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All issues Volume 75 (2020) SHS Web Conf., 75 (2020) 04014 References
Open Access
Issue
SHS Web Conf.
Volume 75, 2020
The International Conference on History, Theory and Methodology of Learning (ICHTML 2020)
Article Number 04014
Number of page(s) 6
Section Methodology of Learning, Education and Training
DOI https://doi.org/10.1051/shsconf/20207504014
Published online 26 March 2020
  1. A. Schleicher, World Class: How to build a 21st- century school system, Strong Performers and Successful (OECD Publishing, Paris, 2018). doi: 10.1787/4789264300002-en [Google Scholar]
  2. STEAM-osvita: innovatsiina naukovo-tekhnichna systema navchannia (STEAM education: an innovative science and technology education system) (2016), http://ippo.kubg.edu.ua/content/11373. Accessed 14 Jan 2020 [Google Scholar]
  3. Introductory Campaign 2019, https://vstup.edbo.gov.ua/statistics/konkurs. Accessed 14 Jan 2020 [Google Scholar]
  4. X. Chen, Students Who study science, technology, engineering, and mathematics (STEM) in postsecondary education. Stats in Brief. NCES 2009-161. National Center for Education Statistics (2009) [Google Scholar]
  5. J.E. Jon, H.I. Chung, STEM Report: Republic Of Korea. Report For The Australian Council Of Learned Academies (ACOLA). (Australian Council of Learned Academies, Melbourne, 2013), p. 55. [Google Scholar]
  6. C.M. Phelps-Gregory, M. Frank, S.M. Spitzer, Prospective elementary teachers’ beliefs about mathematical myths: a historical and qualitative examination. The Teacher Educator 55, 1 (2019). doi: 10.1080/08878730.2019.1618423 [Google Scholar]
  7. C.S. Dweck, Motivational processes affecting learning. American psychologist 41 (10),1040–1048 (1986). doi:10.1037/0003-066X.41.10.1040 [Google Scholar]
  8. L.S. Blackwell, K.H. Trzesniewski, C.S. Dweck, Implicit theories of intelligence predict achievement across an adolescent transition: a longitudinal study and an intervention. Child development ‘ (1),246¬263 (2007). doi: 10.1111/j. 1467-8624.2007.00995.x [Google Scholar]
  9. D. Bressoud, M. Carlson, V. Mesa, C. Rasmussen, The calculus student: Insights from the MAA National Study. International Journal of Mathematical Education in Science and Technology 44(5) (2013) [Google Scholar]
  10. E. Seymour, Tracking the processes of change in US undergraduate education in science, mathematics, engineering, and technology. Science Education 86(1),79–10 (2001). doi: 10.1002/sce. 1044 [Google Scholar]
  11. D.H. Schunk, F. Pajares, Competence perceptions and academic functioning. Handbook of competence and motivation 85 (2005) [Google Scholar]
  12. J. Wai, D. Lubinski, C.P. Benbow, Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance. Journal of Educational Psychology 101(4) (2009). doi:10.1037/a0016127 [Google Scholar]
  13. M. Honey, G. Pearson, H.A. Schweingruber (eds.) STEM integration in K-12 education: Status, prospects, and an agenda for research. (Washington, National Academies Press, 2014) [Google Scholar]
  14. International Society for Technology in Education, https://www.iste.org/standards. Accessed 14 Jan 2020 [Google Scholar]
  15. V.V. Osadchyi, N.V. Valko, N.A. Kushnir, Determining the Level of Readiness of Teachers to Implementation of STEM-Education in Ukraine. CEUR Workshop Proceedings 2393, 144–155 (2019), http://ceur-ws.org/Vol-2393/paper_369.pdf. Accessed 14 Jan 2020 [Google Scholar]
  16. A. Spivakovskiy, N. Kushnir, N. Valko, M. Vinnyk, ICT advanced training of university teachers. CEUR Workshop Proceedings 1844, 176–190 (2017), http://ceur-ws.org/Vol-1844/10000176.pdf. Accessed 14 Jan 2020 [Google Scholar]
  17. Decree of the Cabinet of Ministers of Ukraine No. 266 of April 29, 2015 “On approving the list of branches of knowledge and specialties by which higher education applicants are trained” (2015), https://zakon2.rada.gov.ua/laws/show/266-2015- %D0%BF. Accessed 14 Jan 2020 [Google Scholar]
  18. R. Cagao. Motivational Gaps and Perceptual Bias of Initial Motivation Additional Indicators of Quality for e-Learning Courses. Electronic Journal of e¬Learning 15(1),3–16 (2017) [Google Scholar]
  19. M.M. Vrublevskaya, O.V. Zykova, Proforiyenta- tsionnaya rabota v shkole: Metodicheskiye rekomendatsii (Magnitogorsk, Moscow State University, 2004), p. 80 [Google Scholar]
  20. A.A. Rean, A.R. Kudashev, A.A. Baranov Psikhologiya adaptatsii lichnosti (Prime-Eurosign, SPb, 2006), p. 479 [Google Scholar]

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