Learners’ Graphical Efficacy When Solving Trigonometric Problems
DOI:
https://doi.org/10.22219/mej.v7i2.27636Abstract
This study explored grade 12 learners’ graphical efficacy when solving problems involving trigonometric graphs. A structured test consisting of five trigonometric problems, with variations in context and structure, was administered to a purposefully selected group of 25 Grade 12 learners from the Sekhukhune District in South Africa. Insights into learners' graphing efficacy were obtained through task-based interviews. Data were analysed using direct interpretation which involved deductive thematic analysis of the task-based interviews and content analysis of the test scripts to match learners’ responses to the themes drawn from the Meta-Representational Competence (MRC) framework. The results showed that most learners lack invention and functioning, critiquing and reflection efficacies and hence this affected their drawing and interpretation of the graphs and consequently lead to incorrect solutions. Furthermore, the results show most learners have critiquing efficacy. This indicates that learners lack graphical efficacy for solving trigonometric problems involving trigonometric functions. This finding has pedagogic implications: the apparent lack of graphical efficacy in graphical solutions may suggest inadequate mastery of the concept. Therefore, this study recommends that the teaching and learning of trigonometric graphs should consider the development of invention, functioning, critiquing and reflection efficacies.
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Adjei, S. A. (2018). Refining Prerequisite Skill Structure Graphs Using Randomised Controlled Trials. Retrieved from https://digitalcommons.wpi.edu/etd-dissertations/177.
Angra, A., & Gardner, S. M. (2017). Reflecting on graphs: Attributes of graph choice and construction practices in biology. CBE—Life Sciences Education, 16(3), 1-15 https://doi.org/10.1187/cbe.16-08-0245
Arcavi, A. (2003). The role of visual representations in the learning of mathematics. Educational Studies in Mathematics, 52(3), 215-241. https://doi.org/10.1023/A:1024312321077
Arsaythamby, V., & Julinamary, P. (2015). Learners' Perception on Difficulties of Symbols, Graphs and Problem-Solving in Economic. Procedia-Social & Behavioural Sciences, 177, 240-245. https://doi.org/10.1016/j.sbspro.2015.02.401
Batiibwe, M. S. K. (2020) Developing mathematical thinking through activity-based heuristic approach: a case of making connections between patterns, sequences and graphs. European Journal of Education Studies, 6(12), 284-310. https://doi.org/10.5281/zenodo.3692059
Bodén, U., & Stenliden, L. (2019). Emerging Visual Literacy through Enactments by Visual Analytics and Students. Designs for Learning, 11(1), 40–51. https://doi.org/10.16993/dfl.108
Bogdan, R., & Biklen. S. (1982). Qualitative research for education: An introduction to theory and methods. Boston: Allyn & Bacon.
Boote. S.K. (2014). Assessing and understanding line graph interpretations using a scoring rubric of organized cited factors. Journal of Science Teacher Education, 25, (3), 333-54
https://doi.org/10.1007/s10972-012-9318-8
Bornstein, N. (2020). Teaching transformations of trigonometric functions with technology. Journal of Interactive Media in Education, 1(15), 1-9. https://doi.org/10.5334/jime.503
Cambridge Handbook 2019 (International): Regulations and guidance for administering. Cambridge: Cambridge Assessment International Education.
Carter, J. (2010). Graphs and proofs in analysis. International Studies in the Philosophy of Science, 24(1), 1-14. https://doi.org/10.1080/02698590903467085
Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2019). Implications for educational practice of the science of learning and development. Applied Developmental Science, p.1-44. https://doi.org/10.1080/10888691.2018.1537791
Davis, J. R., & Arend, B. D. (2012). Facilitating seven ways of learning: A resource for more purposeful, effective, and enjoyable college teaching. Virginia: Stylus Publishing, LLC. https://doi.org/10.4324/9781003444763
De Vries, E., & Lowe, R. (2010). Graphicacy: What does the learner bring to a graphic? In Scheiter, K. (Ed), Comprehension of text and graphics. Tracing the mind: how do we learn from text and graphics? Tuebingen Germany: Knowledge Media Research Centre. http://hdl.handle.net/20.500.11937/26759
Department of Basic Education (South Africa). (2011). Curriculum and Assessment Policy Statement Grades 10-12 Mathematics. Government Printing Works, 2011.
Department of Basic Education (South Africa). (2021). Report on the National Senior Certificate Examination: National diagnostic report on learners’ performance. Government Printing Works.
Department of Basic Education (South Africa). (2022). Report on the National Senior Certificate Examination: National diagnostic report on learners’ performance. Government Printing Works.
DiSessa, A. A. (2004). Meta representation: Native Competence and Targets for Instruction. Cognition and Instruction, 22, 293-331. https://doi.org/10.1207/s1532690xci2203_2
DiSessa, A., & Sherin, B. L. (2000). Meta-representation: An introduction. The Journal of Mathematical Behavior, 19(4), 385-398. https://doi.org/10.1016/S0732-3123(01)00051-7
Fudin, M. I., Cahyono, H., & Putri, O. R. U. (2022). Analysis of the Visual to Verbal Mathematical Representation Process for Junior High School Students in Solving HOTS Questions in terms of Adversity Quotient. Mathematics Education Journal, 6(2), 195-203. https://doi.org/10.22219/mej.v6i2.23047
Fyfe, E. R., Mcneil, N. M., Son, J. Y., & Goldstone, R. L. (2014). Concreteness fading in Mathematics and Science instruction: A systematic review. Educational Psychology Review, 26, (1), 9-25. https://doi.org/10.1007/s10648-014-9249-3
Glazer, N. (2011). Challenges with graph interpretation: A review of the literature. Studies in Science Education, 47(2), 183-210. https://doi.org/10.1080/03057267.2011.605307
Görg, C., Pohl, M., Qeli, E., & Xu, K. (2007). Visual Representations. In Kerren, A., Ebert, A., Meye, J., eds.: Human-Centered Visualization Environments. Volume 4417 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, p.163–230, 2007. https://doi.org/10.1007/978-3-540-71949-6_4
Gur, H. (2009). Trigonometry Learning. New Horizons in Education, 57(1), 67-80.
Halim, N., F., Effendi, M., M., & Dintarini, M. (2023). Analysis of Trigonometry Learning Outcomes in the Application of Geogebra-Assisted Jigsaw Metods. Mathematics Education Journal, 7(1), 86-99. https://doi.org/10.22219/mej.v7i1.23266
Hebert, M. A., & Powell, S. R. (2016). Examining fourth-grade mathematics writing: features of organisation, mathematics vocabulary, and mathematical representations. Reading and Writing, 29, (7,) 1511-1537. https://doi.org/10.1007/s11145-016-9649-5
Herscovics, N. (2018). Cognitive obstacles encountered in the learning of algebra. Research issues in the learning and teaching of algebra, 60-86. In, Wagner, S., & Kieran, C. (Eds.). (2018). Research Issues in the Learning and Teaching of Algebra: The Research Agenda for Mathematics Education, Volume 4. https://dx.doi.org/10.4324/9781315044378-6
Hill, M., & Sharma, M. D. (2015). Students’ representational fluency at university: A cross-sectional measure of how multiple representations are used by physics students using the representational fluency survey. Eurasia Journal of Mathematics, Science and Technology Education, 11(6), 1633-1655. https://doi.org/10.12973/eurasia.2015.1427a
Hindi, A., N., AM, & HR, I., S.. (2023). Student Thinking Process in Solving Mathematical Representation Problems. Mathematics Education Journal,7(1),47-59. https://doi.org/10.22219/mej.v7i1.24830
Hsieh, H.-F., & Shannon, S.E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15. (9), 1277-1288. https://doi.org/10.1177/1049732305276687
Jenlink, P. M. (2019). Multimedia Learning Theory: Preparing for the New Generation of Learners. London: Littlefield.
Koedinger, K. R., & Nathan, M. J. (2004). The real story behind story problems: Effects of representations on quantitative reasoning. The Journal of the Learning Sciences, 13, (2), 129–164. https://doi.org/10.1207/s15327809jls1302_1
Lowrie, T.; Diezmann, C., & Logan, T. (2011). Understanding graphicacy: Learners' making sense of graphics in mathematics assessment tasks. International Journal for Mathematics Teaching and Learning, 1, (1), 1-32.
Makwakwa, E. (2012). Exploring problems encountered in the teaching and learning of Statistics in Grade 11. Doctoral dissertation. Faculty of Education. University of South Africa Pretoria.
Maries, A., Lin, S. Y., & Singh, C. (2017). Challenges in designing appropriate scaffolding to improve students’ representational consistency: The case of a Gauss’s law problem. Physical Review Physics Education Research, 13, (2), 020103. https://doi.org/10.1103/PhysRevPhysEducRes.13.020103
Maries, A.; Singh, C. (2016). A good graph is valuable despite the choice of a mathematical approach to problem-solving. arXiv preprint arXiv:1601.04340. https://doi.org/10.48550/arXiv.1601.04340
Maries, A.; Singh, C. (2018). Do learners benefit from drawing productive diagrams themselves while solving introductory physics problems? The case of two electrostatics problems. European Journal of Physics, 39(1), p.015703. https://doi.org/10.1088/1361-6404/aa9038
Matheson, I.; Hutchinson, N. (2014). Visual representation in mathematics. 2014. Online. https://www. ldatschool. ca/visual-representation.
Matuk, C., Zhang, J., Uk, I., & Linn, M. C. (2019). Qualitative graphing in an authentic inquiry context: How construction and critique help middle school students to reason about cancer. Journal of Research in Science Teaching, 56(7), 905-936. https://doi.org/10.1002/tea.21533
Meirelles, I. (2013). Design for information: an introduction to the histories, theories, and best practices behind effective information visualisations. Beverly, MA: Rockport Publishers.
Meirelles, M. I. (2007). Graphs and problem-solving. In Selected Readings of the 2nd Information Design International Conference. São Paulo: SBDI.
Mohamed, E. A. S., Ali, M. A. O., & Mohamed, M. H. A. (2023). The communicative dimension of graphic design elements-Such as infographics. Brazilian Journal of Science, 2(7), 84-91. https://doi.org/10.14295/bjs.v2i7.283
Murata, A. (2008). Mathematics teaching and learning as a mediating process: The case of tape graphs. Mathematical Thinking and Learning, 10(4), 374-406. https://doi.org/10.1080/10986060802291642
Nejad, M. J. (2016). Undergraduate Students’ Perception of Transformation of Sinusoidal Functions. In J. A. Wood, M., B., Turner, E. E., Civil, M., & Eli (Ed.), Proceedings of the 38th annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 589–596). The University of Arizona.
Nkadimeng, M. P. (2022). Implementation of blended learning in Sekhukhune District schools in Limpopo Province, South Africa (Doctoral dissertation). Polokwane: University of Limpopo.
Parrot, M. A. S.; Leong, K. E. (2018). Impact of using a graphing calculator problem-solving. International Electronic Journal of Mathematics Education, 13(3),139-148. https://doi.org/10.12973/iejme/2704
Patton, M. Q. (2014). Qualitative research & evaluation methods: Integrating theory and practice. Thousand Oaks: Sage publications.
Poch, A. L.; Van Garderen, D.; Scheuermann, A. M. (2015). Students' understanding of graphs for solving word problems: A framework for assessing diagram proficiency. Teaching Exceptional Children, 47(3), 153-162. https://doi.org/10.1177/0040059914558947
Quillin, K., Thomas, S. (2015). Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology. CBE—Life Sciences Education, 14(1), es2. https://doi.org/10.1187/cbe.14-08-0128
Rahman, M.S. (2017). The Advantages and Disadvantages of Using Qualitative and Quantitative Approaches and Methods in Language" Testing and Assessment" Research: A Literature Review. Journal of Education and Learning, 6(1), 102-112. https://doi.org/10.5539/jel.v6n1p102
Rosjanuardi, R., & Jupri, A. (2020). Didactical Design on Drawing and Analysing Trigonometric Functions Graph through a Unit Circle Approach. International Electronic Journal of Mathematics Education, 15(3). https://doi.org/10.29333/iejme/9275
Scalise, K., & Clarke‐Midura, J. (2018). The many faces of scientific inquiry: Effectively measuring what students do and not only what they say. Journal of Research in Science Teaching, 55(10), 1469-1496. https://doi.org/10.1002/tea.21464
Schneider, M.; Rode, C.; Stern, E. (2010). Secondary school learners' availability and activation of graphical strategies for learning from texts. London: Routledge.
Slutsky, D. J. (2014). The effective use of graphs. Journal of Wrist Surgery, 3(2), 67-68. https://doi.org/10.1055/s-0034-1375704
Stake, R. E. (1995). The art of case study research. Thousand Oaks: Sage publications.
Steenpaß, A. & Steinbring, H. (2014). Young learners' subjective interpretations of mathematical graphs: elements of the theoretical construct "frame-based interpreting competence". ZDM: The International Journal of Mathematics Education, 46(1), 3-14. https://doi.org/10.1007/s11858-013-0544-0
Stylianou, D. A. (2011). An examination of middle school learners' representation practices in mathematical problem solving through the lens of expert work: Towards an organizing scheme. Educational Studies in Mathematics, 76(3), 265-280. https://doi.org/10.1007/s10649-010-9273-2
Uesaka, Y.; Manalo, E.; Ichikawa, S. I. (2017). What kinds of perceptions and daily learning behaviours promote learners' use of graphs in mathematics problem-solving? Learning and Instruction, 17(3), 322-335. https://doi.org/10.1016/j.learninstruc.2007.02.006
Van Garderen, D.; Scheuermann, A.; Poch, A. (2014). Challenges students identified with a learning disability and as high-achieving experience when using diagrams as a visualization tool to solve mathematics word problems. ZDM, 46(1), 135-149. https://doi.org/10.1007/s11858-013-0519-1
Wulandari, N. D., Cholily, Y. M., & Azmi, R. D. (2020). Analysis of Students' Mathematic Ability in using Open Ended Teaching Materials on Class VIII Function Relations Materials. Mathematic Education Journal (MEJ), 4(2), 194-204. https://doi.org/10.22219/mej.v4i2.12834
Yusrina, M. L., Inganah, S., & Putri, O. R. U. (2020). Analysis Of The Level Of Understanding Concepts And Critical Thinking Ability Of Students In Resolving Trigonomic Equations Using Graphs. Mathematics Education Journal, 4(1), 71-85. https://doi.org/10.22219/mej.v4i1.11472
Zhang, D., Indyk, A., & Greenstein, S. (2021). Effects of schematic chunking on enhancing geometry performance in students with math difficulties and students at risk of math failure. Learning Disability Quarterly, 44(2), 82-95. https://doi.org/10.1177/0731948720902400
Zhang, Y.; Wildemuth, B. M. (2016). Qualitative analysis of content. Applications of social research methods to questions in information and library science, 318-330. 2016
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