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Using tablet-based testing to reduce cheating in large-scale student assessments in Andhra Pradesh
Last registered on June 17, 2020


Trial Information
General Information
Using tablet-based testing to reduce cheating in large-scale student assessments in Andhra Pradesh
Initial registration date
June 17, 2020
Last updated
June 17, 2020 10:32 AM EDT
Primary Investigator
Stockholm School of Economics
Other Primary Investigator(s)
Additional Trial Information
On going
Start date
End date
Secondary IDs
This experiment aims to assess if tablet-based testing may reduce cheating in large-scale official assessments. This was done in the context of a large testing program, conducted by the Government of Andhra Pradesh with support from Central Square Foundation, in February 2019 which covered all Grade 4 students in all schools in one district (Prakasam) which had more than 5 students enrolled in G4. In two-thirds of the schools, the test was conducted on tablets taken to the school by the Cluster Resource Person. In the remaining third, students were tested on paper-based tests with the answer scripts graded centrally. Students in a subset of schools were tested again with external proctoring, all using paper-based assessments, to provide an external benchmark for comparison for the two treatment arms. The goal of the study is to compare cheating between the two types of test administration (tablet and paper) both using analysis flagging suspicious response patterns and, in a subset of schools, comparison with the external benchmark.
External Link(s)
Registration Citation
Singh, Abhijeet. 2020. "Using tablet-based testing to reduce cheating in large-scale student assessments in Andhra Pradesh." AEA RCT Registry. June 17. https://doi.org/10.1257/rct.6018-1.0.
Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Our core objective is to compare cheating in schools which were tested using paper-based assessments to those tested using tablet-based assessments.

We will measure this in two ways: (a) through direct comparison with the retest audit in 120 schools and (b) through an analysis of suspicious response patterns in the item-level data from the full assessment, as done in the testing literature elsewhere.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We set up a large-scale experiment covering all schools with at least 5 students enrolled in Grade 4 in one district in February 2019.

Randomization was carried out not at the level of the individual school but at the level of an academic cluster which typically covers multiple villages. This was to keep the mode of testing unchanged within a single educational market so that schools within the same community could be fairly compared in student report cards. Out of 284 clusters, 196 were assigned for tablet-based testing and the remainder 88 to paper-based testing. All schools within a cluster were assigned to be tested using the same protocol (whether paper or tablets).
There was one pre-determined deviation from the initially-assigned status. Academic clusters, for the most part, nest villages/urban wards but not always. In such cases, if cluster A and B were in different treatment arms, the treatment status of all schools in the village was reassigned to be the same. For instance, if a village had 6 schools, 4 of which are in cluster A and 2 in cluster B, the treatment status of all schools in the village was reassigned to be the same as Cluster A. Such reassignment affected 191 schools out of 2462 schools, which are disproportionately urban areas. In the final sample, 768 schools were assigned for paper-based testing and 1694 to tablet-based testing.

Students, across both treatment arms, were assessed in three subjects – Mathematics, Telugu (the official state language), and English – using the same test papers in February 2019. The tests were designed centrally and intended to capture a wide range of variation. All questions in the test booklets were multiple choice items. In each subject, to deter student cheating, three test booklets (“sets”) were created which had 80% of items in common but with some distinct items and with a distinct ordering of test questions. In schools assigned to paper-based assessment, the test booklets were sent with clear instructions for schools to administer the tests and for the answer scripts to be returned to the Mandal Education Office (the administrative unit above schools). Tablets were taken to the school by a Cluster Resource Person (CRP), each student was given an individual tablet to work on and the test booklet for each subject was decided by the software directly.

The analysis in this study will compare the responses of students who were assessed using tablet to those who were assessed using paper booklets. A potential problem in this comparison is that students may underperform in tablet-based assessments, not only due to potential distortion in paper-based tests but also because they are not familiar with tablet-based tests. Thus, we randomly sampled 120 schools, spread equally across the paper and tablet-based testing arms, and retested students using a traditional paper assessment but with external proctoring and test administration by the research team. This retest was conducted within two weeks of the original assessment but could only be completed in 117 schools.
Experimental Design Details
Randomization Method
On a computer, done by Principal Investigator
Randomization Unit
At teh academic cluster level
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
284 clusters
Sample size: planned number of observations
In the final sample, 768 schools were assigned for paper-based testing and 1694 to tablet-based testing.
Sample size (or number of clusters) by treatment arms
196 clusters in the tablet-based testing arm, 88 clusters in the paper-based testing arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Institute for Financial Management and Research Human Subjects Committee
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)