investigated in related work.

Study Smarter, Not Harder: Designing Grading Schemes to Encourage Effective Effort Allocation (2023)

STEM education has expanded dramatically over the past decade, yet significant learning challenges remain. In light of these, my paper examines how students in STEM can be guided to learn effectively through the design of the course grading scheme. To do so, I first gather rich data covering 3,700 undergraduates at a large public university taking an online introductory programming course that has a cumulative structure. The data allow me to monitor students' study time precisely and to characterize whether they are forward-looking. I then develop and estimate a multi-stage behavioural model of student effort supply. The marginal benefits and costs of effort at each stage of the cumulative learning process are credibly identified using field experiments covered in other related work. The estimated model allows me to explore the efficacy of changing assignment grading weights to improve student learning. I find that the simulated weights that maximize learning are decreasing across assignments, serving to increase effort by myopic students early in the course when they acquire foundational skills. Additional simulations suggests that in a course with a strong cumulative structure, incentives should be front-loaded when majority of students are myopic, middle-loaded when a modest share of students are myopic, and end-loaded when the vast majority of students are forward-looking.

Provision of Online Public Goods: Evidence From a Peer Discussion Board (2023)

How does a policy designer maintain an actively participating online community in the presence of free-rider incentives? This paper studies the question in the context of voluntary online student discussion boards -- a prominent feature of distance education used to support learning at scale. I first collect rich survey and administrative data covering nearly 1200 undergraduate students in a foundational programming course at a large public university. The data allow me to observe the number of unique posts read and written, and characterize students' altruistic attitudes. I then conduct two randomized informational interventions, successfully nudging students to sign-up and then contribute further to the discussion board. The first intervention informs students about availability of the voluntary discussion board, and the next intervention is a writing exercise that helps them internalize the spillover value of peer discussion. I find that having access to and participating in discussion board significantly improves students' learning outcomes. I then develop and estimate a behavioural model of peer discussion board provision. The estimated model allows me to simulate participation in the discussion board when all students cooperate to maximize aggregate learning. I find that students in the control group provide 21% less contributions than the simulated social optimal allocation. Additional simulations show that free-riding can be mitigated by offering students appropriate bonus credit for writing valuable content that is endorsed by the instructor.

Work in Progresss

Effects of Structured Support from Leader on Employee Engagement (2023), with Simone Haeckl and Mari Rege [AEA RCT Registry]

We have developed a web application aiming to increase leaders' supportive leadership behaviors. This paper studies whether receiving structured support from leader increase employee motivation, reduce turnover, and improve store performance. The study takes place across several grocery stores which are part of a large supermarket chain in Norway.

Encouraging High-achieving Students to Enroll in Advanced Courses (2022), with Robert McMillan and Linda Wang

High-achieving students often enrol in less challenging university courses despite the availability of rigorous course options better suited to their capabilities. This practice can restrict which courses they can take in future, and have adverse effects on students' human capital development more generally. This paper studies whether high-achieving students can be `nudged' successfully to follow a more ambitious track. To that end, we conduct several field experiments across four student cohorts in a large research-intensive Canadian university, informing high-achieving first year economics students about advanced upper-year courses in various ways. The nudging approaches differ in their cost and scalability. We find that providing an in-person information session significantly increases the probability of eligible first-year students enrolling in the most rigorous second-year economics courses. The enrolment impacts are especially strong for first-generation university students, who are initially less aware of the availability of advanced course alternatives. In contrast, the same information delivered through an email message or an online information session does not have any statistically significant effect on students' propensity to enrol in advanced courses. Our analysis indicates that resource-intensive nudges that rely on personal contact can have significant impacts, relevant for university course enrolment policies.