Deep Learning as Constructed in Mathematics Teachers’ Written Discourses

Janne Fauskanger; Raymond Bjuland

doi:10.12973/iejme/2705

Full Text (PDF)

Janne Fauskanger ¹ ^* , Raymond Bjuland ¹

More Detail

¹ Department of Education and Sports Science, University of Stavanger, Stavanger, NORWAY^* Corresponding Author

Abstract

This study explores the notion of deep learning as constructed in the discourses of practicing mathematics teachers. Analyses of data from written texts show that the teachers tend to conceptualise deep learning in terms of two broad categories: students’ deep learning and the work of teaching for deep learning. In both categories, students’ previous knowledge or background knowledge, students’ thinking and their understanding, interdisciplinarity and relations to daily life are emphasised. Related to the work of mathematics teaching for deep learning, variation in mediating tools, variation in approaches to teaching, the learning objective for a lesson and the importance of applying knowledge are emphasised. Possible implications from these findings are discussed.

Keywords

deep learning
mathematics teachers’ discourse
teachers’ views

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

INT ELECT J MATH ED, 2018, Volume 13, Issue 3, 149-160

https://doi.org/10.12973/iejme/2705

Publication date: 20 Jul 2018

Article Views: 3684

Article Downloads: 2931

Open Access References How to cite this article

References

Alexander, R. (2008). Towards dialogic teaching: rethinking classroom talk (4th Ed.). York: Dialogos.
Bjuland, R., & Jaworski, B. (2009). Teachers’ perspectives on collaboration with didacticians to create an inquiry community. Research in Mathematics Education, 11(1), 21–38. https://doi.org/10.1080/14794800902732209
Bransford, J. D, Brown, A. L, & Cocking, R. R. (2000/2004) (Expanded Edition). How people learn: Brain, mind, experience, and school. Washington, DC: National Academic Press.
Byrne, M., Flood, B., & Willis, P. (2004). Validation of the approaches and study skills inventory for students (assist) using accounting students in the USA and Ireland: a research note. Accounting Education, 13(4), 449–459. https://doi.org/10.1080/0963928042000306792
Dahlin, B., & Watkins, D. (2000). The role of repetition in the processes of memorizing and understanding: A comparison of the views of German and Chinese secondary school students in Hong Kong. British Journal of Educational Psychology, 70, 65–84. https://doi.org/10.1348/000709900157976
de Jong, T., & Ferguson-Hessler, M. (1996). Types and qualities of knowledge. Educational Psychologist, 31(2), 105–113. https://doi.org/10.1207/s15326985ep3102_2
Fan, L., & Bokhove, C. (2014). Rethinking the role of algorithms in school mathematics: a conceptual model with focus on cognitive development. ZDM – The International Journal on Mathematics Education, 46(3), 481–492. https://doi.org/10.1007/s11858-014-0590-2
Fauskanger, J., & Mosvold, R. (2014). Innholdsanalysens muligheter i utdanningsforskning. [The affordances of content analysis in educational research]. Norsk Pedagogisk Tidsskrift, 98(2), 127–139.
Fullan, M. (2013). Great to excellent: Launching the next stage of Ontario’s education agenda. Retrieved from http://www.michaelfullan.ca/wp-content/uploads/2013/09/13_Fullan_Great-to-Excellent.pdf
Fullan, M., & Langworthy, M. (2014). A rich seam: How new pedagogies find deep learning. London: Pearson.
Grossman, P., Compton, C., Igra, D., Ronfeldt, M., Shahan, E., & Williamson, P. (2009). Teaching practice: A cross-professional perspective. Teachers College Record, 111(9), 2055–2100.
Hemmi, K., & Ryve, A. (2015). Effective mathematics teaching in Finnish and Swedish teacher education discourses. Journal of Mathematics Teacher Education, 18, 501–521. https://doi.org/10.1007/s10857-014-9293-4
Hiebert, J., & Carpenter, T. P. (1992). Learning and teaching with understanding. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning: A project of the National Council of Teachers of Mathematics (pp. 65–97). New York, NY: Macmillan Publishing Co, Inc.
Hiebert, J., & Lefevre, P. (1986). Conceptual and procedural knowledge in mathematics: An introductory analysis. In J. Hiebert (Ed.), Conceptual and procedural knowledge: The case of mathematics (pp. 1–27). Hillsdale, NJ: Erlbaum.
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
Lampert, M., Beasley, H., Ghousseini, H., Kazemi, E., & Franke, M. (2010). Using designed instructional activities to enable novices to manage ambitious mathematics teaching. In M. K. Stein & L. Kucan (Eds.), Instructional explanations in the disciplines (pp. 129–141). New York, NY: Springer. https://doi.org/10.1007/978-1-4419-0594-9_9
Leung, F. K. S. (2006). Mathematics education in East Asia and the West: does culture matter? In F. K. S. Leung, K.-D. Graf & F. J. Lopez-Real (Eds.), Mathematics education in different cultural traditions: A comparative study of East Asia and the West (pp. 21–46). New York: Springer. https://doi.org/10.1007/0-387-29723-5_1
Li, S. (1999). Does practice make perfect? For the Learning of Mathematics, 19(3), 33–35.
Marton, F. (1975). On non-verbatim learning 1. level of processing and level of outcome. Scandinavian Journal of Psychology, 16(1), 273–279. https://doi.org/10.1111/j.1467-9450.1975.tb00193.x
Marton, F., & Säljö, R. (1976). On qualitative differences in learning: I––Outcome and process. British Journal of Educational Psychology, 46(1), 4–11. https://doi.org/10.1111/j.2044-8279.1976.tb02980.x
Marton, F., Dall’Alba, G., & Tse, K. -T. (1996). Memorising and understanding: the keys to the paradox? In D. Watkins & J. B. Biggs (Eds.), The Chinese learner: Cultural, psychological, and contextual influences (pp. 69–83). Hong Kong: Comparative Education Research Centre; and Melbourne: Australian Council for Educational Research.
NOU (2015:8). Fremtidens skole. Fornyelse av fag og kompetanser [The school for the future. The renewal of subjects and competences]. Oslo: Kunnskapsdepartementet.
Rillero, P. (2016). Deep conceptual learning in science and mathematics: Perspectives of teachers and administrators. Electronic Journal of Science Education, 20(2), 14–31.
Rittle-Johnson, B., & Siegler, R. S. (1998). The relation between conceptual and procedural knowledge in learning mathematics: A review. In C. Donlan (Ed.), The development of mathematical skill (pp. 75–110). Hove, UK: Psychology Press.
Rittle-Johnson, B., Siegler, R. S., & Alibali, M. W. (2001). Developing conceptual understanding and procedural skill in mathematics: An iterative process. Journal of Educational Psychology, 93(2), 346–362. https://doi.org/10.1037/0022-0663.93.2.346
Sawyer, R. K. (2014, Eds.). The Cambridge handbook of the learning sciences. Cambridge: Cambridge University Press.
Schoenfeld, A. H. (2007). Problem solving in the United States, 1970–2008: Research and theory, practice and politics. ZDM – The International Journal on Mathematics Education, 39(5–6), 537–551. https://doi.org/10.1007/s11858-007-0038-z
Skemp, R. R. (1976). Relational understanding and instrumental understanding. Mathematics Teaching, 77, 20–26.
Star, J. R. (2005). Reconceptualizing procedural knowledge. Journal for Research in Mathematics Education, 36(5), 404–411.
Tchoshanov, M. A. (2011). Relationship between teacher knowledge of concepts and connections, teaching practice, and student achievement in middle grades mathematics. Educational Studies in Mathematics, 76(2), 141–164. https://doi.org/10.1007/s10649-010-9269-y
Zeichner, K. (2012). The turn once again toward practice-based teacher education. Journal of Teacher Education, 63(5), 376–382. https://doi.org/10.1177/0022487112445789

How to cite this article

APA

Fauskanger, J., & Bjuland, R. (2018). Deep Learning as Constructed in Mathematics Teachers’ Written Discourses. International Electronic Journal of Mathematics Education, 13(3), 149-160. https://doi.org/10.12973/iejme/2705

Vancouver

Fauskanger J, Bjuland R. Deep Learning as Constructed in Mathematics Teachers’ Written Discourses. INT ELECT J MATH ED. 2018;13(3):149-60. https://doi.org/10.12973/iejme/2705

AMA

Fauskanger J, Bjuland R. Deep Learning as Constructed in Mathematics Teachers’ Written Discourses. INT ELECT J MATH ED. 2018;13(3), 149-160. https://doi.org/10.12973/iejme/2705

Chicago

Fauskanger, Janne, and Raymond Bjuland. "Deep Learning as Constructed in Mathematics Teachers’ Written Discourses". International Electronic Journal of Mathematics Education 2018 13 no. 3 (2018): 149-160. https://doi.org/10.12973/iejme/2705

Harvard

Fauskanger, J., and Bjuland, R. (2018). Deep Learning as Constructed in Mathematics Teachers’ Written Discourses. International Electronic Journal of Mathematics Education, 13(3), pp. 149-160. https://doi.org/10.12973/iejme/2705

MLA

Fauskanger, Janne et al. "Deep Learning as Constructed in Mathematics Teachers’ Written Discourses". International Electronic Journal of Mathematics Education, vol. 13, no. 3, 2018, pp. 149-160. https://doi.org/10.12973/iejme/2705