202
Views
2
CrossRef citations to date
0
Altmetric
Articles

Efficiency of blended learning of calculus content during the Covid19 crisis

ORCID Icon, ORCID Icon &
Pages 52-66 | Received 22 Feb 2022, Accepted 06 May 2022, Published online: 18 May 2022

References

  • Adedoyin, O. B., & Soykan, E. (2020). COVID-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, 2(1), 1–13. https://doi.org/10.1080/10494820.2020.1813180
  • Al Salman, S., Alkathiri, M., & Khaled Bawaneh, A. (2021). School off, learning on: Identification of preference and challenges among school students towards distance learning during COVID19 outbreak. International Journal of Lifelong Education, 40(1), 53–71. https://doi.org/10.1080/02601370.2021.1874554
  • Anabousy, A., Daher, W., Baya’a, N., & Abu-Naja, M. (2014). Conceiving function transformations in different representations: Middle school student working with technology. Mathematics Education, 9(2), 99–114. https://doi.org/10.29333/iejme/284
  • Anthony, B., Kamaludin, A., Romli, A., Raffei, A. F. M., Phon, D. N. A. L. E., Abdullah, A., & Ming, G. L. (2022). Blended learning adoption and implementation in higher education: A theoretical and systematic review. Technology, Knowledge and Learning, 27(2), 531–578. https://doi.org/10.1007/s10758-020-09477-z
  • Arzarello, F., Ferrara, F., & Robutti, O. (2012). Mathematical modelling with technology: The role of dynamic representations. Teaching Mathematics and Its Applications, 31(1), 20–30. https://doi.org/10.1093/teamat/hrr027
  • Bakar, A., Mohd Ayub, K. F. A., & Ahmad Tarmizi, R. (2010). Utilization of computer technology in learning transformation. International Journal of Education and Information Technologies, 4(2), 91–99.
  • Bersin, J. (2004). The blended learning book: Best practices, proven methodologies and lessons learned. San Francisco, CA.
  • Bodner, G. M. (1986). Constructivism: A theory of knowledge. Journal of Chemical Education, 63(10), 873–878. https://doi.org/10.1021/ed063p873
  • Bonk, C. J., & Graham, C. R. (2006). The Handbook of blended learning. Pfeiffer.
  • Borba, M., & Confrey, J. (1996). A student's construction of transformations of functions in a multiple representational environment. Educational Studies in Mathematics, 31(3), 319–337. https://doi.org/10.1007/BF00376325
  • Božić, R. (2019). Metodička obrada funkcija sa parametrima uz pomoć računara (Doktorska disertacija, Univerzitet u Novom Sadu). National Repository of Dissertations in Serbia. https://nardus.mpn.gov.rs/handle/123456789/11380
  • Božić, R., Takači, Đ, & Stankov, G. (2019). Influence of dynamic software environment on students’ achievement of learning functions with parameters. Interactive Learning Environments, 29(4), 655–669. https://doi.org/10.1080/1049820.2019.1602842
  • Brooks, J. G., & Brooks, M. G. (1993). In search of understanding: The case for constructivist classrooms. American Society for Curriculum Development.
  • Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers & Education, 123, 53–64. https://doi.org/10.1016/j.compedu.2018.04.007
  • Daher, W. M., & Anabousi, A. A. (2015). Students’ recognition of function transformations’ themes associated with the algebraic representation. Journal of Research in Mathematics Education, 4(2), 179–194. https://doi.org/10.17583/redimat.2015.1110
  • Devlin, M., & McKay, J. (2016). Teaching students using technology: Facilitating success for students from low socioeconomic status backgrounds in Australian universities. Australasian Journal of Educational Technology, 32(1), 92–106. https://doi.org/10.14742/ajet.2053
  • Doorman, M., Drijvers, P., Gravemeijer, K., Boon, P., & Reed, H. (2012). Tool use and the development of the function concept: From repeated calculations to functional thinking. International Journal of Science and Mathematics Education, 10(6), 1243–1267. https://doi.org/10.1007/s10763-012-9329-0
  • Doruk, B. K., Aktumen, M., & Aytekin, C. (2013). Pre-service elementary mathematics teachers’ opinions about using GeoGebra in mathematics education with reference to ‘teaching practices’. Teaching Mathematics and Its Applications, 32(3), 140–157. https://doi.org/10.1093/teamat/hrt009
  • Drijvers, P., Thurm, D., Vandervieren, E., Klinger, M., Moons, F., Van der Ree, H., Mol, A., Barzel, B., & Doorman, M. (2021). Distance mathematics teaching in Flanders, Germany, and the Netherlands during COVID-19 lockdown. Educational Studies in Mathematics, 108(1-2), 35–64. https://doi.org/10.1007/s10649-021-10094-5
  • Ermete, M., Brackett, N., Powell, K., Krause, E., & Lapp, D. (2010). The Role of Dynamic Representations in Students’ Development of Algebraic Concepts. Program Reports. https://www.cmich.edu/colleges/cst/math/Documents/LURE_2010_Program_Reports.pdf
  • Fitri, S., & Zahari, C. L. (2019). The implementation of blended learning to improve understanding of mathematics. Journal of Physics Conference Series, 1188 - 012109. https://doi.org/10.1088/1742-6596/1188/1/012109
  • Font, V., Godino, J., & D’amore, B. (2018). An ontosemiotic approach to representations in mathematics education. For the Learning of Mathematics, 27(2), 3–9.
  • Goldin, G., & Kaput, J. (1996). A joint perspective on the idea of representation in learning and doing mathematics. In L. P. Steffe, P. Nesher, P. Cobb, G. A. Goldin, & B. Greer (Eds.), Theories of mathematical learning (pp. 397–430). Erlbaum.
  • Goldin, G., & Shteingold, N. (2001). System of representations and the development of mathematical concepts. In A. Cuoco & F. R. Curcio (Eds.), The roles of representation in school mathematics (pp. 1–23). NCTM.
  • Gunbas, N. (2015). Students’ mathematics word problem-solving achievement in a computer-based story. Journal of Computer Assisted Learning, 31(1), 78–95. https://doi.org/10.1111/jcal.12067
  • Guri-Rosenblit, S. (2005). ‘Distance education’ and ‘e-learning’: Not the same thing. Higher Education, 49(4), 467–493. https://doi.org/10.1007/s10734-004-0040-0
  • Guven, B. (2012). Using dynamic geometry software to improve eight grade students’ understanding of transformation geometry. Australasian Journal of Educational Technology, 28(2), 364–382. https://doi.org/10.14742/ajet.878
  • Hwang, W. Y., & Hu, S. S. (2013). Analysis of peer learning behaviors using multiple representations in virtual reality and their impacts on geometry problem solving. Computers & Education, 62, 308–319. https://doi.org/10.1016/j.compedu.2012.10.005
  • Iran-Nejad, A. (1995). Constructivism as substitute for memorization in learning: Meaning is created by learner. Education, 116, 16–32.
  • Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models (2nd Ed. pp. 215–239), Lawrence Erlbaum Associates.
  • Kilpatrick, J., Swafford, J., & Findell, B. (2001). Adding it up: Helping children learn mathematics. National Academy Press.
  • Lin, Y. W., Tseng, C. L., & Chiang, P. J. (2017). The effect of blended learning in mathematics course. EURASIA Journal of Mathematics, Science and Technology Education, 13(3), 741–770. https://doi.org/10.12973/eurasia.2017.00641a
  • Lisarelli, G. (2017). Exploiting Potentials of Dynamic Representations of Functions with Parallel Axes. The 13th International Conference on Technology in Mathematics Teaching (ICTMT 13). Lyon, Ecole Normale Supérieure de Lyon and the University Lyon.
  • Lopes, A. P., & Soares, F. (2018). FLIPPING A MATHEMATICS COURSE, A BLENDED LEARNING APPROACH. INTED2018 Proceedings, pp. 3844-3853.
  • Lorsbach, A., & Tobin, K. (1992). Constructivism as a referent for scince teaching. NARST Research Matters-to the Science Teacher, 30.
  • Maatuk, A. M., Elberkawi, E. K., Aljawarneh, S., Rashaideh, H., & Alharbi, H. (2022). The COVID-19 pandemic and E-learning: Challenges and opportunities from the perspective of students and instructors. Journal of Computing in Higher Education, 34(1), 21–38. https://doi.org/10.1007/s12528-021-09274-2
  • McClaran, R. (2013). Investigating the impact of Interactive applets on students’ understanding of parameter changes to parent functions: An explanatory mixed methods study. Theses and dissertations-science, technology. Engineering, and Mathematics (STEM) Education.
  • Milenković, A., Takači, Đ, & Božić, R. (2020). On the influence of software application for visualization in teaching double integrals. Interactive Learning Environment, https://doi.org/10.1080/10494820.2020.1719164
  • Milovanović, M., Takači, Đ, & Milajić, A. (2011). Multimedia approach in teaching mathematics – example of lesson about the definite integral application for determining an area. International Journal of Mathematical Education in Science and Technology, 42(2), 175–187. https://doi.org/10.1080/0020739X.2010.519800
  • Nakahara, T. (2008). Cultivating mathematical thinking through representation-utilizing the representational system. APEC-TSUKUBA International Congress, Japan.
  • Naylor, S., & Keogh, B. (1999). Constructivism in classroom: Theory into practice. Journal of Science Teacher Education, 10(2), 93–106. https://doi.org/10.1023/A:1009419914289
  • Ozgun-Koca, S. A. (2008). Ninth grade students studying the movement of fish to learn about linear relationships: The use of video-based analysis software in mathematics classrooms. The Mathematics Educator, 18(1), 15–25.
  • Poon, J. (2014). A cross-country comparison on the use of blended learning in property education. Property Management, 32(2), 154–175. https://doi.org/10.1108/PM-04-2013-0026
  • Psotka, J. (2022). Exemplary online education: For whom online learning can work better. Interactive Learning Environments, 30(2), 199–201. https://doi.org/10.1080/10494820.2022.2031065
  • Rau, M., Michaelis, J., & Fay, N. (2015). Connection making between multiple graphical representations: A multi-methods approach for domain-specific grounding of an intelligent tutoring system for chemistry. Computers & Education, 82, 460–485. https://doi.org/10.1016/j.compedu.2014.12.009
  • Şengören, S. K. (2014). Prospective physics teachers’ use of multiple representations for solving the image formation problems. Journal of Baltic Science Education, 13(1), 59–74. https://doi.org/10.33225/jbse/14.13.59
  • Setyaningrum, W. (2019). Blended learning: Does it help students in understanding mathematical concepts? Jurnal Riset Pendidikan Matematika, 5(2), 244–253. https://doi.org/10.21831/jrpm.v5i2.21428
  • Sever, G., & Yerushalmy, M. (2007). To sense and to visualize functions: The case of graphs’ stretching. In P. P. Demetra & P. George (Eds.), The fifth Conference of the European Society for research in mathematics Education (CERME5) (pp. 1509–1518). Department of Education, University of Cyprus.
  • Sjoberg, S. (2010). Constructivism and learning. In B. McGaw & P. Peterson (Eds.), International encyclopaedia of education (3rd Edition, pp. 485–490). Elsevier.
  • Stevanović, A., Božić, R., & Radović, S. (2021). Higher education students’ experiences and opinion about distance learning during the Covid-19 pandemic. Journal of Computer Assisted Learning, 37(6), 1682–1693 https://doi.org/10.1111/jcal.12613
  • Stols, G. (2012). Does the use of technology make a difference in the geometric cognitive growth of pre-service mathematics teachers? Australasian Journal of Educational Technology, 28(7), 1233–1247. https://doi.org/10.14742/ajet.799
  • Taber, K. S. (2011). Constructivism as educational theory: Contingency in learning, and optimally guided instruction. In J. Hassaskhan (Ed.), Educational theory (pp. 39–61). Nova Science Publishers, Hauppauge.
  • Takači, Đ., Pešić, D., & Tatar, J. (2006). On the continuity of functions. International Journal of Mathematical Education in Science and Tehnology, 37(7), 783–791.
  • Takači, Đ., Stankov, G., & Milanović, I. (2015). Efficiency of learning environment using GeoGebra when calculus contents are learned in collaborative groups. Computers & Education, 82, 421–431. https://doi.org/10.1016/j.compedu.2014.12.002
  • Tall, D. (1992). The transition to advanced mathematical thinking: Functions, limits, infinity, and proof. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 495–511). Macmillan.
  • Tall, D. (2003). Using technology to support an embodied approach to learning concepts in mathematics. In L. M. Carvalho & L. C. Guimarães (Eds.), História e Tecnologia no Ensino da Matemática (vol. 1, pp. 1–28). Brasil.
  • Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: A structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306–328. https://doi.org/10.1080/10494820.2015.1122635
  • Teo, T., & Milutinovic, V. (2015). Modelling the intention to use technology for teaching mathematics among pre-service teachers in Serbia. Australasian Journal of Educational Technology, 31(4), 363–380. https://doi.org/10.14742/ajet.1668
  • Tobin, K., & Tippins, D. (1993). Constructivism as a referent for teaching and learning. In K. Tobin (Ed.), The practice of constructivism in science education (pp. 3–22). Lawrence Erlbaum Associates.
  • van der Meij, J., & de Jong, T. (2011). The effects of directive self-explanation prompts to support active processing of multiple representations in a simulation-based learning environment. Journal of Computer Assisted Learning, 27(5), 411–423. https://doi.org/10.1111/j.1365-2729.2011.00411.x
  • Venema, S., & Lodge, J. M. (2013). Capturing dynamic presentation: Using technology to enhance the chalk and the talk. Australasian Journal of Educational Technology, 29(1), 20–31. https://doi.org/10.14742/ajet.62
  • Von Glasersfeld, E. (1995). Radical constructivism: A way of knowing and learning. Falmer Press.
  • Wekerle, C., Daumiller, M., & Kollar, I. (2022). Using digital technology to promote higher education learning: The importance of different learning activities and their relations to learning outcomes. Journal of Research on Technology in Education, 54(1), 1–17. https://doi.org/10.1080/15391523.2020.1799455
  • Yerushalmy, M. (1991). Student perceptions of aspects of algebraic function using multiple representation software. Journal of Computer Assisted Learning, 7(1), 42–57. https://doi.org/10.1111/j.1365-2729.1991.tb00223.x

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.