Enhancing economics education through phenomenography, variation theory, and multiple representations

Nurudeen Babatunde Bamiro, Lagos State University, Ojo, Nigeria
Zainizam Zakariya, Universiti Pendidikan Sultan Idris, Malaysia
Lateefat Oludare Yahya, Lagos State University, Nigeria
Abidat Oluwashola Mohammed, Lagos State University, Nigeria

Abstract


This study explores the intersection between phenomenography and variation theory in educational settings, focusing on their implications for teaching economics. Phenomenography, a research approach aimed at understanding how individuals perceive and conceptualize phenomena, provides insights into learners' diverse interpretations of concepts. Variation theory, derived from phenomenography, guides instructional design by emphasizing the importance of experiencing variations in critical aspects of the learning material. The study investigates whether employing multiple representations enhances knowledge transfer, learning outcomes, and concept variation. The findings suggest that integrating variation theory into economics classrooms can optimize students' understanding by directing attention to critical aspects of concepts through varied instructional strategies.


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Adu, E. O., Galloway, O., & Olaoye, B. C. (2014). Introduction to social studies: A basic text for tertiary institution students. Educational Research and Study Group, Ibadan, Nigeria.

Ainsworth, S. (1999). The functions of multiple representations. Computers & education, 33(2-3), 131-152.

Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16, 183–198

Ainsworth, S., & Van Labeke, N. (2004). Multiple forms of dynamic representation. Learning and Instruction, 14, 241–255.

Airey, J., & Linder, C. (2006). Language and the experience of learning university physics in Sweden. European journal of physics, 27(3), 553.

Åkerlind, G. (2015). From phenomenography to variation theory: A review of the development of the variation theory of learning and implications for pedagogical design in higher education. HERDSA Review of Higher Education, 2, 5-26.

Assan, T. T. E. B. (2011). Exploring Learner Understanding of Economic and Management Sciences’(Ems) Concepts Through Variation of Learning Theory: Classroom Experiences. Problems of Education in the 21st Century, 29(1), 7-21.

Assan, T.E.B. (2009). Educators’ Classroom Experiences with Variation of Learning Theory. Problems of Education in the 21st Century, 18(8).

Ayene, M., Kriek, J., & Damtie, B. (2011). Wave-particle duality and uncertainty principle: Phenomenographic categories of description of tertiary physics students’ depictions. Physical Review Special Topics-Physics Education Research, 7(2), 020113.

Booth, S. (2008). Researching learning in networked learning: Phenomenography and variation theory as empirical and theoretical approaches. In Proceedings of the 6th international conference on networked learning (pp. 450-455).

Bowden, J., & Marton, F. (1998). The University of Learning: Beyond Quality and Competence (1st ed.). Routledge. https://doi.org/10.4324/9780203416457

Bowden, J., & Walsh, E. (Eds.) (1994). Phenomenographic research: Variations in method. Melbourne: RMIT University Press.

Bowden, J., & Walsh, E. (Eds.) (2000). Phenomenography. Melbourne: RMIT University Press

Cifuentes-Faura, J., Faura-Martínez, U., & Lafuente-Lechuga, M. (2020). Assessment of sustainable development in secondary school economics students according to gender. Sustainability, 12(13), 5353.

Demirbağ, M., & Günel, M. (2014). Argümantasyon Tabanlı fen eğitimi sürecine modsal betimleme entegrasyonunun akademik başarı, argüman kurma ve yazma becerilerine etkisi [Integrating Argument-Based Science Inquiry with Modal Representations: Impact on Science Achievement, Argumentation, and Writing Skills]. Kuram ve Uygulamada Eğitim Bilimleri, 14, 373-392.

Disessa, A. A. (2004). Metarepresentation: Native competence and targets for

Federal Republic of Nigeria, (2004). National Policy on Education. Lagos: Federal Government Press.

Gero, J. S., & Reffat, R. M. (1997). Multiple representations for situated agent–based learning. In B. Varma, B. & X. Yao (Eds.), Proceeding of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA–97) (pp. 81–85). Gold Coast: Griffith University.

Gunel, M., Hand, B., & Gunduz, S. (2006). Comparing student understanding of quantum physics when embedding multimodal representations into two different writing formats: Presentation format versus summary report format. Science Education, 90(6), 1092-1112.

Hahn, K., & Kim, K. M. (2010). Issues and Challenges for Secondary School Economics Education in South Korea: implications from five events since 2004. Citizenship, Social and Economics Education, 9(1), 60-68.

Hand, B., & Choi, A. (2010). Examining the impact of student use of multiple modal representations in constructing arguments in organic chemistry laboratory classes. Research in Science Education, 40, 29-44.

instruction. Cognition and instruction, 22(3), 293-331.

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.

Keller, J.M. (1987). Development and use of the ARCS model of instructional design,” Journal of Instructional Development, (10)3, 2-10.

Lemke, J. (1990). Talking science: Language, learning and values. Norwood, NJ: Ablex Publishing.

Lo, M.L. (2012). Variation Theory and the Improvement of Teaching and Learning. Gothenburg studies in educational sciences, 323.

Marton, F. & Booth, S., (1997). Learning and Awareness, Lawrence Erlbaum, Mahwah, New Jersey

Marton, F. & Pang, M.F., (2006), ‘On some necessary conditions of learning’. The Journal of the Learning Sciences, vol. 15, pp. 193-220.

Marton, F. (1975). On non‐verbatim learning: 1. Level of processing and level of outcome. Scandinavian Journal of Psychology, 16(1), 273-279.

Marton, F. (1981). Phenomenography—describing conceptions of the world around us. Instructional science, 10(2), 177-200.

Marton, F., & Morris, P. J. T. F. (2002). What matters? In What matters? Discovering critical conditions of classroom learning (pp. 133-143). Acta Universitatis Gothoburgensis.

Marton, F., Runesson, U., & Tsui, A. B. (2004). The space of learning. In Classroom discourse and the space of learning (pp. 3-40). Routledge.

Marton, F., Tsui, A. B., Chik, P. P., Ko, P. Y., & Lo, M. L. (2004). Classroom discourse and the space of learning. Routledge.

Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational psychologist, 32(1), 1-19.

Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional design methods across different media. Learning and instruction, 13(2), 125-139.

McDermott, M. A. (2009). The impact of embedding multiple modes of representation on student construction of chemistry knowledge. The University of Iowa.

McKibben, E., & Breheny, M. (2023). Making sense of making sense of time: Longitudinal narrative research. International Journal of Qualitative Methods, 22, 16094069231160928.

Meltzer, D. E. (2005). Relation between students’ problem-solving performance and representational format. American journal of physics, 73(5), 463-478.

Meyer, J. H., & Land, R. (2006). Threshold concepts and troublesome knowledge: An introduction. In Overcoming barriers to student understanding (pp. 3-18). Routledge.

Okeke, A. O., & Ezewulu, A. U. (2021). Challenges and prospects of economics education in Nigerian school. UNIZIK Journal of Educational Research and Policy Studies, 2, 242-246.

Olaleye, F. O. (2011). Teachers’ characteristics as predictor of academic performance of students in secondary schools in Osun State –Nigeria. European Journal of Educational Studies 3(3).

Pang, M. F., & Marton, F. (2005). Learning theory as teaching resource: Enhancing students’ understanding of economic concepts. Instructional science, 33, 159-191.

Parks, P. (2023). Story circles: A new method of narrative research. American Journal of Qualitative Research, 7(1), 58-72.

Pineda, L., & Garza, G. (2000). A model for multimodal reference resolution. Computational Linguistics, 26(2), 139-193.

Prain, V., & Waldrip, B. (2006). An exploratory study of teachers’ and students’ use of multi‐modal representations of concepts in primary science. International Journal of Science Education, 28(15), 1843-1866.

Richardson, J. (1999). "The concept and methods of phenomenographic research. Review of Educational Research 69(1): 53-83.

Rohaan, E.J., Taconis, R & Jochems, W.M.G. (2009). Measuring teachers’ pedagogical content knowledge in primary technology education. Research in Science & Technological Education Vol. 27, No. 3, November 2009, 327–338.

Sabbaghan, S. (2015). The affordances of variation theory (new phenomenography) in enhancing eal students’ learning. In Preciado Babb, Marton, F., Runnesson, U., and Tsiu, B. M. A., The space of learning, In Marton, F. and Tsiu B. M. A., editors, Classroom Discourse and the Space of Learning, Lawrence Erlbaum Associates, pp 3-40, 2004.

Schnotz, W. (2002). Towards an integrated view of learning from text and visual displays. Educational Psychology Review, 14(1), 101–120.

Schnotz, W., & Lowe, R. (2003). External and internal representations in multimedia learning. Learning and Instruction, 13, 117–123.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.

Tang, K., Delgado, C., & Moje, E. B. (2014). An integrative framework for the analysis of multiple and multimodal representations for meaning-making in science education. Science Education, 98(2), 305–326.

Ting, D. S. W., Cheung, C. Y. L., Lim, G., Tan, G. S. W., Quang, N. D., Gan, A., ... & Wong, T. Y. (2017). Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. Jama, 318(22), 2211-2223.

Umo J.U. (1986). Economics; An African Perspectives. Johnwest, Lagos Nigeria.

Waldrip B. & V. Prain. (2013). “Teachers’ Initial Response to A Representational Focus”, by Tytler, R, Prain, V, Hubber, P &Waldrip, B in Teachers’ Initial Response to A Representational Focus. (Sense Publisher, 2013).

Waldrip, B., Rodie, F., & Sutopo, S. (2014). The implications of culture for teachers’ use of representations. Science teachers’ use of visual representations, 171-193.

Yeşildağ Hasançebi, F., & Günel, M. (2013). College students’ perceptions toward the multi modal representations and instruction of representations in learning modern Physics. Egitim Arastirmalari-Eurasian Journal of Educational Research, 53, 197-214.

Yore, L. D., & Treagust, D. F. (2006). Current realities and future possibilities: Language and science literacy—empowering research and informing instruction. International Journal of Science Education, 28(2-3), 291-314.




DOI: https://doi.org/10.21831/jptk.v30i2.72900

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