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Field
Primary Outcomes (Explanation)
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Before
(1) Likelihood of studying economics on higher education will be asked directly to students on a scale from 0 to 100. Students will also be asked about the likelihood of studying their best or second best subject (i.e besides economics) on higher education.
(2) Economic literacy is based on questions that measure students’ proficiency on the topics they learned during the course. This survey was developed together with teachers that helped to create the course materials.
(3) Self-efficacy will be measured with scales based on May (2009); Kundu (2016); and Lent et al. (2016) adapted for the decision of students to study economics.
(4) Outcome expectation on study and job outcomes was based on the scale from Betz & Voyten (1997).
(5) Economic stereotypes will be measured by a Linkert-scale on how much students associate common stereotypes with economists.
(6) Social image will be measured by a Linkert-scale based on how positively/negatively students’ social circle would evaluate their decision to study economics and on how positively or negatively they evaluate economic stereotypes to be.
(7) Political views will be estimated by a two-dimensional scale based on Evans et al. (1996), which measures left-right and libertarian-authoritarian values.
Besides the tests of the main outcome variables, pre-existing conditions of students (e.g. grades in math and language, situation of family, previous interest in economics, socioeconomic status) and school (e.g. private/public, region, performance in past standardized tests, funding by student) will also be collected.
References:
Betz, N. E., & Voyten, K. K. (1997). Efficacy and outcome expectations influence career exploration and decidedness. The Career Development Quarterly, 46(2), 179-189.
Evans, G., Heath, A., & Lalljee, M. (1996). Measuring left-right and libertarian-authoritarian values in the British electorate. British Journal of Sociology, 93-112.
Kundu, A., & Ghose, A. (2016). The relationship between attitude and self-efficacy in mathematics among higher secondary students. Journal of Humanities and Social Science, 21(4), 25-31.
Lent, R. W., Ezeofor, I., Morrison, M. A., Penn, L. T., & Ireland, G. W. (2016). Applying the social cognitive model of career self-management to career exploration and decision-making. Journal of Vocational Behavior, 93, 47-57.
May, D. K. (2009). Mathematics self-efficacy and anxiety questionnaire (Doctoral dissertation, University of Georgia).
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After
(1) Likelihood of studying economics on higher education will be asked directly to students on a scale from 0 to 100. Students will also be asked about the likelihood of studying their best or second best subject (i.e besides economics) on higher education.
(2) Economic literacy is based on questions that measure students’ proficiency on the topics they learned during the course. This survey was developed together with teachers that helped to create the course materials.
(3) Self-efficacy will be measured with scales based on May (2009); Kundu (2016); and Lent et al. (2016) adapted for the decision of students to study economics.
(4) Outcome expectation on study and job outcomes was based on the scale from Betz & Voyten (1997).
(5) Economic stereotypes will be measured by a Linkert-scale on how much students associate common stereotypes with economists.
(6) Social image will be measured by a Linkert-scale based on how positively/negatively students’ social circle would evaluate their decision to study economics and on how positively or negatively they evaluate economic stereotypes to be.
(7) Political views will be estimated by a two-dimensional scale based on Evans et al. (1996), which measures left-right and libertarian-authoritarian values.
Besides the tests of the main outcome variables, pre-existing conditions of students (e.g. grades in math and language, situation of family, previous interest in economics, socioeconomic status) and school (e.g. private/public, region, performance in past standardized tests, funding by student) will also be collected.
Our main hypothesis is that the first intervention (i.e. sample course on what students will learn in higher education economics) will improve economic literacy, self-efficacy and outcome expectation. Those variables will then serve as mediating variables, which we expect to increase the likelihood of someone studying economics in higher education. For students that find the course too hard or uninteresting, this effect might be zero or negative. For the second intervention (i.e. videos, images, infographics and testimonies about non-standard jobs in economics), our hypothesis is that this will reduce the amount of negative stereotypes towards studying economics, which can influence the subjective social image of studying economics. Both social image and stereotypes can also serve as mediating variables to increase the likelihood of studying economics.
Moreover, as secondary outcome, we would like to analyse heterogeneous treatment effects. More specifically, the treatment effect depending on (i) political views (i.e. we believe that the second intervention might have a higher effect size to left-leaning students); (ii) gender (considering differences in competitiveness, as seen in Buser et al. (2014), we expect the first intervention to have a higher effect size to girls); and (iii) socio-economic status (our hypothesis is that low socio-economic status students might receive a higher impact from both interventions, than students in more favourable environments).
References:
Betz, N. E., & Voyten, K. K. (1997). Efficacy and outcome expectations influence career exploration and decidedness. The Career Development Quarterly, 46(2), 179-189.
Buser, T., Niederle, M., & Oosterbeek, H. (2014). Gender, competitiveness, and career choices. The quarterly journal of economics, 129(3), 1409-1447.
Evans, G., Heath, A., & Lalljee, M. (1996). Measuring left-right and libertarian-authoritarian values in the British electorate. British Journal of Sociology, 93-112.
Kundu, A., & Ghose, A. (2016). The relationship between attitude and self-efficacy in mathematics among higher secondary students. Journal of Humanities and Social Science, 21(4), 25-31.
Lent, R. W., Ezeofor, I., Morrison, M. A., Penn, L. T., & Ireland, G. W. (2016). Applying the social cognitive model of career self-management to career exploration and decision-making. Journal of Vocational Behavior, 93, 47-57.
May, D. K. (2009). Mathematics self-efficacy and anxiety questionnaire (Doctoral dissertation, University of Georgia).
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