Improving Student's Financial Proficiency by Differentiating Computer-Assisted Instruction and Feedback? Evidence from a Randomised Control Trial.

Last registered on September 23, 2019
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Pre-Trial

Trial Information

General Information

Title
Improving Student's Financial Proficiency by Differentiating Computer-Assisted Instruction and Feedback? Evidence from a Randomised Control Trial.
RCT ID
AEARCTR-0004431
Initial registration date
September 23, 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
September 23, 2019, 4:06 PM EDT

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

Locations

Country
Belgium
Region
Flanders

Primary Investigator

Name
Kaat Iterbeke
Affiliation
KU Leuven
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Koen Declercq
PI Affiliation
UCLouvain
PI Name
Wouter Schelfhout
PI Affiliation
UAntwerpen
PI Name
Kristof De Witte
PI Affiliation
KU Leuven

Additional Trial Information

Status
Completed
Start date
2018-08-15
End date
2019-01-31
Keywords
Education
Additional Keywords
Differentiated Instruction; Feedback; Financial Literacy; Randomised Control Trial
JEL code(s)
C93; I21;O16
Secondary IDs
Abstract
This study examines the impact of within-class differentiation on the learning outcomes of Flemish students in eighth and ninth grade. In particular, using a computer-based learning environment, we evaluate the impact of two differentiation practices on the effectiveness of a financial education programme. First, differentiating instructions to the particular needs of students is examined for which high-ability students follow a more challenging learning path and low-ability students a basic path with additional instructions. Second, we examine whether providing students with elaborated feedback on own performances improves their learning outcomes. In order to establish the results on the effects of both practices, we conducted a large-scale randomised control trial involving 32 schools and 1,177 students.
External Link(s)

Registration Citation

Citation
De Witte, Kristof et al. 2019. "Improving Student's Financial Proficiency by Differentiating Computer-Assisted Instruction and Feedback? Evidence from a Randomised Control Trial.." AEA RCT Registry. September 23. https://doi.org/10.1257/rct.4431-1.0
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Experimental Details

Interventions

Intervention(s)
In order to examine the impact of the within-class computer-assisted differentiation practices, i.e. differentiated instruction and feedback, we designed four conditions, i.e. one control condition and three experimental conditions.
- The control condition did not receive the financial education programme.
- In the first experimental condition, all students had to follow an intermediate-level learning path, regardless of their proficiency level. Elaborated feedback was given after all exercises.
- In the second experimental condition, students followed a differentiated learning path. The paths included simple verification feedback.
- In the third experimental condition, students followed a differentiated learning path and elaborated feedback was provided. This experimental condition contains the most extended form of differentiation. A comparison with the first experimental condition allows us to evaluate the impact of differentiating instruction. The value added of elaborated feedback is investigated via a comparison with the second experimental condition.
Intervention Start Date
2018-09-17
Intervention End Date
2019-01-31

Primary Outcomes

Primary Outcomes (end points)
We measure financial proficiency using a computer-aided multiple-choice test that contains questions covering both financial knowledge and financial behaviour.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The financial education programme was developed for students in eighth and ninth grade in Flemish secondary education. Schools were invited to participate in the financial education programme in an open call. Teachers were given the liberty to plan the lectures in October or in November. From the schools willing to participate in either wave, we randomly assigned them to the control condition or one of the experimental conditions. In order to guarantee a uniform implementation, we requested the teachers to give the lectures during the pre-specified periods, depending on the particular wave, and during regular class hours. In order to evaluate the programme, students had to take three financial literacy tests, i.e. a first test prior to the lectures to measure students’ baseline financial proficiency, a second test at the start of the last lecture to capture the short-term effectiveness of the programme, and third test administered as an homework approximately six weeks after the lectures for students in the experimental conditions to measure longer-term effects. Students in the control condition completed the pre- and first post-treatment test at the same time as students in the experimental conditions.
Experimental Design Details
Randomization Method
Stratified randomization was performed by a computer.
Randomization Unit
Randomization was done at the level of the school to avoid spillover effects and contamination of the treatment within the same school.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
46 schools signed up to participate in the financial education programme of which 32 schools entirely followed the protocol (students completed both the pre- and post-treatment financial literacy test).
Sample size: planned number of observations
1,177 students
Sample size (or number of clusters) by treatment arms
Control condition: 312 students, 9 schools
Experimental condition I: 159 students, 5 schools
Experimental condition II: 281 students, 8 schools
Experimental condition III: 425 students, 10 schools
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
January 31, 2019, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
January 31, 2019, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
32 schools
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1,177 students
Final Sample Size (or Number of Clusters) by Treatment Arms
Control condition: 312 students, 9 schools Experimental condition I: 159 students, 5 schools Experimental condition II: 281 students, 8 schools Experimental condition III: 425 students, 10 schools
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials