Behavioural Interventions to Increase Parental Engagament

Last registered on May 25, 2014

Pre-Trial

Trial Information

General Information

Title
Behavioural Interventions to Increase Parental Engagament
RCT ID
AEARCTR-0000349
First published
May 25, 2014, 7:25 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 Bristol

Other Primary Investigator(s)

PI Affiliation
Harvard University

Additional Trial Information

Status
On going
Start date
2014-02-01
End date
2014-07-31
Secondary IDs
Abstract
These trials aim to prompt parents to become more involved in their child’s education. Parents will be texted additional information regarding their child’s school life, and the impact of these text messages on attainment, attendance and attitudes towards school will then be evaluated.

Registration Citation

Citation
Chande, Raj and Todd Rogers. 2014. "Behavioural Interventions to Increase Parental Engagament." AEA RCT Registry. May 25. https://doi.org/10.1257/rct.349-1.0
Former Citation
Chande, Raj and Todd Rogers. 2014. "Behavioural Interventions to Increase Parental Engagament." AEA RCT Registry. May 25. https://www.socialscienceregistry.org/trials/349/history/1837
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Trial 1. Parents will be texted in advanced of their child's Maths test.
Trial 2. Parents will be texted a conversational prompt related to the day's Science class.
Trial 3. Parents will be texted a report of their child's attendance (academic year to date), compared to the rest of their child's year.
Intervention Start Date
2014-04-24
Intervention End Date
2014-07-31

Primary Outcomes

Primary Outcomes (end points)
Trial 1. Maths test results (z-standardized within class) and maths test grade (z-standardized within year)
Trial 2. Science test results (z-standardized within class) and science test grade (z-standardized within year)
Trial 3. Attendance for the first and second halves of the Summer Term in the 2013/14 school year.
Primary Outcomes (explanation)
For trials 1 and 2, grades will be converted into within year z-scores.
For trial 3, the number of days missed will be calculated by multiplying the percentage of days missed (which is how schools conventionally store attendance data) by the number of school days in the relevant period.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Trial 1

Students are individually randomised to treatment/control groups. 5 schools make up the sample. Block randomisation ensuring balance across treatment control groups for: school, year group, class, prior attainment, free school meal status. Parents are texted 5 days, 3 days, 1 day in advance of a maths test. Students are surveyed for feedback after the test. Test grades are then compared for differences in within year z scores.

Trial 2

Students are individually randomised to treatment/control groups. 5 schools make up the sample. Block randomisation ensuring balance across treatment control groups for: school, year group, class, prior attainment, free school meal status. For 4 to 6 weeks, parents are conversational prompts related to the day's science class. Students are surveyed for feedback after their end of term test. Test grades are then compared for differences in within year z scores.

Trial 3

Students are individually randomised to treatment A/treatment B/control groups. 10 schools make up the sample. Block randomisation ensuring balance across treatment control groups for: school, year group, prior attendance. Treatment A parents are texted number of days missed by student in previous two terms. Treatment B texted Treatment A + comparison to typical (modal) student in that school/year. Attendance across two half-term blocks of the Summer term compared at the end of the academic year.
Experimental Design Details
Trial 1

Outcome Variables

Maths test result (within class z-score), Maths test Grade/Attainment level (within year z-score), attitudes towards parent engagement and maths in general (survey responses). Note that 3 different surveys were conducted, (see appendix B).

Outcome Variables: Issues

- All schools do not keep a record of test results once they have been standardized into attainment levels (which are not as granular as test scores). Therefore there is risk that small effects will be missed if looking at attainment levels only.
- Survey data is stated rather than revealed preference.

Sample

5 secondary schools, year groups 7 to 11 inclusive. Students were removed from the study if their parents refused permission to participate or if the school had no working mobile phone number for any parent.

Randomisation

Randomisation was done at the student level to maximize power and because although some contamination was likely, the intervention only ran for 5 days and hence was unlikely to completely undermine the randomization. Block randomization was used, so students were sorted by class, free school meal status and prior attainment, then randomized within those blocks. This was done to ensure the treatment and control groups would be balanced on observables. The Stata randomization algorithm has been kept by RC.

Data

Outcomes data provided by school. Covariates data gathered from the school and found in the National Pupil Database (NPD). Survey data administered and entered by RAs.

Trial 2

Outcome Variables

Science test results (within class z-score), attainment level (within year z-score), attitudes towards parent engagement and science in general (surveys). Note that 2 different surveys were conducted, see appendices.

Outcome Variables: Issues

Not clear that all schools keep a record of test results once they have been standardized into attainment levels, which are not as granular as test scores. Risk that small effects will be missed if looking at attainment levels only.

Sample

5 secondary schools, year groups 7 to 11 inclusive. BTEC students were dropped from the study, as were Separate Science students in one school because scheduling the texts according to the timetable became too complicated due to extent to which students sat in different classes on different days. Students were removed from the study if their parents refused permission to participate or if the school had no working mobile phone number for any parent.

Randomisation

Randomisation was done at the student level to maximize power and because although some contamination was likely, the intervention only ran for 6 weeks and hence was unlikely to completely undermine the randomization. Clearly, the risk of contamination was higher than in Experiment 1. Block randomization was used, so students were sorted by class, free school meal status and prior attainment, then randomized within those blocks. This was done to ensure the treatment and control groups would be balanced on observables. The Stata randomization algorithm has been kept by RC.

Data

Outcomes data provided by school. Covariates data gathered from school and National Pupil Database (NPD). Survey data administered and entered by RAs.

Trial 3

Outcome Variables

Attendance rate in first and second half of summer term.

Outcome Variables: Issues

Sample

10 secondary schools, year groups 7 to 10 inclusive. Students were only included if they had missed 4 days or more than the modal number of days missed in their year group. Students were removed from the study if their parents refused permission to participate or if the school had no working mobile phone number for any parent. Students were also withdrawn if schools felt they had been absent because of extenuating circumstances (such as serious health problems or family distress). ‘Extenuating circumstances’ was left to the school’s discretion.

Randomisation

Randomisation was done at the student level to maximize power and because although some contamination was likely, the intervention was composed of only 1 text message and hence was unlikely to completely undermine the randomization. Block randomization was used, so students were sorted by year group and prior attendance records, then randomized within those blocks. This was done to ensure the treatment and control groups would be balanced on observables. The Stata randomization algorithm has been kept by RC.

Data

Outcomes data provided by school. Covariates data gathered from school and National Pupil Database (NPD). Survey data administered and entered by RAs.
Randomization Method
Randomisation done using Stata. Raj Chande holds randomisation code used. Individual randomisation, blocking by covariates.
Randomization Unit
Student level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Trial 1: 5 schools
Trial 2: 5 schools
Trial 3: 10 shools
Sample size: planned number of observations
Trial 1: 5000. Trial 2: 5000 Trial 3: 5000
Sample size (or number of clusters) by treatment arms
Trial 1: 50/50 split
Trial 2: 50/50 split
Trial 3: 33/33/33 split
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Bristol
IRB Approval Date
2014-01-14
IRB Approval Number
3881
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials