Is There any Impact of Teaching Vector Spaces From Real Problems? The Case of First Year Engineering Students
Journal of Research in Science, Mathematics and Technology Education, Volume 3, Issue 3, September 2020, pp. 125-139
OPEN ACCESS VIEWS: 1074 DOWNLOADS: 695 Publication date: 15 Sep 2020
OPEN ACCESS VIEWS: 1074 DOWNLOADS: 695 Publication date: 15 Sep 2020
ABSTRACT
In some linear algebra courses at the university level in engineering majors, the vector spaces are presented to students in an abstract way with scarce connections with other subjects and real problems. The goal of this study was to examine the effectiveness, regarding content knowledge and motivation, of a didactic proposal based on a problem based learning and the necessity principle, PBL-NP, modelling real engineering problems through homogeneous systems of linear equations, to introduce the concept of vector space. A quasiexperiment (post-test) was designed with a convenience sample composed of two groups: the experimental group, EG, amounting 33 students who were taught using the PBL -NP, and the control group, CG, composed by 79 students, taught by following an abstract approach. Inferential statistics was used to compare the learning outcomes between groups, by using as contrast variable an external test. The results show that the students in the EG group felt more relaxed and put less effort than CG students, while both groups gather the abstract concepts in a similar extent. Also the percentage who passed the course is higher in the EG compared with CG. Although both groups value positively the subject, a percentage of students in the CG group add some comments referred to the lack of practice related with real problems in the algebra courses taught with the abstract approach.
KEYWORDS
Achievement, linear algebra, motivation, necessity principle, problem solving, vector spaces
CITATION (APA)
Raquel, F.-C., Henar, H., Francisco, P., & Cristina, S. (2020). Is There any Impact of Teaching Vector Spaces From Real Problems? The Case of First Year Engineering Students. Journal of Research in Science, Mathematics and Technology Education, 3(3), 125-139. https://doi.org/10.31756/jrsmte.332
REFERENCES
- Bayat, S., & Tarmizi, R. A. (2010). Assessing cognitive and metacognitive strategies during algebra problem solving among university students. Procedia-Social and Behavioral Sciences, 8, 403-410.
- Burgos, J. de, (2000). Algebra lineal [Linear algebra]. McGraw-Hill.
- Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for research. Ravenio Books.
- Clark, R. M., & Dickerson, S. J. (2018). Assessing the impact of reflective activities in digital and analog electronics courses. IEEE Transactions on Education, 62(2), 141-148.
- Collins, A., & Ferguson, W. (1993). Epistemic forms and epistemic games: Structures and strategies to guide inquiry. Educational Psychologist, 28(1), 25-42.
- Day, R. S. (1988). Alternative representations. In G. H. Bower (Ed.) The psychology of learning and motivation, vol. 22, (pp. 261-305). Academic Press
- Dorier, J. L. (1998). The role of formalism in the teaching of the theory of vector spaces. Linear algebra and its applications, 275, 141-160. doi.: 10.1016 /S0024-3795(97)10061-1
- Dorier, J. L. (Ed.). (2000). On the teaching of linear algebra (Vol. 23). Springer Science & Business Media.
- Dorier, J.-L. & Sierpinska, A., (2001). Research into the teaching and learning of linear algebra, In D. Holton (Ed.), The Teaching and Learning of Mathematics at University Level: An ICMI Study, (pp. 255-273). Kluwer .
- Dorier, J.-L., Robert, A., Robinet, J., & Rogalski, M. (2000). On a research programme concerning the teaching and learning of linear algebra in the first-year of a French science university. International Journal of Mathematics Education, Science and Technology31(1), 27-35.
- Grossman, S. I. (1995). Álgebra lineal [Linear algebra]. McGraw-Hill
- Harel, G. (2000). Three principles of learning and teaching mathematics. In J-L. Dorier (Ed.) On the teaching of linear algebra (pp. 177-189). Springer.
- Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning. Routledge.
- House, J. D., & Telese, J. A. (2008). Relationships between student and instructional factors and algebra achievement of students in the United States and Japan: An analysis of TIMSS 2003 data. Educational Research and Evaluation, 14(1), 101-112.
- Jing, T. J., Tarmizi, R. A., Bakar, K. A., & Aralas, D. (2017). The adoption of variation theory in the classroom: Effect on students’ algebraic achievement and motivation to learn. Electronic Journal of Research in Educational Psychology, 15(2), 307-325. http://dx.doi.org/10.14204/ejrep.42.16070
- Julian, P. K. (2017). The effects of a project-based course on students’ Attitudes toward mathematics and students’ achievement at a two-year college. The Mathematics Enthusiast, 14(1), 509-516.
- Kirshner, D. (1989). The visual syntax of algebra. Journal for Research in Mathematics Education, 274-287.
- Konyalioglu, A. C., Ipek, A. S., & Isik, A. (2003): On the teaching linear algebra at the university level: The role of visualization in the teaching vector spaces. Journal of the Korea Society of Mathematical Education Series D:
- Research in Mathematical Education, 7(1), 59-67.
- Konyalioglu, S., Konyalioglu, A. C., Ipek, A. S., & Isik, A. (2005). The role of visualization approach on student’s conceptual learning. International Journal for Mathematics Teaching and Learning, 47, 1-9.
- Mason, G. S., Shuman, T. R., & Cook, K. E. (2013). Comparing the effectiveness of an inverted classroom to a traditional classroom in an upper-division engineering course. IEEE Transactions on Education, 56(4), 430-435.
- McAuley, E., Duncan, T., & Tammen, V. V. (1989). Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: A confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60(1), 48-58.
- Mills, J. E., & Treagust, D. F. (2003). Engineering education—Is problem-based or project-based learning the answer. Australasian Journal of Engineering Education, 3(2), 2-16.
- Nakhleh, M. B., & Mitchell, R. C. (1993). Concept learning versus problem solving: There is a difference. Journal of Chemical Education, 70(3), 190-192.
- Nurrenbern, S. C., & Pickering, M. (1987). Concept learning versus problem solving: Is there a difference? Journal of Chemical Education, 64(6), 508.
- Rojas, F., & Deulofeu, J. (2015). El formador de profesores de matemática: un análisis de las percepciones de sus prácticas instruccionales desde la tensión estudiante-formador. [The math teacher trainer: an analysis of the perceptions of his or her instructional practices from the student-trainer tension]. Enseñanza de las Ciencias: Revista de Investigación y Experiencias Educativas, 33(1), 47-71.
- Sawrey, B. A. (1990). Concept learning versus problem solving: Revisited. Journal of Chemical Education, 67(3), 253.
- Smith, S. F. (1983, August). Flexible learning of problem-solving heuristics through Adaptive Search. IJCAI, 83, 422425.
- Tarmizi, R. A., & Bayat, S. (2010). Assessing meta-cognitive strategies during algebra problem solving performance among university students. International Journal of Learning, 16(12).
- Ting, J. J., Ahmad Tarmizi, R., Abu Bakar, K., & Aralas, D. (2018). Effects of variation theory approach in teaching and learning of algebra on urban and rural students’ algebraic achievement and motivation. International Journal of Mathematical Education in Science and Technology, 49(7), 986-1002. DOI:
- 10.1080/0020739X.2018.1435915
- Toussaint, M. J. (2016). The impact of "real world" experiences through academic service learning on students' success rate, attitudes, and motivation in intermediate algebra at a public university. ProQuest LLC.
- Wang, Tse-Wei. (1989). A course on applied linear algebra. Chemical Engineering Education, 23(4), 236–241.
- Watson, A., Spyrou, P., & Tall, D. (2003). The relationship between physical embodiment and mathematical symbolism: The concept of vector. The Mediterranean Journal of Mathematics Education, 1(2), 73-97.
- Zhang, J. (1997). The nature of external representations in problem solving. Cognitive science, 21(2), 179-217.
LICENSE
This work is licensed under a Creative Commons Attribution 4.0 International License.