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http://dx.doi.org/10.7468/mathedu.2022.61.4.559

Changes in mathematics pedagogical lexicons: Extension research of the International Classroom Lexicon using a text mining approach  

Lee, Gima (Korea University)
Kim, Hee-jeong (Korea University)
Publication Information
The Mathematical Education / v.61, no.4, 2022 , pp. 559-579 More about this Journal
Abstract
Research on lexicon and language provides insights into the interests, values and practices of a community where individuals use the language. The International Classroom Lexicon Project, in which ten countries participated, identified own country's mathematics teaching and learning lexicons by investigating mathematics classroom instruction from teachers' perspectives in a speaking-oriented community. This study, as an extension of the International Classroom Lexicon Project research, investigated pedagogical lexicons used in 「Mathematics and Education」 journals specialized for Korean professional mathematics teachers published by the Korean Society of Teachers of Mathematics. Using the text mining approach, we also traced how these pedegogical lexicons have changed quantitatively over the past 10 years with a diachronic perspective. As a results, several novel terms were found in the writing-oriented community, which were not identified in the speaking-oriented community. In addition, we could discover some pedagogical lexicons have increased statistically significantly and some lexicons appeared(increased) rapidly across years. This implies the teacher community's values and zeitgeist by reflecting these changes in the sociocultural, incidental and social changing (i.e., periodical change) contexts. This study has value as a first step in understanding zeitgeist for mathematics education in Korean mathematics teacher community according to changes of times over the past 10 years. Also, this study contributes to the methodological insights: the text mining technique provides a methodological contribution to researching changes in interests, values and zeitgeist according to these changes in the times.
Keywords
The International Classroom Lexion Project; Korean pedagogical lexicons; text mining; Word2Vec; social change; zeitgeist;
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1 Aiden, E., & Michel, J. (2013). Uncharted: Big data as a lens on human culture. Riverhood Books.
2 Cho, H. M., & Kim, H. J. (2018). The international classroom lexicon project: A study on the pedagogical lexicons survey in the Korean mathematics classroom. School Mathematics, 23(3), 463-481. ttps://doi.org/10.29275/sm.2018.09.20.3.463   DOI
3 Cole, M., & Engestrom, Y. (1993). A cultural historical approach to distributed cognition. In G. Salomon (Eds.), Distributed Cognitions: Psychological and Educational Considerations (pp. 1-46). Cambridge University Press.
4 Han, C. R., Kim, H. J., & Kwon, O. N. (2018). Teacher noticing on students' reasoning of statistical variability. Journal of the Korean School Mathematics, 21(2), 183-206. https://doi.org/10.30807/ksms.2018.21.2.005   DOI
5 Kang, H. S., & Yang, J. H. (2019). Analyzing semantic relations of word vectors trained by the Word2vec model. Journal of KIISE, 46(10), 1088-1093. https://doi.org/10.5626/JOK.2019.46.10.1088   DOI
6 Kim, H. J. (2022). Pre-service mathematics teachers' noticing competency: Focusing on teaching for robust understanding of mathematics. The Mathematical Education, 61(2), 339-357. https://doi.org/10.7468/mathedu.2022.61.2.339   DOI
7 Kim, H. J. (2020). Teacher planning sessions as professional opportunities to learn: An elementary mathematics teacher's re-conceptualization of instructional triangles. International Journal of Science and Mathematics Education, 18, 1207-1227. https://doi.org/10.1007/s10763-019-10019-y   DOI
8 Boroditsky, L. (2001). Does language shape thought?: Mandarin and English speakers' conception of time. Cognitive Psychology, 43(1), 1-22. https://doi.org/10.1006/cogp.2001.0748   DOI
9 Casasanto, D. (2008). Who's afraid of the big bad whorf? Crosslinguistic differences in temporal language and thought. Language Learning, 58, 63-79. https://doi.org/10.1111/j.1467-9922.2008.00462.x   DOI
10 Cho, H. M., & Kim, H. J. (2021). What do pre-service teachers and in-service teachers see from Korean mathematics classroom?: International classroom lexicon project. Journal of the Korean School Mathematics, 24(1), 107-126. https://doi.org/10.30807/ksms.2021.24.1.006   DOI
11 Levinson, S. C. (2003). Space in language and cognition: Explorations in cognitive diversity. Cambridge University Press. https://doi.org/10.1017/CBO9780511613609   DOI
12 Vygotsky, L. S. (1987). Thinking and speech. In R. W. Rieber, & A. S. Carton (Eds.), The collected works of Lev Vygotsky (Vol. 1): Problems of General Psychology (pp. 39-285). Plenum Press. (Original Work Published 1934)
13 Kim, H. j., & Cho, H. M. (2021b). Korean lexicon. In C. Mesiti, M. Artigue, H. Hollingsworth, Y. Cao, & D. J. Clarke (Eds.), Teachers talking about their classrooms: Learning from the Professional lexicons of mathematics teachers around the world (pp. 298-332). Routledge.
14 Kim, M. H. (2004). A study on the characteristics of spoken and written Korean. Korean Language Research, (15), 23-73.
15 Lee, H. J., & Kim, H. J. (2022). Learning from noticing: Elementary mathematics preservice teachers' noticing and responsiveness on lesson modification. Educational Studies. https://doi.org/10.1080/03055698.2022.2031893   DOI
16 Lee, K. H. (2010). Searching for Korean perspective on mathematics education through discussion on mathematical modeling. Journal of Educational Research in Mathematics, 20(3), 221-239.
17 Mesiti, C., Artigue, M., Hollingsworth, H., Cao, Y., & Clarke, D. J. (2021). Teachers talking about their classrooms: Learning from the Professional lexicons of mathematics teachers around the world. Routledge. https://doi.org/10.4324/9780429355622   DOI
18 Michel, J. B., Shen, Y. K., Aiden, A. P., Veres, A., Gray, M. K., Pickett, J. P., Hoiberg, D., Clancy, D., Norvig, P., Orwant, J., Pinker, S., Nowak, M. A., & Aiden, E. L. (2011). Quantitative analysis of culture using millions of digitized books. Science, 331(6014), 176-182. https://doi.org/10.1126/science.1199644   DOI
19 Choi, J. A., & Kwak, M. H. (2019). Topic changes in mathematics educational research based on LDA. Journal of Education & Culture, 25(5), 1149-1176. https://doi.org/10.24159/joec.2019.25.5.1149   DOI
20 Kim, H. J., & Cho, H. M. (2021a). Identifying and documenting Korean middle school mathematics classroom practices. In C. Mesiti, M. Artigue, H. Hollingsworth, Y. Cao, & D. J. Clarke (Eds.), Teachers Talking about Their Classrooms: Learning from the Professional Lexicons of Mathematics Teachers around the World (pp. 285-297). Routledge.
21 Dobie, T. E., & Sherin, M. G. (2020). What's in a name? Language use as a mirror into your teaching practice. Mathematics Teacher: Learning and Teaching Pre K-12, 113(5), 354-360. https://doi.org/10.5951/mtlt.2019.0296   DOI
22 Hwang, H. S., Lee, C. K., Jang, H. K., & Kang, D. H. (2018). Word embedding using relative position information between words. Journal of KIISE, 45(9), 943-949. https://doi.org/10.5626/JOK.2018.45.9.943   DOI
23 Dobie, T. E., & Sherin, B. (2021). The language of mathematics teaching: A text mining approach to explore the zeitgeist of US mathematics education. Educational Studies In mathematics, 107, 159-188. https://doi.org/10.1007/s10649-020-10019-8   DOI
24 Han, C. R., Kim, H. j., Kwon, O. N., & Lim, W. (2022). Exploring changes of mathematics teachers' noticing in a video club: Identifying turning points. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-022-10251-z   DOI
25 Hong, J. H., & Kim, M. J. (2018). How do changes in word frequencies over time in newspaper corpora reflect social concerns? Language Information, 0(27), 5-29. https://doi.org/10.35128/rili.2018.27.1   DOI
26 Hwang, J. N., & Pang, J. S. (2020). An analysis of domestic and international research trends of mathematical reasoning through topic modeling. The Journal of educational research in mathematics, 30(4), 625-648. https://doi.org/10.29275/jerm.2020.11.30.4.625   DOI
27 Huh, J. Y. (2018). Korean language clustering technique using Word2Vec. The Journal of The Institute of Internet, Broadcasting and Communication, 18(5), 25-30. https://doi.org/10.7236/JIIBC.2018.18.5.25   DOI
28 Seoul Metropolitan Office of Education. (2018). Policies and practices of hyukshin schools in seoul: selected writings. Seoul Metropolitan Office of Education.
29 Santagata, R., Zannoni, C., & Stigler, J. (2007). The role of lesson analysis in pre-service teacher education: An empirical investigation of teacher learning from a virtual video-based field experience. Journal of Mathematics Teacher Education, 10(2), 123-140. https:doi.org/10.1007/s10857-007-9029-9   DOI
30 Sapir, E. (1949). Selected writings of Edward Sapir in language, culture and personality (G. David, Eds.). University of California Press.
31 Son, W. J. (2012). Learning communities. Haenaem Publish.
32 Shin, D. J. (2020). A comparative study of domestic and international research trends of mathematics education through topic modeling. The Mathematical Education, 59(1), 63-80. https://doi.org/10.7468/mathedu.2020.59.1.63   DOI
33 Milewski, A., & Strickland, S. (2016). (Toward) Developing a common language for describing instructional practices of responding: A teachergenerated framework. Mathematics Teacher Educator, 4(2),126-144. https://doi.org/10.5951/mathteaceduc.4.2.0126   DOI
34 Mesiti, C., Artigue, M., Grau, V., & Novatna, J. (2022). Towards an international lexicon. ZDM-Mathematics Education, 54, 239-255. https://doi.org/10.1007/s11858-022-01349-3   DOI
35 Roh, D. K. (1996). Korean Oral and Written Language. Kukhak Archive.
36 Sarkar, D. (2016). Text analytics with python: A practical real-world approach to gaining actionable insights from your data. Apress.
37 Jin, M. R., & Ko, H. K. (2019). Analysis of trends in mathematics education research using text mining. Communications of Mathematical Education, 33(3), 275-294. https://doi.org/10.7468/jksmee.2019.33.3.275   DOI
38 Son, T. K., & Hwang, S. H. (2020). An analysis of domestic and international research trends of assessment in mathematics education using topic modeling. The Journal of Educational Research in Mathematics, 30(4), 601-624. https://doi.org/10.29275/jerm.2020.11.30.4.601   DOI
39 Son, T. K., & Hwang, S. H. (2021). Analysis of the research trends of domestic elementary mathematics education using topic modeling. Journal of Elementary Mathematics Education in Korea, 25(1), 61-80.
40 Son, B. Y., & Ko, H. K. (2018). The frequency analysis of teacher's emotional response in mathematics class. Communications of Mathematical Education, 32(4), 555-573. https://doi.org/10.7468/jksmee.2018.32.4.555   DOI
41 Sung, Y. K., & Lee, Y. M. (2018). Politics and the practice of school change: The hyukshin school movement in South Korea. Curriculum Inquiry, 48(2), 238-252. https://doi.org/10.1080/03626784.2018.1435976   DOI
42 Yoon, T. Y., & Lee, S. A. (2018). Analyzing text using python. Neulbom.
43 Sun, H. S., Lee, Y. S., & Lim, C. W. (2021). Understanding the semantic change of Hangeul using word embedding. The Korean Journal of Applied Statistics, 34(3), 295-308. https://doi.org/10.5351/KJAS.2021.34.3.295   DOI
44 Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4   DOI
45 Son, T. K., & Lee, K. H. (2020). An analysis of domestic research trends of mathematics curriculum research through topic modeling: Focused on domestic journals published from 1997 to 2019. The Mathematical Education, 59(3), 201-216. https://doi.org/10.7468/mathedu.2020.59.3.201   DOI
46 Stigler, J. W., & Hiebert, J. (1999). The teaching gap: Best ideas from the world's teachers for improving education in the classroom. The Free Press.
47 Silber-Varod, V., Eshet-Alkalai, Y., & Geri, N. (2016). Culturomics: Reflections on the potential of big data discourse analysis methods for identifying research trends. The Online Journal of Applied Knowledge Management, 4(1). 82-98. https://doi.org/10.36965/OJAKM.2016.4(1)82-98   DOI