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Field
Primary Outcomes (Explanation)
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Before
1) How well informed: We ask in baseline and endline how well parents feel informed
2) Registered school track: We ask in an endline survey at which school type parents registered their child
3) Transition rates from elementary school to different school tracks: We use administrative data that has aggregated information which share of children transitioned from an elementary school to the different school types (also by gender and citizenship)
4) School event participation: We ask whether parents participated in informational events
5) School grades: We ask for students grades in math, German and Science
6) We will ask and rank importance of school characteristics
7) Predicted school track: We will use Machine learning to predict the registered school track based on characteristics
8 and 9) We will decompose the effect of different features in the treatment version of the app, namely language availability and local information
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After
1) How well informed: We ask in baseline and endline how well parents feel informed and which schools they know
2) Registered school track: We ask in an endline survey at which school type parents registered their child
3) Transition rates from elementary school to different school tracks: We use administrative data that has aggregated information which share of children transitioned from an elementary school to the different school types (also by gender and citizenship)
4) School event participation: We ask whether parents participated in informational events
5) School grades: We ask for students grades in math, German and Science
6) We will ask for importance of school characteristics
7) Predicted school track: We will use Machine learning to predict the registered school track based on characteristics
8 and 9) We will decompose the effect of different features in the treatment version of the app, namely language availability and local information
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