The Effectiveness of Parental Tutoring Compared to Teaching at School

Last registered on May 20, 2022

Pre-Trial

Trial Information

General Information

Title
The Effectiveness of Parental Tutoring Compared to Teaching at School
RCT ID
AEARCTR-0004707
Initial registration date
September 13, 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 16, 2019, 2:01 PM EDT

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

Last updated
May 20, 2022, 5:52 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
KU Leuven

Other Primary Investigator(s)

PI Affiliation
KU Leuven, UNU-MERIT Maastricht University
PI Affiliation
IRES, UCLouvain and FNRS

Additional Trial Information

Status
Completed
Start date
2019-09-15
End date
2021-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This intervention seeks to measure the effects of parental tutoring at home compared to traditional teaching in the class at school. The experiment will evaluate the effects of an intervention in economics education in grade 9 and 10 of Flemish secondary schools in Belgium. The study will measure knowledge, attitudes and behaviour of students, parents and teachers. In particular, it will assess economic and political knowledge, financial literacy, political preferences on economic issues, trust in institutions as well as family communication. Randomisation will be done at school level. The expected sample size is 60 schools with 2,400 participating students.
External Link(s)

Registration Citation

Citation
Maldonado, Joana Elisa, Kristof De Witte and Koen Declercq. 2022. "The Effectiveness of Parental Tutoring Compared to Teaching at School." AEA RCT Registry. May 20. https://doi.org/10.1257/rct.4707
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Experimental Details

Interventions

Intervention(s)
Participating schools will be randomly assigned to the following three experimental conditions:
Control group: Students do not receive any treatment.
Treatment group 1: Students follow three class periods of a digital learning path about the role of the government on the labour market in class and one class period with an interactive discussion game in class.
Treatment group 2: Students follow three class periods of a digital learning path about the role of the government on the labour market in class and receive a homework assignment that has to be completed with a parent and includes an interactive discussion game.
Intervention Start Date
2019-10-07
Intervention End Date
2019-11-30

Primary Outcomes

Primary Outcomes (end points)
We measure the knowledge acquired during the intervention in a post-test based on a set of 16 questions. Three of these questions will measure general financial literacy. Three questions will measure specific knowledge acquired during the interactive discussion game. The remaining questions will measure the knowledge on the specific topics of the digital learning path. In addition, the post-test measures attitudes concerning political preferences and trust in institutions. Finally, the post-test also enquires about family communication patterns.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
An open call for schools to participate was launched at the beginning of September 2019. Participating students are in grade 9 and 10, i.e. the third or fourth year of secondary education in Flanders and on average aged 15-16. Schools that register for participation will be randomised to the aforementioned three experimental conditions. Before and after the intervention, knowledge, attitudes and behaviour of students, parents and teachers will be assessed in online surveys. Students assigned to the control group will complete the same tests at the same time as students in the treatment groups, without receiving any intervention. Approximately four months after the intervention, students in the treatment groups will be given a second post-test to measure long-term effects.
Experimental Design Details
Before the intervention, all students (control group + treatment groups), teachers and parents will complete an online questionnaire to test their baseline knowledge, attitudes and behaviour. Participants also have to report several personal characteristics like gender, grades, and socio-economic background. After this baseline assessment, schools will be randomised in the three experimental groups. Teachers in the treatment groups will receive the course material and instructions for implementation after all questionnaires are completed. Teachers will then, approximately two weeks after the completion of the baseline surveys, implement the course about the role of the government on the labour market. The course material consists of a digital adaptive learning path where students work in teams of two, solving questions in order to complete a virtual ‘urban trail’ through a city. Information to solve the question is provided within the path in the form of information sheets with summaries of the key information by topic. Students will thus work independently with a minimum of teacher intervention. All course material was developed by high school teachers tailored to the age and the ability of the students. In addition, students in both treatment groups do an interactive discussion game. In treatment group 1, this game is played at school with the whole class and followed by a quiz which students complete individually. In treatment group 2, the same game is given as a homework which has to be completed with a parent. Students in treatment group 2 hence receive the same treatment, but play the game at home with a parent instead of at school with the teacher and their classmates. Students in treatment group 2 also complete a quiz after the game. In both treatment groups, parents and teachers fill in a questionnaire after the intervention. In the last class period with the digital learning path, students complete a post-test which measures knowledge, attitudes and behaviour after the intervention. At the same time, students in the control group will fill in this test without having received any intervention. Approximately four months after the intervention, students in the treatment groups will be given a second post-test to measure long-term effects.
Randomization Method
Schools will be randomly assigned to the three experimental conditions by a computer, using a random number generator in Stata.
Randomization Unit
Randomisation will be done at the school level. All students and teachers in the same school will be assigned to the same experimental condition. In this way, all teachers in the same school will receive the same instructions in order to minimize spill-over effects and contamination of the different treatment conditions.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
The treatment will be clustered at school-level. The expected number of clusters is 60.
Sample size: planned number of observations
The expected number of observations is 2,400 students.
Sample size (or number of clusters) by treatment arms
The expected 60 clusters will be randomly assigned to the three experimental conditions, i.e. approximately 20 schools in each condition.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The computation is based on List et al. (2011) and accounts for intracluster correlation in the calculation of the minimal detectable effect size. In our experimental setting, there are 20 schools expected in each experimental condition. Each school could have on average approximately 40 participating students. Based on previous experiments, the intracluster correlation in the final sample can be assumed to equal 0.1. This intracluster correlation can be reduced by controlling for characteristics of schools and students. Using the conventional power of 0.8 and a significance level of 0.05, the calculation results in a minimal detectable effect size of 0.31 standard deviations. Details of the calculation: According to List et al. (2011), in a clustered design, the minimum number of observations in each experimental group can be computed as follows: n=2(t_(α/2)+t_β)²(σ/δ)²(1+(m-1)ρ) This implies that the minimum detectable effect size is equal to: δ=σ/√(n/(2(t_(α/2)+t_β)²(1+(m-1)ρ))) Or the minimum detectable effect size expressed as a fraction of a standard deviation is equal to: δ/σ=1/√(n/(2(t_(α/2)+t_β)²(1+(m-1)ρ))) δ/σ=1/√(800/(2(1.96+0.84)²(1+(40-1)0.1)))=0.31 Reference List, J., Sadoff, S. and Wagner, M. (2011), So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design, Experimental Economics 14, 439-457.
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
November 30, 2019, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
February 29, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
62 schools
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1,434 students
Final Sample Size (or Number of Clusters) by Treatment Arms
524 students control, 430 students teacher-led instruction, 480 parent-led instruction
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials