Evaluating an Adaptive Learning Intervention in Statistics for Economics

Last registered on September 21, 2026

Pre-Trial

Trial Information

General Information

Title
Evaluating an Adaptive Learning Intervention in Statistics for Economics
RCT ID
AEARCTR-0019736
Initial registration date
September 15, 2026

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
September 21, 2026, 9:33 AM EDT

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

Locations

Primary Investigator

Affiliation
University of Southampton

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-09-21
End date
2027-09-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The study of Economics at university heavily relies on quantitative (mathematical) skills.Often students differ substantially in their pre-existing knowledge of mathematical concepts used in economics, depending e.g. on their choice of A levels or whether their secondary education was in the UK or overseas. Differences in pre-existing knowledge are likely to impact students’ learning experience in their Economics degree programme. Moreover, students’ knowledge endowment from secondary education is likely to differ systematically with demographic characteristics (SES included) thus raising issues of ensuring equal opportunity for all our students.
Existing research indiates the presence of differences in academic outcomes by student background, which can partially be explained by individal preparedness and pre-existing knowledge of quantitative skills. This study will investigate whether targeted support in the form of adaptive learning help to close any gaps in academic performance.
To do so this study will use experimental methods to investigate whether the introduction of an adaptive learning method into the module Statistics for Economics has an effect on student outcomes, in the form of exam grades, and on behaviour, in the form of enagement.
The results can inform educational policy at the host institution and elsewhere, for instance if a positive effect is identified that is large enough to be economically relevant.
External Link(s)

Registration Citation

Citation
Gall, Thomas. 2026. "Evaluating an Adaptive Learning Intervention in Statistics for Economics." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.19736-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2027-01-25
Intervention End Date
2027-05-31

Primary Outcomes

Primary Outcomes (end points)
The key outcome of interest is individual final exam performance.
Primary Outcomes (explanation)
We are mainly interested in heterogeneous treatment effects, that is in final exam performance conditional on predicted exam performance and assigned groups.

Secondary Outcomes

Secondary Outcomes (end points)
The secondary outcome of interest is student engagement.
Secondary Outcomes (explanation)
Student

Experimental Design

Experimental Design
The population of interest (student on the module) will be randomly divided into two two groups. The first group will receive educational content according to the intervention, while the second group will receive the same educational content as prior cohorts before the intervention.
Experimental Design Details
Not available
Randomization Method
Randomisation by computer in office.
Randomization Unit
Individual
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
400 individuals.
Sample size: planned number of observations
400
Sample size (or number of clusters) by treatment arms
200 in treatment group, 200 in control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The past year's exam grade distribution on the module had standard deviation 15.4. Setting alpha=0.05 and 1.beta=0.80 the mimimally detectable effect size for 200 units per group is 4.33 marks, which corresponds to 9%. Therefore the experiment is able to detect an effect size that is likely to persuade universities to spend resources on rolling out the intervention further.
IRB

Institutional Review Boards (IRBs)

IRB Name
Univerity of Southampton FSS Faculty Ethics Committee
IRB Approval Date
2026-07-30
IRB Approval Number
83113.A3