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Articles

How informal science learning experience influences students’ science performance: a cross-cultural study based on PISA 2015

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Pages 598-616 | Received 14 Oct 2019, Accepted 17 Jan 2020, Published online: 06 Feb 2020

References

  • Alexander, J. M., Johnson, K. E., & Kelley, K. (2012). Longitudinal analysis of the relations between opportunities to learn about science and the development of interests related to science. Science Education, 96(5), 763–786.
  • Bakoban, R. A., & Aljarallah, S. A. (2015). Extracurricular activities and their effect on the student's grade point average: Statistical study. Educational Research & Reviews, 10(20), 2737–2744.
  • Bamberger, Y., & Tal, T. (2007). Learning in a personal context: Levels of choice in a free choice learning environment in science and natural history museums. Science Education, 91(1), 75–95.
  • Bandura, A. (1994). Self-efficacy. In R. J. Corsini (Ed.), Encyclopedia of psychology ( 2nd ed., Vol.3, pp. 368–369). New York, NY: Wiley.
  • Barry, C. T., Cwikla, J., & Zeigler-Hill, V. (2010). Project WetKids: Findings and plans for an out-of-school program that improves student interest in science. Paper presented at the 2010 annual meeting of American Educational Research Association. Retrieved from the AERA Online Paper Repository.
  • Bell, P., Lewenstein, B., Shouse, A. W., & Feder, A. W. (2009). Learning science in informal environments: People, places, and pursuits. Washington, DC: The National Academies Press.
  • BIS. (2015). 2010-2015 government policy: public understanding of science and engineering. Retrieved from https://www.gov.uk/government/publications/2010-to-2015-government-policy-public-understanding-of-science-and-engineering/2010-to-2015-government-policy-public-understanding-of-science-and-engineering
  • Cheung, A. C. K., Yuen, T. W. W., Yuen, C. Y. M., & Cheng, Y. C. (2011). Strategies and policies for Hong Kong's higher education in Asian markets: Lessons from the United Kingdom. Australia, and Singapore. International Journal of Educational Management, 25(2), 144–163.
  • Cho, S.-K. (2012). An experience of science communication in Korea: The space-sharing project with mass media. In B. Schiele, M. Claessens, & S. Shi (Eds.), Science communication in the world: Practices, theories and trends (pp. 169–182). New York, NY: Springer.
  • Croucher Foundation. (2019). The out-of-school STEM ecosystem in Hong Kong, third report 2017-2018.Retrieved from https://croucher.org.hk/wp-content/uploads/2019/08/CF_2019_0719.pdf
  • Denault, A. S., & Poulin, F. (2009). Intensity and breadth of participation in organized activities during the adolescent years: Multiple associations with youth outcomes. Journal of Youth and Adolescence, 38(9), 1199–1213.
  • DIUS. (2009). A vision for science and society. Retrieved from https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/36747/49-08-S_b.pdf
  • Eshach, H. (2007). Bridging in-school and out-of-school learning: Formal, non-formal, and informal education. Journal of Science Education and Technology, 16(2), 171–190.
  • Falk, J. H., & Dierking, L. D. (2000). Learning from museums: Visitor experiences and the making of meaning. Lanham: Altamira Press.
  • Falk, J. H., & Dierking, L. D. (2010). The 95 percent solution: School is not where most Americans learn most of their science. American Scientist, 98(6), 486–493.
  • Falk, J. H., Osborne, J., Dierking, L., Dawson, E., Wenger, M., & Wong, B. (2012). Analysing the UK science education community: The contribution of informal providers. London: Wellcome Trust.
  • Forestier, K., & Crossley, M. (2015). International education policy transfer-borrowing both ways: The Hong Kong and England experience. Compare: A Journal of Comparative and International Education, 45, 664–685.
  • Fortus, D., & Vedder-Weiss, D. (2014). Measuring students’ continuing motivation for science learning. Journal of Research in Science Teaching, 51(4), 497–522.
  • Fredricks, J. A., & Eccles, J. S. (2006). Extracurricular involvement and adolescent adjustment: Impact of duration, number of activities, and breadth of participation. Applied Developmental Science, 10(3), 132–146.
  • Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: Software of the mind (3rd ed.). New York: McGraw-Hilll.
  • Hofstein, A., & Rosenfeld, S. (1996). Bridging the gap between formal and informal science learning. Studies in Science Education, 28(1), 87–112.
  • Hong, Z. R., Lin, H. S., & Veach, M. C. (2008). Effects of an extracurricular science intervention on science performance, self-worth, social skills, and sexist attitudes of Taiwanese adolescents from single-parent families. Sex Roles, 59(7-8), 555–567.
  • Hopkins, E. J., & Weisberg, D. S. (2016). The youngest readers’ dilemma: A review of children’s learning from fictional sources. Developmental Review, 2016. doi: 10.1016/j.dr.2016.11.001
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.
  • Israel, M., Wang, S., & Marino, M. T. (2016). A multilevel analysis of diverse learners playing life science video games: Interactions between game content, learning disability status, reading proficiency, and gender. Journal of Research in Science Teaching, 53, 324–345.
  • Jarvis, T., & Pell, A. (2005). Factors influencing elementary school children's attitudes toward science before, during, and after a visit to the UK national space centre. Journal of Research in Science Teaching, 42(1), 53–83.
  • Köller, O., Baumert, J., & Schnabel, K. (2001). Does interest matter? The relationship between academic interest and achievement in mathematics. Journal of Research in Mathematics Education, 32, 448–470.
  • Krapp, A., & Prenzel, M. (2011). Research on interest in science: Theories, methods, and findings. International Journal of Science Education, 33(1), 27–50.
  • Lee, J. (2014). Universal factors of student achievement in high-performing Eastern and Western countries. Journal of Educational Psychology, 106(2), 364–374.
  • Lee, W., Lee, M. J., & Bong, M. (2014). Testing interest and self-efficacy as predictors of academic self-regulation and achievement. Contemporary Educational Psychology, 39(2), 86–99.
  • Markowitz, D. G. (2004). Evaluation of the long-term impact of a university high school summer science program on students—interest and perceived abilities in science. Journal of Science Education and Technology, 13(3), 395–407.
  • Marsh, H. W., & Martin, A. J. (2011). Academic self-concept and academic achievement: Relations and causal ordering. British Journal of Educational Psychology, 81(Pt1), 59–77.
  • Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2005). Academic self-concept, interest, grades, and standardized test scores: Reciprocal effects models of causal ordering. Child Development, 76(2), 397–416.
  • Masters, G. N. (1982). A rasch model for partial credit scoring. Psychometrika, 47(2), 149–174.
  • McGinnis, J. R., Hestness, E., Riedinger, K., Katz, P., Marbach-Ad, G., & Dai, A. (2012). Informal science education in formal science teacher preparation. In K. Tobin, B. J. Fraser, & C. McRobbie (Eds.), Second international handbook of science education Vol. 2 (pp. 1097–1108). Dordrecht, the Netherlands: Springer.
  • Miller, J. D. (2010). Adult science learning in the Internet era. Curator: The Museum Journal, 53(2), 191–208.
  • Morentin, M., & Guisasola, J. (2015). Primary and secondary teachers’ ideas on school visits to science centres in the Basque country. International Journal of Science and Mathematics Education, 13(1), 191–214.
  • Motlagh, S. E., Amrai, K., Yazdani, M. J., Abderahim, H., & Souri, H. (2011). The relationship between self-efficacy and academic achievement in high school students. Procedia-Social and Behavioral Sciences, 15, 765–768.
  • Muthén, L. K., & Muthén, B. O. (2012). Mplus user's guide (7th ed.). Los Angeles, CA: Muthen and Muthen.
  • Nagengast, B., Marsh, H. W., Scalas, L. F., Xu, M. K., Hau, K. T., & Trautwein, U. (2011). Who took the ‘x’ out of expectancy-value theory? A psychological mystery, a substantive-methodological synergy, and a cross-national generalization. Psychological Science, 22(8), 1058–1066.
  • Newell, A. D., Tharp, B. Z., Vogt, G. L., Moreno, N. P., & Zientek, L. R. (2015). Students’ attitudes toward science as predictors of gains on student content knowledge: Benefits of an after-school program. School Science & Mathematics, 115(5), 216–225.
  • OECD. (2007). PISA 2006: Science Competencies for tomorrow's world, Volume1. Paris: OECD Publishing. Retrieved from http://www.oecd-ilibrary.org/education/pisa-2006_9789264040014-en;jsessionid=2cpmwkh08hdjv.x-oecd-live-02
  • OECD. (2011). Quality time for students: Learning in and out of school. Paris: OECD Publishing. Retrieved from http://www.oecd.org/edu/school/programmeforinternationalstudentassessmentpisa/pisa-qualitytimeforstudentslearninginandoutofschool.htm
  • OECD. (2016). PISA 2015 results: Excellence and equity in education. Retrieved from http://www.oecd.org/education/pisa-2015-results-volume-i-9789264266490-en.htm
  • OECD. (2017). PISA 2015 Technical report. Retrieved from http://www.oecd.org/pisa/data/2015-technical-report/
  • Potvin, P., & Hasni, A. (2014). Analysis of the decline in interest towards school science and technology from grades 5 through 11. Journal of Science Education & Technology, 23(6), 784–802.
  • Raudenbush, S. W., Bryk, A. S., & Congdon, R. (2004). HLM 6 for Windows [computer software]. Lincolnwood, IL: Scientific Software International.
  • Rennie, L. J. (2007). Learning science outside of school. In S. K. Abell, & N. G. Lederman (Eds.), Handbook of research on science education (pp. 125–167). Mahwah, NJ: Lawrence Erlbaum.
  • Rennie, L. J. (2014). Learning science outside of school. In N. G. Lederman, & S. K. Abell (Eds.), Handbook of research on science education, Vol. 2 (pp. 120–144). New York: Taylor & Francis.
  • Salmi, H., Kaasinen, A., & Suomela, L. (2016). Teacher professional development in outdoor and open learning environments: A research based model. Creative Education, 07(10), 1392–1403.
  • Sandifer, C. (1997). Time-based behaviors at an interactive science museums: Exploring the differences between weekday/weekend and family/non-family visitors. Science Education, 81, 689–701.
  • Schiele, B., Claessens, M., & Shi, S. (2012). Science communication in the world: Practices, theories and trends. New York, NY: Springer.
  • Schunk, D. H., Meece, J. R., Pintrich, P. R., & Education, P. (2008). Motivation in education: Theory, research, and applications: International edition. IEEE Journal of Quantum Electronics, 15(9), 1009–1010.
  • Sellar, S., & Lingard, B. (2013). Looking East: Shanghai, PISA 2009 and the reconstitution of reference societies in the global education policy field. Comparative Education, 49(4), 464–485.
  • Sha, L., Schunn, C., & Bathgate, M. (2015). Measuring choice to participate in optional science learning experiences during early adolescence. Journal of Research in Science Teaching, 52(5), 686–709.
  • Sha, L., Schunn, C. D., Bathgate, M., & Beneliyahu, A. (2016). Families support their children's success in science learning by influencing interest and self- efficacy. Journal of Research in Science Teaching, 53(3), 450–472.
  • Stocklmayer, S. M., Rennie, L. J., & Gilbert, J. K. (2010). The roles of the formal and informal sectors in the provision of effective science education. Studies in Science Education, 46(1), 1–44.
  • Suter, L. E. (2014). Visiting science museums during middle and high school: A longitudinal analysis of student performance in science. Science Education, 98(5), 815–839.
  • Whitesell, E. R. (2016). A day at the museum: The impact of field trips on middle school science achievement. Journal of Research in Science Teaching, 53(7), 1036–1054.
  • Wilson, D., Jones, D., Kim, M. J., Allendoerfer, C., Bates, R., Crawford, J., … Veileux, N. (2014). The link between cocurricular activities and academic engagement in engineering education. Journal of Engineering Education, 103(4), 625–651.
  • Wright, J. C., Anderson, D. R., Huston, A. C., Collins, P. A., Schmitt, K. L., & Linebarger, D. L. (2001). The effect of early childhood TV-viewing on learning. In J. H. Falk (Ed.), Free-choice science education (pp. 79–92). New York: Teachers College Press.
  • Xu, Z., & Jang, E. E. (2017). The role of math self-efficacy in the structural model of extracurricular technology-related activities and junior elementary school students’ mathematics ability. Computers in Human Behavior, 68, 547–555.
  • Zhang, D., & Tang, X. (2017). The influence of extracurricular activities on middle school students’ science learning in China. International Journal of Science Education, 39(1), 1–19.

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