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Inquiry-based learning put to test: long-term effects of the Swedish science and technology for Children program

Author

Listed:
  • Mellander, Erik

    (IFAU - Institute for Evaluation of Labour Market and Education Policy)

  • Svärdh, Joakim

    (KTH, Education and Communication in Engineering Science, ECE)

Abstract

We quantitatively evaluate the effects in grade 9 on content and process skills in sciences, from participation in the Swedish science and technology for children program, the NTA program. Students predominantly participate in this program during grades 1-6. Our outcome measures are scores and grades on nationwide tests, and course grades, in biology, chemistry and physics, 2009-2010. A nationally representa¬tive random sample of almost 16 000 test-taking students is coupled with multi-level information about the NTA, and background factors. Non-random selection into the program is addressed by propensity score analysis. The matched sample of pairs of NTA participants and non-participants, determined by the propensity scores, is quite well behaved, although there are significant, but small, differences for some of the matching covariates. We find significantly positive effects on test scores (average increase 16.4%) and test grades in physics, but not in biology and chemistry. No significant effects are found for course grades.

Suggested Citation

  • Mellander, Erik & Svärdh, Joakim, 2015. "Inquiry-based learning put to test: long-term effects of the Swedish science and technology for Children program," Working Paper Series 2015:23, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2015_023
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    References listed on IDEAS

    as
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    2. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    quantitative evaluation; national standardized tests; representative sample; non-random selection; propensity score analysis; multi-level modeling; post-matching multivariate regression;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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