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STRATEGIC SCHOOL STAFFING: WHAT PERSONELL INVESTMENTS DO TEACHERS FAVOR?
Last registered on October 29, 2020

Pre-Trial

Trial Information
General Information
Title
STRATEGIC SCHOOL STAFFING: WHAT PERSONELL INVESTMENTS DO TEACHERS FAVOR?
RCT ID
AEARCTR-0006600
Initial registration date
October 28, 2020
Last updated
October 29, 2020 7:20 AM EDT
Location(s)

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Primary Investigator
Affiliation
Harvard
Other Primary Investigator(s)
PI Affiliation
UC-Berkeley
Additional Trial Information
Status
In development
Start date
2020-11-01
End date
2021-01-01
Secondary IDs
Abstract
A critical responsibility of school and district leaders is to attract, develop, and retain teachers. Efforts to succeed in these core tasks have proven notoriously challenging for many school districts across the United States. One factor that adds to this challenge is that policymakers must make decisions on how to manage the teacher workforce with insufficient information on teachers’ preferences. In this study, we collect information on teachers' preferences over compensation, benefits, and other non-pecuniary rewards. To identify the personnel investments teachers favor, we conduct a discrete choice survey experiment where we ask teachers to consider five sets of two hypothetical school profiles and then indicate which school they prefer. We describe each school profile using seven attributes, each of which represents a distinct personnel investment.

Better understanding how teachers value plausible alternative personnel investments is particularly important for at least two reasons. First, personnel costs are the single largest line item on a school budget, accounting for 80% of expenditures in the average public school (NCES, 2020). Second, personnel decisions determine teachers’ salaries and benefits, their class size, and their access to helpful colleagues (e.g. nurses, counselors, instructional coaches)- each of which may play an important role in shaping teachers' employment decisions.
External Link(s)
Registration Citation
Citation
Lovison, Virginia and Cecilia Mo. 2020. "STRATEGIC SCHOOL STAFFING: WHAT PERSONELL INVESTMENTS DO TEACHERS FAVOR?." AEA RCT Registry. October 29. https://doi.org/10.1257/rct.6600-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2020-11-01
Intervention End Date
2020-11-30
Primary Outcomes
Primary Outcomes (end points)
The probability a teacher prefers a school profile
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Discrete choice experiment: We present teachers with two fictional school profiles and ask teachers which school they prefer. We describe each school profile using the following seven attributes: salary, class size, childcare benefits, and the presence or absence of support staff, including school nurses, school counselors, special education specialists, and instructional coaches. The specific value of each attribute is populated at random. The random variation in attribute levels allows us to estimate the average change in the probability a teacher chooses a school profile when it includes the attribute “treatment” value rather than the attribute “reference” value, holding constant all other attributes
Experimental Design Details
Not available
Randomization Method
Randomization done by computer
Randomization Unit
Attribute level
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
N/A
Sample size: planned number of observations
1,000 US K-12 public teachers will complete the choice task 5 times for a total of 5,000 observations
Sample size (or number of clusters) by treatment arms
N/A
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect size for this study is .02. This number reflects the change in the probability a teacher prefers a given school due to the inclusion of a specific attribute.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Harvard
IRB Approval Date
2002-05-19
IRB Approval Number
IRB20-0756 (EXEMPT)
Analysis Plan

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