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Studying without distractions? The effect of a digital blackout on academic performance
Last registered on September 03, 2020

Pre-Trial

Trial Information
General Information
Title
Studying without distractions? The effect of a digital blackout on academic performance
RCT ID
AEARCTR-0006378
Initial registration date
September 03, 2020
Last updated
September 03, 2020 7:28 AM EDT
Location(s)

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Primary Investigator
Affiliation
Bocconi University
Other Primary Investigator(s)
PI Affiliation
Bocconi University
Additional Trial Information
Status
In development
Start date
2020-09-07
End date
2021-01-29
Secondary IDs
Abstract
Rising concerns about the effects of technological distractions on concentration and learning outcomes are making us question which are the most efficient ways of studying and using smartphones. In order to investigate this issue, I want to randomize a treatment to first-year students at Bocconi University and provide them with an app that helps them disconnect from distractions on their smartphones. The treatment will last for several weeks up to the mid-term exams, and through surveys before and after the intervention I will try to detect some relevant effects on academic performance, expectations about exam grades, appreciation of courses, and from social influence.
External Link(s)
Registration Citation
Citation
Garbin, Francesca and Pamela Giustinelli. 2020. "Studying without distractions? The effect of a digital blackout on academic performance." AEA RCT Registry. September 03. https://doi.org/10.1257/rct.6378-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
The objective of this experiment is to test whether using an app for blocking digital distractions is effective or not for improving academic outcomes, and eventually to quantify this effect. Students will use this app for several weeks in order to prompt possible habit changes. In case positive results are obtained, this research will be a valuable instrument to support the future implementation of a wider scheme aimed at all students.
Intervention Start Date
2020-09-21
Intervention End Date
2020-10-16
Primary Outcomes
Primary Outcomes (end points)
The analysis will use as outcome variables: grades and GPA both in the first semester and in the following ones; students' expected and perceived performance before and after taking the exams; students’ appreciation of courses; realized study time, that might be affected by the treatment; other academic expectations. Heterogeneous effects may be assessed thanks to app data on frequency and length of breaks during the digital blackouts. Treatment effects may be analysed in the form of intention-to-treat analysis.
Primary Outcomes (explanation)
Primary outcomes stem from both survey measures and administrative data, and are combined with the data coming from app usage. Surveys are administered at baseline before the intervention, and after the intervention at different points in time during the semester.
Secondary Outcomes
Secondary Outcomes (end points)
The analysis may be focused on other relevant factors in the education production function and on time usage. Survey questions collect a wide variety of both pre-intervention and post-intervention information that can be exploited in the analysis. Family inputs can be analysed in order to detect heterogeneous patterns. Elements related to socio-economic background, well-being, personality traits, study habits, COVID-19 risk perception, technology use and history, academic expectations, and social networks may be used as well.
Secondary Outcomes (explanation)
The surveys explore many types of outcomes and can be used to construct other relevant variables.
Experimental Design
Experimental Design
I implement an experiment with first-year Bocconi students to study whether distractions coming from smartphones are detrimental to the academic performance. At the beginning of the first semester, I survey eligible students in order to gather general information about their background and their habits, and their willingness to participate in the experiment. Students are randomized into the treatment and are asked to download a blocking app on their smartphones. The app blocks other apps and their notifications (e.g. social media, messaging, news). Students are asked to activate it according to a certain schedule for the four weeks of the experiment. During the experiment, students make the conscious and intentional choice to remain off their phones by using the app.
Experimental Design Details
Not available
Randomization Method
Students who complete the first two surveys and agree to participate in the experiment will be randomly divided into two groups. The control and treatment groups will be randomized according to some stratifying variables, possibly subject to changes depending on the number of respondents. Randomization will be done using the statistical software Stata.
At the end of the intervention, treated students will be randomized in order to receive the newsletter or not. This randomization will not be based on any stratifying variable, and it will also be computer-based.
Randomization Unit
Randomization is conducted at the individual level.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
The goal is to have at least several hundred students involved, in order to have hundreds of treated individuals. A maximum of 400 individuals can be treated, as this number corresponds to the number of app licenses currently purchased.
Sample size: planned number of observations
The design is not clustered, so the number of clusters and the number of observations correspond.
Sample size (or number of clusters) by treatment arms
The goal is to have an almost balanced number of treated and control students.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Bocconi Research Ethics Committee
IRB Approval Date
2020-07-21
IRB Approval Number
FA000028