Malleability of Sustained Attention

Last registered on January 25, 2019

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Pre-Trial

Trial Information

General Information

Title

Malleability of Sustained Attention

RCT ID

AEARCTR-0002673

Initial registration date

January 25, 2019

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

January 25, 2019, 6:44 PM EST

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

Locations

Country

India

Region

Lucknow

Primary Investigator

Name

Christina Brown

Affiliation

University of Chicago

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Other Primary Investigator(s)

PI Name

Heather Schofield

PI Affiliation

University of Pennsylvania

Contact Investigator

PI Name

Supreet Kaur

PI Affiliation

University of California, Berkeley

Contact Investigator

Additional Trial Information

Status

On going

Start date

2017-08-28

End date

2020-12-31

Keywords

Education

Additional Keywords

Behavioral Economics, Psychology and Economics

JEL code(s)

J24, I2, D9

Secondary IDs

Abstract

The economics and education literatures traditionally view human capital as an individual's stock of knowledge and skills. In this project, we posit an additional potential component: the capacity for sustained attention. In cognitive psychology, the mind's ability to direct and sustain attention is thought to underlie all activity: cognitive processes (such as solving a math problem) as well as non-cognitive activities (such as exerting self-control) (Chun et al. 2011). In this project, we examine whether the capacity for exerting sustained attention is malleable. Using a field experiment, we introduce a novel tablet-based adaptive learning platform into low-income Indian primary schools. The platform engages students in sustained practice in either mathematics or cognitive activities for 30 minutes at a time, several days a week for the academic school year. For many students, who typically face disruptive classroom environments and exert little focused direction of attention at home or school, this intervention drastically boosts the amount of sustained attentional practice they receive. We will quantify treatment effects on sustained attention using standard laboratory tests from cognitive psychology, practical tests of attention and performance decline over the course of traditional subject tests. If we find impacts on such outcomes, this would suggest broadening our view of the cognitive dimensions of human capital, and how it is shaped through schooling.

External Link(s)

Registration Citation

Citation

Brown, Christina, Supreet Kaur and Heather Schofield. 2019. "Malleability of Sustained Attention." AEA RCT Registry. January 25. https://doi.org/10.1257/rct.2673-1.0

Former Citation

Brown, Christina, Supreet Kaur and Heather Schofield. 2019. "Malleability of Sustained Attention." AEA RCT Registry. January 25. https://www.socialscienceregistry.org/trials/2673/history/40686

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Students are randomly assigned to one of three experimental arms. Each arm will vary how students spend their three 30-minute program periods each week. The three arms are:
1. Treatment 1 - Tablet-based math practice: Students are given a tablet with math software and asked to work on problems in the given module which matches the topic being covered in their math class. The math software used is dynamically adaptive, provides students with the correct answer after each question and is more visually appealing than working in paper and pencil.
2. Treatment 2 - Tablet-based cognitive activity practice: Students are given a tablet with a cognitive activity which requires focused attention for an extended period of time. The activities are rotated through every few weeks and include memory activities (memory tile and n-back), maze-like activities (flow free), and spatial awareness activities (tangrams and Tetris). These activities are free of any math content.
3. Control - Status quo math practice (Control): This class is structured to similar to the style of practice in their regular math classes. The teacher provides students with a small number of problems to work on independently. The problems given are the same ones that students would see on the tablet, so the content itself is constant across this arm and treatment 1.

These program periods would have been study-hall, elective or assembly periods in the absence of the program, so students do not miss any of their core instruction periods as a result of the study.

In addition, students in all sections will receive 1 period of math instruction roughly once per two weeks.

Intervention Start Date

2017-09-11

Intervention End Date

2019-06-30

Primary Outcomes

Primary Outcomes (end points)

The outcomes we will measure are students' performance on a grade-level math exam, a Ravens Progressive Matrices task and three sustained attention measures: the Sustained Attention to Response Task (SART), symbol search task and a listening attention task.

Primary Outcomes (explanation)

We will look at the percent correct and rate of decline over the length of the task.

To look at the effect of the math software, we will also separately look at the effect on basic skills, such as those defined by ASER, and overall performance.

Secondary Outcomes

Secondary Outcomes (end points)

We will attempt to collect observational data on students' behavior and attentional capacity during their class periods. We will also try to obtain administrative behavior data and student assessment data from the school.

Secondary Outcomes (explanation)

Experimental Design

Students in grades 1-5 will be randomly assigned to one of three experimental arms:
- Treatment 1: Tablet-based math practice
- Treatment 2: Tablet-based cognitive activity practice
- Control: Status quo math practice

Our design allows to estimate the effect of additional focused math practice through the use of the tablet on student's math ability, decline over the length of the math exam and broad measures of attention by comparing treatment 1 to the control. By comparing treatment 2 versus control on our attention outcomes, we can also see if we remove any academic content, are we able to train attention skills more broadly.

The randomization will be stratified by grade and baseline income and math performance. Baseline measures of the main outcomes will be collected to the extent it is operationally feasible given school operational constraints and used as a control throughout our analysis.

Experimental Design Details

Randomization Method

Randomization of students into treatments is done using Stata.

Randomization Unit

Students are individually randomized. Randomization is stratified by grade, baseline academic performance, and household income.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

We will have approximately 1400 students total in the sample. The final numbers may change based on enrollment changes in our partner schools. The randomization is at the student level.

Sample size: planned number of observations

We will have approximately 1400 students total in the sample.

Sample size (or number of clusters) by treatment arms

Our sample is evenly split between the three experimental arms, with approximately 465 students in each arm.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Accounting for one baseline measurement of our outcomes, the projected correlation between the baseline and endline measures, and the sample size, we are powered to detect a 0.1 standard deviation effect on our main outcomes (alpha = 0. 5, power = 80%).

Supporting Documents and Materials

IRB