Abstrakt
Ve dvou předkládaných kvantitativních studiích jsme zkoumali vliv procvičování učiva matematiky pomocí interaktivní sbírky úloh Khan Academy na znalosti a dovednosti žáků čtyřletého gymnázia. V první studii z roku 2016/17 jsme se zaměřili na přenos naučených procedurálních znalostí a dovedností z anglického prostředí Khan Academy do českého školního kontextu. Ve druhé studii z roku 2017/18 jsme se věnovali otázce rozvoje konceptuálních znalostí skrze procvičování procedurálních dovedností. Obě studie probíhaly na stejném vzorku 44 žáků ze dvou tříd pražského gymnázia. Data jsme analyzovali pomocí testování hypotéz s hladinou spolehlivosti 5 %. Autor studií byl v době výzkumu učitelem matematiky těchto žáků. Zatímco v první studii byl přínos procvičování statisticky významný, ve druhé studii nebyl rozvoj konceptuálních znalostí žáků tak jednoznačný. Sekundárně jsme se věnovali žákovskému vnímání vlivu Khan Academy na jejich znalosti a dovednosti.
Reference
Alcock, L., Ansari, D., Batchelor, S., Bisson, M., Smedt, B. D., Gilmore, C., . . . Weber, K. (2016). Challenges in mathematical cognition: A collaboratively-derived research agenda. Journal of Numerical Cognition, 2(1), 20-41. doi:10.5964/jnc.v2i1.10
Anderson, L. W. & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. New York: Longman.
Attali, Y. (2015). Effects of multiple-try feedback and question type during mathematics problem solving on performance in similar problems. Computers & Education, 86, pp.260–267. doi: 10.1016/j.compedu.2015.08.011
Bempechat, J., Li, J., Neier, S. M., Gillis, C. A. & Holloway S. D. (2011). The homework experience: Perceptions of low-income youth. Journal of Advanced Academics, 22(2), 250-278. doi: 10.1177/1932202X1102200204
Berthold, K. & Renkl, A. (2009). Instructional aids to support a conceptual understanding of multiple representations. Journal of Educational Psychology, 101(1), 70–87. doi: 10.1037/a0013247
Bloom, B. S. (1956). Taxonomy of educational objectives: The classification of educational goals. New York: Longmans, Green. doi: 10.1177/001316445601600310
Bokhove, C. & Drijvers, P. (2012). Effects of a digital intervention on the development of algebraic expertise. Computers & Education, 58(1), 197–208. doi: 10.1016/j.compedu.2011.08.010
Brunström, M. & Fahlgren, M. (2015). Designing prediction tasks in a mathematics software environment. International Journal for Technology in Mathematics Education, 22(1), 3–18.
Cambridge Assessment, United Kingdom, 2019. https://www.cambridgeenglish.org/exams-and-tests/
Clarina, R. & Koul, R. (2003). Multiple-try feedback and higher-order learning outcomes. International Journal of Instructional Media, 32(3), 239–245.
Crompton, H., Burke, D., & Lin, Y. C. (2019). Mobile learning and student cognition: A systematic review of PK‐12 research using Bloom’s Taxonomy. British Journal of Educational Technology, 50(2), 684-701. doi: 10.1111/bjet.12674
Desmos, získáno 8. 5. 2019 z https://teacher.desmos.com
Dettmers, S., Trautwein, U., Lüdtke, O., Kunter, M. & Baumert, J. (2010). Homework Works if Homework Quality Is High: Using Multilevel Modeling to Predict the Development of Achievement in Mathematics. Journal of Educational Psychology, 102, 467–482. doi: 10.1037/a0018453
Dixon, J. A., Deets, J. K. & Bangert, A. (2001). The representations of the arithmetic operations include functional relationships. Memory and Cognition, 29(3), 462–477
Fan, H., Xu, J., Cai, Z., He, J. & Fan, X. (2017). Homework and students' achievement in math and science: A 30-year meta-analysis, 1986–2015. Educational Research Review, 20, 35–54. doi: 10.1016/j.edurev.2016.11.003
Hecht, S. A., & Vagi, K. J. (2010). Sources of group and individual differences in emerging fraction skills. Journal of Educational Psychology, 102(4), 843–859. doi: 10.1037/a0019824
Jupri, A., Drijvers, P. and van den Heuvel-Panhuizen, M. (2016). An instrumentation theory view on students’ use of an applet for algebraic substitution. International Journal for Technology in Mathematics Education, 23(2), 63–80.
Kamii, C., & Dominick, A. (1997). To teach or not to teach algorithms. The Journal of Mathematical Behavior, 16(1), 51–61. doi: 10.1016/S0732-3123(97)90007-9
Khan Academy, získáno 7. 12. 2018 z www.khanacademy.org
Knuth, E. J., Stephens, A. C., McNeil, N. M. & Alibali, M. W. (2006). Does understanding the equal sign matter? Evidence from solving equations. Journal for Research in Mathematics Education, 37(4), 297–312.
Lavigne, N. C. (2005). Mutually informative measures of knowledge: concept maps plus problem sorts in statistics. Educational Assessment, 10(1), 39–71. doi: 10.1207/s15326977ea1001_3
Mueller, C. M. & Dweck, C. S. (1998). Praise for intelligence can undermine children's motivation and performance. Journal of Personality and Social Psychology, 75(1), 33–52 doi: 10.1037/0022-3514.75.1.33
Murphy, R. et al. (2014). Research on the Use of Khan Academy in Schools. Menlo Park, CA: SRI Education. dostupné z https://www.sri.com/sites/default/files/publications/2014-03-07_implementation_briefing.pdf.
Mustaffa, N., Ismail, Z., Said, M. N. H. M. and Tasir, Z. (2017). A Review on the Development of Algebraic Thinking Through Technology. Advanced Science Letters, 23, 2951–2953. doi: 10.1166/asl.2017.7615
Rittle-Johnson, B. (2006). Promoting transfer: effects of self-explanation and direct instruction. Child Development, 77(1), 1–15. doi: 10.1111/j.1467-8624.2006.00852.x
Rittle-Johnson, B. & Schneider, M. (2016). Developing conceptual and procedural knowledge of mathematics. In The Oxford handbook of numerical cognition (pp. 1102–1118). Oxford, United Kingdom: Oxford University Press. doi: 10.1093/oxfordhb/9780199642342.013.014
Rittle-Johnson, B., Schneider, M. & Star, J. R. (2015). Not a One-Way Street: Bidirectional Relations Between Procedural and Conceptual Knowledge of Mathematics. Educational Psychology Review, 27(4), 587–597. doi: 10.1007/s10648-015-9302-x
Similar web, získáno 8. 5. 2019 z www.similarweb.com/website/khanacademy.org
Star, J. R. & Rittle-Johnson, B. (2009). It pays to compare: an experimental study on computational estimation. Journal of Experimental Child Psychology, 102(2), 408–426. doi: 10.1016/j.jecp.2008.11.004
Strandberg, M. (2013). Homework – is there a connection with classroom assessment? A review from Sweden. Educational Research, 55(4), 325–346. doi: 10.1080/00131881.2013.844936
Trautwein, U., Lüdtke, O. (2009). Predicting homework motivation and homework effort in six school subjects: The role of person and family characteristics, classroom factors, and school track. Learning and Instruction, 19, 243–258. doi: 10.1016/j.learninstruc.2008.05.001
Vančura, J. (2016). Využití Khan Academy pro výuku matematiky na střední škole. Setkání Učitelů Matematiky Všech Typů a Stupňů Škol 2016. Srní, Czech Republic: SUMA JČMF.
Vančura, J. (2017). Research on the language barriers of students who use Khan Academy as a mathematics homework platform. CERME 10 Proceedings, 2660–2667, Dublin. https://keynote.conference-services.net/resources/444/5118/pdf/CERME10_0195.pdf
Vančura, J. (2018a). Can students transfer their mathematical skills gained from their Khan Academy homework to other contexts? INTED2018 Proceedings, 2707–2714 Valencia. doi: 10.21125/inted.2018
Vančura, J. (2018b). Využití Khan Academy pro zadávání a hodnocení domácích úkolů. Matematika, fyzika, informatika, 28(3), 169–180.
Wilson, J., & Rhodes, J. (2010). Student perspectives on homework. Education, 131(2), 351-358.
Zákon č. 561/2004 Sb., o předškolním, základním, středním, vyšším odborném a jiném vzdělávání, školský zákon. (2004). Praha: Tiskárna Ministerstva vnitra.