Middle School Students’ Motivation in Solving Modelling Activities With Technology

Wajeeh Daher

doi:10.29333/ejmste/11127

Full Text (PDF)

Wajeeh Daher ¹ ² ^*

More Detail

¹ Al-Qasemi Academic College of Education, ISRAEL² An-Najah National University, PALESTINE^* Corresponding Author

Abstract

Researchers pointed at modelling activities as affecting positively students’ learning including motivation to learn, but little research has studied students’ motivation to learn mathematics during their engagement in modelling activities with technology. Three groups of 4-5 students carried out the Roc modelling activity utilizing the internet and GeoGebra. The data was collected using video recording and students’ solution texts. Inductive and deductive content analysis were used to analyze the data. The research results indicated that the groups experienced motivational patterns that included both sympathy and mastery styles, where these styles were accompanied with confirming styles in general, but sometimes with rebellious styles too. In addition, carrying out the modelling activity using the internet and GeoGebra, the group members were engaged primarily with processes-based motivational styles, but doing so, they kept in mind their goal to build a mathematical model of the Roc bird.

Keywords

GeoGebra
mathematical activity
middle school
modelling activity
motivation
technology

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 17, Issue 9, September 2021, Article No: em1999

https://doi.org/10.29333/ejmste/11127

Publication date: 06 Aug 2021

Article Views: 2627

Article Downloads: 1423

Open Access Disclosures References How to cite this article

Disclosure

Declaration of Conflict of Interest: No conflict of interest is declared by author(s).

Data sharing statement: Data supporting the findings and conclusions are available upon request from the corresponding author(s).

References

Apter, M. J. (2001). An introduction to reversal theory. In M. J. Apter (Ed.), Motivational styles in everyday life: A guide to reversal theory (pp. 3-35). American Psychological Association. https://doi.org/10.1037/10427-001
Arseven, A. (2015). Mathematical modelling approach in mathematics education. Universal Journal of Educational Research, 3(12), 973-980. https://doi.org/10.13189/ujer.2015.031204
Arzarello, F., Ferrara, F., & Robutti, O. (2012). Mathematical modelling with technology: the role of dynamic representations. Teaching Mathematics and Its Applications: International Journal of the IMA, 31(1), 20-30. https://doi.org/10.1093/teamat/hrr027
Baker, R., Walonoski, J., Heffernan, N., Roll, I., Corbett, A., & Koedinger, K., (2008). Why students engage in “Gaming the system” behavior in interactive learning environments. Journal of Interactive Learning Research, 19(2), 185-224.
Bal-Taştan, S., Davoudi, S. M. M., Masalimova, A. R., Bersanov, A. S., Kurbanov, R. A., Boiarchuk, A. V., & Pavlushin, A. A. (2018). The impacts of teacher’s efficacy and motivation on student’s academic achievement in science education among secondary and high school students. EURASIA Journal of Mathematics, Science and Technology Education, 14(6), 2353-2366. https://doi.org/10.29333/ejmste/89579
Barak, M., Maymon, T., & Harel, G. (1999). Teamwork in modern organizations: implications for technology education. International Journal of Technology and Design Education, 9(1), 85-101. https://doi.org/10.1023/A:1008849803984
Bawaneh, A. K., & Moumene, A. B. H. (2020). Flipping the classroom for optimizing undergraduate students’ motivation and understanding of medical physics concepts. EURASIA Journal of Mathematics, Science and Technology Education, 16(11), em1899. https://doi.org/10.29333/ejmste/8561
Benita, M., Roth, G., & Deci, E. L. (2014). When are mastery goals more adaptive? It depends on experiences of autonomy support and autonomy. Journal of Educational Psychology, 106(1), 258. https://doi.org/10.1037/a0034007
Biccard, P., & Wessels, D. C. (2011). Documenting the development of modelling competencies of grade 7 mathematics students. In G. Kaiser, W. Blum, R. Borromeo Ferri, & G. Stillman, (Eds.), Trends in teaching and learning of mathematical modelling (pp. 375-383). Springer Nature. https://doi.org/10.1007/978-94-007-0910-2_37
Blum, W. (1995). Applications and modeling in mathematics teaching and mathematics education – some important aspects of practice and of research. In C. Sloyer et al (Eds.), Advances and perspectives in the teaching of Mathematical modeling and Applications (pp. 1- 20). Water Street Mathematics.
Blum, W., & Leiß, D. (2005). “Filling Up”-the problem of independence-preserving teacher interventions in lessons with demanding modeling tasks. In M. Bosch (Ed.), Proceedings of the Fourth Congress of the European Society for Research in Mathematics Education (CERME 4) (pp. 1623-1633). Fundemi Iqs, Universitat Ramon Llull.
Bomia, L., Beluzo, L., Demeester, D., Elander, K., Johnson, M., & Sheldon, B. (1997). The impact of teaching strategies on intrinsic motivation. ERIC Clearinghouse on Elementary and Early Childhood Education. (ERIC Document Reproduction Service No. ED 418 925).
Bora, A., & Ahmed, S. (2019). Mathematical modeling: An important tool for mathematics teaching. International Journal of Research and Analytical Reviews (IJRAR), 6(2), 252-256.
D’Mello, S., Lehman, B., Pekrun, R., & Graesser, A. (2014). Confusion can be beneficial for learning. Learning and Instruction, 29, 153-170. https://doi.org/10.1016/j.learninstruc.2012.05.003
Daher, W. (2009). Preservice teachers’ perceptions of applets for solving mathematical problems: Need, difficulties and functions. Journal of Educational Technology & Society, 12(4), 383-395.
Daher, W. (2014). Students’ adoption of social networks as environments for learning and teaching: The case of the Facebook. International Journal of Emerging Technologies in Learning, 9(4), 16-24. https://doi.org/10.3991/ijet.v9i8.3722
Daher, W. (2015). Discursive positionings and emotions in modelling activities. International Journal of Mathematical Education in Science and Technology, 46(8), 1149-1164. https://doi.org/10.1080/0020739X.2015.1031836
Daher, W. M., & Shahbari, J. A. (2015). Pre-service teachers’ modelling processes through engagement with model eliciting activities with a technological tool. International Journal of Science and Mathematics Education, 13(1), 25-46. https://doi.org/10.1007/s10763-013-9464-2
Daher, W., & Awawdeh Shahbari, J. (2020). Secondary students’ identities in the virtual classroom. Sustainability, 12(11), 4407. https://doi.org/10.3390/su12114407
Daher, W., & Baya’a, N. (2012). Characteristics of middle school students learning actions in outdoor mathematical activities with the cellular phone. Teaching Mathematics and its Applications: An International Journal of the IMA, 31(3), 133-152. https://doi.org/10.1093/teamat/hrr018
Daher, W., Alfahel, E., & Anabousy, A. (2021). Moderating the relationship between student’s gender and science motivation. EURASIA Journal of Mathematics, Science and Technology Education, 17(5), em1956. https://doi.org/10.29333/ejmste/10829
English, L. D. (2003). Problem posing in the elementary curriculum. In F. Lester & R. Charles (Eds.), Teaching mathematics through problem solving (pp. 187-198). National Council of Teachers of Mathematics.
Galbraith, P., & Holton, D. (2018). Mathematical modelling: a guidebook for teachers and teams. Australian Council for Educational Research.
Geiger, V., Faragher, R., & Goos, M. (2010). CAS-enabled technologies as ‘agents provocateurs’ in teaching and learning mathematical modeling in secondary school classrooms. Mathematics Education Research Journal, 22(2), 48-68. https://doi.org/10.1007/BF03217565
Higgins, K., Huscroft-D’Angelo, J., & Crawford, L. (2019). Effects of technology in mathematics on achievement, motivation, and attitude: A meta-analysis. Journal of Educational Computing Research, 57(2), 283-319. https://doi.org/10.1177/0735633117748416
Jang, H. (2008). Supporting students’ motivation, engagement, and learning during an uninteresting activity. Journal of Educational Psychology, 100(4), 798-811. https://doi.org/10.1037/a0012841
Lewis, G. (2015, February). Patterns of motivation and emotion in mathematics classrooms. In Proceedings of CERME 9-Ninth Congress of the European Society for Research in Mathematics Education (pp. 1216-1222).
Michaelides, M. P., Brown, G. T., Eklöf, H., & Papanastasiou, E. C. (2019). The Relationship of Motivation with Achievement in Mathematics. In Motivational Profiles in TIMSS Mathematics (pp. 9-23). Springer, Cham. https://doi.org/10.1007/978-3-030-26183-2_2
Middleton, J. A., & Spanias, P. A. (1999). Motivation for achievement in mathematics: Findings, generalizations, and criticisms of the research. Journal for Research in Mathematics Education, 30(1), 65-88. https://doi.org/10.2307/749630
Molina-Toro, J. F., Rendón-Mesa, P. A., & Villa-Ochoa, J. (2019). Research trends in digital technologies and modeling in mathematics education. EURASIA Journal of Mathematics, Science and Technology Education, 15(8), em1736. https://doi.org/10.29333/ejmste/108438
Mousoulides, N. G., Christou, C., & Sriraman, B. (2008). A modeling perspective on the teaching and learning of mathematical problem solving. Mathematical Thinking and Learning, 10(3), 293-304. https://doi.org/10.1080/10986060802218132
Mousoulides, N., Pittalis, M., Christou, C., Boytchev, P., Sriraman, B., & Pitta, D. (2007). Mathematical modelling using technology in elementary school. In 8th international conference on technology in mathematics teaching, University of Hradec Králové, Czech Republic.
Ntourou, V., Kalogiannakis, M., & Psycharis, S. (2021). A study of the impact of arduino and visual programming in self-efficacy, motivation, computational thinking and 5th grade students’ perceptions on Electricity. EURASIA Journal of Mathematics, Science and Technology Education, 17(5), em1960. https://doi.org/10.29333/ejmste/10842
Patton, M. Q. (2002). Qualitative research and evaluation methods. Sage.
Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational psychology review, 18(4), 315-341. https://doi.org/10.1007/s10648-006-9029-9
Rowe, A. D., & Fitness, J. (2018). Understanding the role of negative emotions in adult learning and achievement: A social functional perspective. Behavioral Sciences, 8(2), 27. https://doi.org/10.3390/bs8020027
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67. https://doi.org/10.1006/ceps.1999.1020
Schutz, P. A., Hong, J. Y., Cross, D. I., & Osbon, J. N. (2006). Reflections on investigating emotion in educational activity settings. Educational Psychology Review, 18(4), 343-360. https://doi.org/10.1007/s10648-006-9030-3
Shahbari, J. A., & Peled, I. (2017). Modelling in primary school: Constructing conceptual models and making sense of fractions. International Journal of Science and Mathematics Education, 15(2), 371-391. https://doi.org/10.1007/s10763-015-9702-x
Shahbari, J. A., Daher, W., & Rasslan, S. (2014). Mathematical knowledge and the cognitive and metacognitive processes emerged in model-eliciting activities. International Journal on New Trends in Education and Their Implications, 5(2), 209-219.
Shahbari, J. A., Tabach, M., & Heyd-Metzuyanim, E. (2019). Development of modelling routines and its relation to identity construction. In S. Chamberlin & B. Sriraman, (Eds.), Affect in Mathematical Modeling (pp 177-199). Springer International Publishing. https://doi.org/10.1007/978-3-030-04432-9_11
Siller, H.-S. & Greefrath, G. (2010). Mathematical modeling in class regarding to technology. In V. Durand-Guerrier, S. Soury-Lavergne, and F. Arzarello (Eds.), Proceedings of the Sixth Congress of the European Society for Research in Mathematics Education (CERME 6), (pp. 2136-2145). Lyon, France.
Svebak, S. (1988). A state-based approach to the role of effort in experience of emotions. In V. Hamilton, G. H. Bower, & N. H. Frijda (eds), Cognitive perspectives on emotion and motivation (pp. 145-171). Kluwer Academic Publishers. https://doi.org/10.1007/978-94-009-2792-6_6
Wæge, K. (2010, January). Motivation for learning mathematics in terms of needs and goals. In Proceedings of the Sixth Congress of the European Society for Research in Mathematics Education (Vol. 6, pp. 84-93).
Williams, S. (2011). Engaging and informing students through group work. Psychology Teaching Review, 17(1), 24-34.

How to cite this article

APA

Daher, W. (2021). Middle School Students’ Motivation in Solving Modelling Activities With Technology. Eurasia Journal of Mathematics, Science and Technology Education, 17(9), em1999. https://doi.org/10.29333/ejmste/11127

Vancouver

Daher W. Middle School Students’ Motivation in Solving Modelling Activities With Technology. EURASIA J Math Sci Tech Ed. 2021;17(9):em1999. https://doi.org/10.29333/ejmste/11127

AMA

Daher W. Middle School Students’ Motivation in Solving Modelling Activities With Technology. EURASIA J Math Sci Tech Ed. 2021;17(9), em1999. https://doi.org/10.29333/ejmste/11127

Chicago

Daher, Wajeeh. "Middle School Students’ Motivation in Solving Modelling Activities With Technology". Eurasia Journal of Mathematics, Science and Technology Education 2021 17 no. 9 (2021): em1999. https://doi.org/10.29333/ejmste/11127

Harvard

Daher, W. (2021). Middle School Students’ Motivation in Solving Modelling Activities With Technology. Eurasia Journal of Mathematics, Science and Technology Education, 17(9), em1999. https://doi.org/10.29333/ejmste/11127

MLA

Daher, Wajeeh "Middle School Students’ Motivation in Solving Modelling Activities With Technology". Eurasia Journal of Mathematics, Science and Technology Education, vol. 17, no. 9, 2021, em1999. https://doi.org/10.29333/ejmste/11127