The impact of financial education on financial literacy, economic preferences and heuristics and biases in decision-making – an intervention study in schools

Last registered on February 10, 2026
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Pre-Trial

Trial Information

General Information

Title
The impact of financial education on financial literacy, economic preferences and heuristics and biases in decision-making – an intervention study in schools
RCT ID
AEARCTR-0017854
Initial registration date
February 07, 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
February 10, 2026, 6:40 AM EST

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

Locations

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Primary Investigator

Name
Nora Veith
Affiliation
Max Planck Institute for Behavioral Economics
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Other Primary Investigator(s)

PI Name
Matthias Sutter
PI Affiliation
Max Planck Institute for Behavioral Economics
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PI Name
Sebastian O. Schneider
PI Affiliation
Max Planck Institute for Behavioral Economics
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PI Name
Michael Weyland
PI Affiliation
Ludwigsburg University of Education
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PI Name
Simon Jersak
PI Affiliation
Ludwigsburg University of Education
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PI Name
Maria Ritter
PI Affiliation
Ludwigsburg University of Education
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PI Name
Manuel Froitzheim
PI Affiliation
University Siegen
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PI Name
Jacqueline Dreisbach
PI Affiliation
University Siegen
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Additional Trial Information

Status
In development
Start date
2026-02-09
End date
2027-09-30
Keywords
Behavior, Education
Additional Keywords
Financial Education, Financial Literacy, risk and time preferences, decision-making behavior, heuristics and biases, online learning environment
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Financial literacy is increasingly recognized as an essential life skill due to rising living costs, growing demands for private financial planning, and increased individual responsibility (OECD, 2020). It refers to an individual’s ability to understand and effectively manage everyday financial matters, enabling them to make informed decisions. Despite this, significant gaps in financial knowledge persist around the globe, in particular also because financial literacy is rarely taught in schools. Nevertheless, recent studies show that school-based programs can effectively enhance financial literacy (e.g., Sutter et al., 2023).

This project develops and evaluates a school-based intervention designed to improve students’ financial literacy. We introduce two different treatments that emphasize different ways to teach financial literacy. The control treatment (which involves no intervention related to financial literacy) serves as the comparison for both treatment arms. First, we study the treatment effects on the level of financial literacy. Second, like in previous work (Sutter et al., 2023), we examine potential treatment effects on risk and time preferences. Third, we investigate treatment effects on decision making tasks that are intended to capture heuristics and biases, a hitherto unexplored aspect of financial literacy education. Fourth, we study treatment effects on attitudes towards financial topics. The assessment of treatment effects is accomplished through tests prior to, directly following, and about six months after the intervention, thereby capturing both immediate and longer-term learning outcomes.

OECD (2020), PISA 2018 Results (Volume IV): Are Students Smart about Money?, PISA, OECD Publishing, Paris, https://www.oecd.org/en/publications/pisa-2018-results-volume-iv_48ebd1ba-en.html.

Sutter, M., Weyland, M., Untertrifaller, A., Froitzheim, M., & Schneider, S. O. (2023). Financial literacy, experimental preference measures and field behavior: A randomized educational intervention (ECONtribute Discussion Paper No. 229/2023). ECONtribute.
External Link(s)

Registration Citation

Citation
Dreisbach, Jacqueline et al. 2026. "The impact of financial education on financial literacy, economic preferences and heuristics and biases in decision-making – an intervention study in schools." AEA RCT Registry. February 10. https://doi.org/10.1257/rct.17854-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The study will be run in schools. Online learning interventions will be conducted using two different approaches. The interventions require about eight school lessons and will take place during regular school hours. Additionally, a third class in each school will serve as a control group and receive no intervention (but will have regular class lectures).
Intervention Start Date
2026-02-23
Intervention End Date
2027-07-30

Primary Outcomes

Primary Outcomes (end points)
Financial literacy (FL), assessed by the number of correct answers in a financial literacy test, measured before the intervention, directly after, and about six months post-intervention.
Risk and time preferences, measured by the number of riskless and patient choices made by students, assessed before the intervention, directly after, and about six months post-intervention.
Decision-making behavior (related to financial topics), evaluated with tasks that measure heuristics and biases in decision making before the intervention, directly after, and about six months post-intervention.

It is hypothesized that students in both treatment groups (treatment 1 and treatment 2) will show greater improvements in the measured outcomes (better financial literacy, more risk aversion and patience; less biases in decision making) in the post-intervention tests compared to the control group.
It is hypothesized that students in treatment 1 will show stronger improvements in the measured outcomes than students in treatment 2.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Students will be assessed at three time points: before the intervention, directly after, and about six months after the intervention.
Experimental Design Details
Not available
Randomization Method
Classes will be randomly allocated to treatment arms using an independent randomization procedure.
Randomization Unit
Class level, cluster randomized trial
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
A total of approximately 45 to 60 clusters (classes)
Sample size: planned number of observations
We will run the study with approx. 1.200 students
Sample size (or number of clusters) by treatment arms
Approximately 15–20 classes per arm (control, treatment A, treatment B).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Committee of the Ludwigsburg University of Education
IRB Approval Date
2025-11-12
IRB Approval Number
Ethikantrag_I-Öko-NoVe-0055
Analysis Plan