|
Field
Abstract
|
Before
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.
|
After
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 assign first-year students at Bocconi University to the use of an app that helps them disconnect from distractions on their smartphones. The treatment lasts for several weeks up to the mid-term exams, and through surveys before and after the intervention I aim to detect relevant effects on academic performance, expectations about exam grades, course evaluations, and network influence.
|
|
Field
Trial End Date
|
Before
January 29, 2021
|
After
July 31, 2021
|
|
Field
Last Published
|
Before
September 03, 2020 07:28 AM
|
After
December 10, 2020 04:09 AM
|
|
Field
Intervention End Date
|
Before
October 16, 2020
|
After
March 12, 2021
|
|
Field
Primary Outcomes (End Points)
|
Before
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.
|
After
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, and thanks to network structure position. Treatment effects may be analysed in the form of intention-to-treat analysis.
|
|
Field
Experimental Design (Public)
|
Before
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.
|
After
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.
The intervention will run in the second semester (Spring 2021) as well.
|
|
Field
Randomization Method
|
Before
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.
|
After
In the first semester randomization into treatment has not been feasible due to a small amount of participants: randomization would have prevented the eventual detection of statistically significant effects. The analysis on the first semester group ("the pilot") is carried out using propensity score matching.
In the second semester students who 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.
|
|
Field
Planned Number of Clusters
|
Before
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.
|
After
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. In particular, in the second semester a maximum of 310 licenses will be made available.
|
|
Field
Additional Keyword(s)
|
Before
Technological Distractions, Education Production Function, Smartphone, Undergraduate Students, Multitasking, Time Allocation, Randomized Experiment
|
After
Technological Distractions, Education Production Function, Smartphone, Undergraduate Students, Multitasking, Time Allocation, Propensity Score Matching
|