Role of Beliefs on Study Effort

Last registered on April 12, 2023


Trial Information

General Information

Role of Beliefs on Study Effort
Initial registration date
March 17, 2017

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
March 19, 2017, 11:58 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
April 12, 2023, 1:51 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

University of Chicago

Other Primary Investigator(s)

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.

Study effort is one of the most important determinants of student performance. Are students aware of how effort translates into performance? And if they are not, can we inform them about this relationship to change their study behavior and outcomes? Through a framed field experiment, this project aims to answer these questions in the context of an online language-learning platform.
External Link(s)

Registration Citation

Ersoy, Fulya. 2023. "Role of Beliefs on Study Effort." AEA RCT Registry. April 12.
Former Citation
Ersoy, Fulya. 2023. "Role of Beliefs on Study Effort." AEA RCT Registry. April 12.
Sponsors & Partners

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Experimental Details


Stage 1: Participants in Stage 1 are induced to exert different levels of effort depending on their random group assignment.

Stage 2: Participants are randomly assigned in one of the 4 groups: Participants in the control arm do not receive information. Participants in treatment arms are provided with information about the effect of effort on performance for Stage 1 participants. Depending on which treatment arm they are, they get somewhat different information.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
The beliefs about how effort affects performance

How many lessons completed during the study period (effort measure)

Improvement in test scores (Will be measured as the difference between final test score and initial test score)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Stage 1: Measuring the Causal Relationship Between Effort and Performance
In Stage 1, participants first complete an initial survey and take an online assessment test. The main aim of the survey is to collect demographic information about participants. The test assesses their initial level of knowledge of Spanish. Participants then sign up for an online language-learning platform. Participants are randomly allocated to online classrooms with different assignment levels. After studying through the platform as assigned for one month, they take another online test that assesses their final level of knowledge and they answer a short survey about their study behavior.

Stage 2: Eliciting and Changing Beliefs about How Effort Affects Performance
In Stage 2, participants first complete the initial survey and take the online assessment test. They then sign up for the same online language-learning platform. Every week, they complete a survey eliciting their beliefs about the importance of study effort on determining performance. After the first belief elicitation survey, a random subset of the participants receives information regarding the effect of the study effort on performance, which is based on the information collected in Stage 1 whereas the others do not receive such information. Participants in Stage 2 are free to study through the platform as much as they like for one month. At the end of study period, they take the final test and answer a short end survey about their study patterns.
Experimental Design Details

Randomization Method
Randomization done in office by a computer using the "" website.
Randomization Unit
Randomization unit is the individual.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
600 participants
Sample size: planned number of observations
600 participants
Sample size (or number of clusters) by treatment arms
Stage 1: 150 participants
Effort Group 1: 30
Effort Group 2: 30
Effort Group 3: 30
Effort Group 4: 30
Effort Group 5: 30

Stage 2: 460 participants
No Information: 115
Information Group 1 : 115
Information Group 2: 115
Information Group 3: 115
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Stanford University
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
August 01, 2017, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
August 01, 2017, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

While distance learning has become widespread, causal estimates regarding returns to effort in technology-assisted learning environments are scarce due to high attrition rates and endogeneity of effort. In this paper, I manipulate effort by randomly assigning students different numbers of lessons in a popular online language learning platform. Using administrative data from the platform and the instrumental variables strategy, I find that completing 9 Duolingo lessons, which corresponds to approximately 60 minutes of studying, leads to a 0.057–0.095 standard deviation increase in test scores. Comparisons to the literature and back-of-the-envelope calculations suggest that distance learning can be as effective as in-person learning for college students for an introductory language course.
Ersoy, F. Returns to effort: experimental evidence from an online language platform. Exp Econ 24, 1047–1073 (2021).
How does the perceived relationship between effort and achievement affect effort? To answer this question, I conduct a framed field experiment with a popular online learning platform. I exogenously manipulate students’ beliefs about returns to effort by assigning them to a control group or to treatments which provide information about returns to effort. Students update their beliefs towards the information and change their study effort in the same direction with the shifts in their beliefs. This result shows that low-cost information interventions can influence students’ beliefs about returns to effort and these beliefs are important components of their effort choices.
Fulya Ersoy, Effects of perceived productivity on study effort: Evidence from a field experiment, Journal of Economic Behavior & Organization, Volume 207, 2023, Pages 376-391.

Reports & Other Materials