Author
Listed:
- Vanitha Virudachalam
(Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, Illinois 61820)
- Sergei Savin
(The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)
- Matthew P. Steinberg
(Accelerate, Brooklyn, New York 11217)
Abstract
U.S. K–12 school districts that traditionally utilized ongoing “formative” assessments of student progress increasingly rely on additional “interim” assessments to predict student performance on standardized tests. Moreover, some districts are experimenting with merit-based teacher bonuses tied to standardized test scores. We examine the relationship between interim assessments and teacher bonuses using a two-period principal–agent model. The school district (principal), operating under a limited budget, decides whether to implement interim assessments and how much merit pay to offer, and teachers (agents) choose how much effort to exert in each period. We use two-state (proficient versus not proficient) Markovian dynamics to describe the evolution of student test readiness, in which the transition probability in a given period depends on both teachers’ effort decisions and the starting state. Our results indicate that, despite the popularity of interim assessments, their usefulness is far from guaranteed. In particular, the accuracy promised by these assessments is a double-edged sword: positive midyear results can make it easier to incentivize second period teacher effort, but negative results can have a demotivating effect. Moreover, even when an interim assessment does result in a higher probability of the school ending the year in the proficient state, the resulting higher expected costs of merit-based bonuses for the district may exceed the available budget. Thus, even a free interim assessment might be too expensive for the school district.
Suggested Citation
Vanitha Virudachalam & Sergei Savin & Matthew P. Steinberg, 2024.
"Too Much Information: When Does Additional Testing Benefit Schools?,"
Management Science, INFORMS, vol. 70(9), pages 6220-6233, September.
Handle:
RePEc:inm:ormnsc:v:70:y:2024:i:9:p:6220-6233
DOI: 10.1287/mnsc.2020.01547
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:70:y:2024:i:9:p:6220-6233. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.