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Field
Secondary Outcomes (End Points)
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Before
• self-efficacy (primarily measured as “Self_efficacy_general”)
• math confidence (oc-Mathe)
• STEM confidence (jobability)
• Competitiveness (2 if comp_math + comp_german==1, 1 if only one of the variable ==1, 0 if both 0)
• stereotypical beliefs (1st measure explicit stereotypes (BELIEFS) – primary measure; 2nd measure less explicit: RANKING, secondary measure; 3rd measure explicit stereotypes (IAT) – least likely to be affected, but still observed)
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After
• self-efficacy (primarily measured as “Self_efficacy_general”)
• math confidence (oc-Mathe)
• STEM confidence (jobability)
• Competitiveness (2 if comp_math==1, 0 otherwise)
• stereotypical beliefs (1st measure explicit stereotypes (BELIEFS) – primary measure; 2nd measure less explicit: RANKING, secondary measure; 3rd measure explicit stereotypes (IAT) – least likely to be affected, but still observed)
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Field
Secondary Outcomes (Explanation)
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Before
• Self_efficacy_general= mean(self-efficacy5-7): Index based on 3 questions from Bettinger et al. (2018).
Self_efficacy 5&6: -2= “nein stimmt nicht”- 2 = “ja, stimmt“
Self-efficacy 7: -2= “ja,stimmt”- 2 = “nein, stimmt nicht“
Likert scales are aggregated across questions and divided by the number of questions.
• Math confidence: guess_math-performance (split in two variables):
Overest_math=guess_math-math_performance if guess_math>=math_performance
underest_math=-(guess_math-math_performance) if guess_math<=math_performance
• Stem confidence: measured using variable job ability:
-2 = nein gar nicht / 2 =ja sehr
Generate aggregated measure of relative belief in ability in MINT Jobs: sum job_ ability(ing+comp+math)/sum job_ability*
• stereotypical beliefs:
Beliefs: 3 questions on stereotypical beliefs who is more skilled in math and 3 questions on who is more skilled in German
Q1,Q3,Q5: “Burschen mehr” -2 –“Mädchen mehr” 2
Q2, Q4, Q6: “Mädchen mehr” -2 –“Burschen mehr” 2
Likert scales are aggregated across questions and divided by the number of questions.
Ranking: : (number of boys chosen for math ranking – number of boys in top 3) + (number of girls chosen in German ranking- number of girls in top 3)
IAT: : (number of boys chosen for math ranking – number of boys in top 3) + (number of girls chosen in German ranking- number of girls in top 3)
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After
• Self_efficacy_general= mean(self-efficacy5-7): Index based on 3 questions from Bettinger et al. (2018).
Self_efficacy 5&6: -2= “nein stimmt nicht”- 2 = “ja, stimmt“
Self-efficacy 7: -2= “ja,stimmt”- 2 = “nein, stimmt nicht“
Likert scales are aggregated across questions and divided by the number of questions.
• Math confidence: guess_math-performance (split in two variables):
Overest_math=guess_math-math_performance if guess_math>=math_performance
underest_math=-(guess_math-math_performance) if guess_math<=math_performance
• Stem confidence: measured using variable job ability:
-2 = nein gar nicht / 2 =ja sehr
Generate aggregated measure of relative belief in ability in MINT Jobs: sum job_ ability(ing+comp+math)/sum job_ability*
• stereotypical beliefs:
Beliefs: 3 questions on stereotypical beliefs who is more skilled in math and 3 questions on who is more skilled in German
Q1,Q3,Q5: “Burschen mehr” -2 –“Mädchen mehr” 2
Q2, Q4, Q6: “Mädchen mehr” -2 –“Burschen mehr” 2
Likert scales are aggregated across questions and divided by the number of questions.
Ranking: : (number of boys chosen for math ranking – number of boys in top 3)
IAT: Implicit association test, differences in decision time between congruent an incongruent word pairs
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