Entrepreneurship in high-growth sectors and employment in sectors requiring training in science, technology, engineering, and math (STEM) offer an opportunity for high-paying careers, but most young people in low-income countries do not select these educational and career paths. In high school, students may not be aware of these career paths, they may lack the appropriate skills, and they may lack role models. This evaluation will test the impact of offering a 12-week online course offered in high school that includes content on personal initiative and negotiation skills, basic scientific methods, and role model interviews with entrepreneurs and scientists. Using data from an online monitoring system designed in tandem with the course, the evaluation will also test strategies for increasing course adoption among teachers, such as face-to-face versus online training, as well has different approaches for structuring how the material is presented, such as the order of content or adaptive exercises.
|Study title:||Showing Life Opportunities: Increasing opportunity-driven entrepreneurship and STEM careers through online courses in schools|
|Research question:||What kind of online course designs increase take-up among teachers and learning and engagement among students?|
|Policy problem:||Low take-up of entrepreneurship and STEM careers by youth due to lack of knowledge, skills and appropriate role models.|
Treatment Schools where students are offered the online animated courses on entrepreneurship-related soft skills, science courses, and role models
Control Schools where students are offered a placebo course which uses the computer time to offer online courses in English and Math.
Nimble Experiment 1
Treatment Schools with online training where teachers receive weekly benchmarking information on take-up and usage of online courses in other schools
Nimble Experiment 2
Treatment Classes that receive role model content in the beginning of the online course
Nimble Experiment 3
Treatment Students that receive adaptive-exercises which vary depending on initial performance and student interests.
|Data sources:||Data from online learning platform and survey data|
|Researchers:||David McKenzie, Igor Asanov, Diego d’ Andria, Mona Mensmann, Bruno Crepon, Guido Buenstorf, Tom Astebro|