Skip to main content
Log in

Investigating teachers’ understanding through topic modeling: a promising approach to studying teachers’ knowledge

  • Published:
Journal of Mathematics Teacher Education Aims and scope Submit manuscript

Abstract

Examining teachers’ knowledge on a large scale involves addressing substantial measurement and logistical issues; thus, existing teacher knowledge assessments have mainly consisted of selected-response items because of their ease of scoring. Although open-ended responses could capture a more complex understanding of and provide further insights into teachers’ thinking, scoring these responses is expensive and time consuming, which limits their use in large-scale studies. In this study, we investigated whether a novel statistical approach, topic modeling, could be used to score teachers’ open-ended responses and if so, whether these scores would capture nuances of teachers’ understanding. To test this hypothesis, we used topic modeling to analyze teachers’ responses to a proportional reasoning task and examined the associations of the topics identified through this method with categories identified by a separate qualitative analysis of the same data as well as teachers’ performance on a measure of ratios and proportional relationships. Our findings suggest that topic modeling seemed to capture nuances of teachers’ responses and that such nuances differentiated teachers’ performance on the same concept. We discuss the implications of this study for education research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. Although empirical evidence supporting the role of teachers’ knowledge in student learning is weak, we argue that the weakness of this association is related to several methodological and measurement issues (Copur-Gencturk et al., 2021).

  2. For more details on these studies, see (Copur-Gencturk & Tolar, under review; Charalambous et al., 2020).

  3. A few organizations in the United States maintain databases that contain information about teachers, including such variables as their email addresses, the subjects taught, and the grade level at which they are currently teaching, among others. These companies provide access to this information for a fee.

  4. We have missing background data on two participants.

  5. TF-IDF (term frequency-inverse document frequency) is a statistical measure that evaluates how important a word is to a document in a corpus. This is calculated by using two components: (1) how many times a word appears in a document, and (2) the frequency of the word across a set of documents.

  6. The first author trained another rater, and they coded the responses separately, reaching 97% exact agreement. All responses were coded by two raters.

References

  • Aaronson, D., Barrow, L., & Sander, W. (2007). Teachers and student achievement in the Chicago public high schools. Journal of Labor Economics, 25(1), 95–135.

    Article  Google Scholar 

  • Arun, R., Suresh, V., Madhavan, C. V., & Murthy, M. N. (2010). On finding the natural number of topics with latent Dirichlet allocation: Some observations. In M. J. Zaki, J. X. Yu, B. Ravindran, & V. Pudi (Eds.), Pacific-Asia conference on knowledge discovery and data mining (pp. 391–402). Heidelberg: Springer, Berlin. https://doi.org/10.1007/978-3-642-13657-3_43

    Chapter  Google Scholar 

  • Ball, D. L., Thames, M. H., & Phelps, G. (2008). Content knowledge for teaching: What makes it special? Journal of Teacher Education, 59(5), 389–407.

    Article  Google Scholar 

  • Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., Jordan, A., Klusmann, U., Krauss, S., Neubrand, M., & Tsai, Y. M. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.

    Article  Google Scholar 

  • Beckmann, S. (2017). Mathematics for elementary teachers with activities. Pearson.

    Google Scholar 

  • Begle, E. (1979). Critical variables in mathematics education: Findings from a survey of the empirical literature. Washington, DC: Mathematical Association of America and National Council of Teachers of Mathematics.

  • Ben-Chaim, D., Fey, J. T., Fitzgerald, W. M., Benedetto, C., & Miller, J. (1998). Proportional reasoning among 7th grade students with different curricular experiences. Educational Studies in Mathematics, 36(3), 247–273.

    Article  Google Scholar 

  • Blazar, D. (2015). Effective teaching in elementary mathematics: Identifying classroom practices that support student achievement. Economics of Education Review, 48, 16–29.

    Article  Google Scholar 

  • Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84.

    Article  Google Scholar 

  • Blei, D. M., & McAuliffe, J. D. (2007). Supervised topic models. In Proceedings of the 20th International Conference on Neural Information Processing Systems (pp. 121–128).

  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.

    Google Scholar 

  • Blömeke, S., Houang, R. T., & Suhl, U. (2014). Diagnosing teacher knowledge by applying multidimensional item response theory and multiple-group models. In S. Blömeke, F. J. Hsieh, G. Kaiser, & W. H. Schmidt (Eds.), International perspectives on teacher knowledge, beliefs and opportunities to learn: TEDS-M results (pp. 483–501). Springer.

    Chapter  Google Scholar 

  • Blömeke, S., Busse, A., Kaiser, G., König, J., & Suhl, U. (2016). The relation between content-specific and general teacher knowledge and skills. Teaching and Teacher Education, 56, 35–46.

    Article  Google Scholar 

  • Borko, H., Eisenhart, M., Brown, C. A., Underhill, R. G., Jones, D., & Agard, P. C. (1992). Learning to teach hard mathematics: Do novice teachers and their instructors give up too easily? Journal for Research in Mathematics Education, 23(3), 194–222.

    Article  Google Scholar 

  • Cao, J., Xia, T., Li, J., Zhang, Y., & Tang, S. (2009). A density-based method for adaptive LDA model selection. Neurocomputing, 72(7–9), 1775–1781.

    Article  Google Scholar 

  • Chang, J. (2015). lda: Collapsed gibbs sampling methods for topic models. R package version 1.4.2, URL http://CRAN.R-project.org/package=lda.

  • Charalambous, C. Y., Hill, H. C., Chin, M. J., & McGinn, D. (2020). Mathematical content knowledge and knowledge for teaching: Exploring their distinguishability and contribution to student learning. Journal of Mathematics Teacher Education, 23(6), 579–613.

    Article  Google Scholar 

  • Choi, H.-J., Kwak, M., Kim, S., Xiong, J., Cohen, A. S., & Bottge, B. A. (2019). An application of a topic model to two educational assessments. In M. Wiberg, D. Molenaar, J. González, J.-S. Kim, & H. Hwang (Eds.), Quantitative psychology: The 85th annual meeting of the psychometric society (pp. 449–459).

  • Copur-Gencturk, Y. (2015). The effects of changes in mathematical knowledge on teaching: A longitudinal study of teachers' knowledge and instruction. Journal for Research in Mathematics Education, 46(3), 280–330.

  • Copur-Gencturk, Y. (2021a). Teachers’ conceptual understanding of fraction operations: Results from a national sample of elementary school teachers. Educational Studies in Mathematics, 1–21.

  • Copur-Gencturk, Y. (2021b). Teachers’ knowledge of fraction magnitude. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-021-10173-2

  • Copur-Gencturk, Y., & Doleck, T. (2021). Strategic competence for multistep fraction word problems: An overlooked aspect of mathematical knowledge for teaching. Educational Studies in Mathematics, 107(1), 49–70.

  • Copur-Gencturk, Y., & Ölmez, İ. B. (2021). Teachers’ attention to and flexibility with referent units. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-021-10186-x

  • Copur-Gencturk, Y., & Thacker, I. (2021). A comparison of perceived and observed learning from professional development: Relationships among self-reports, direct assessments, and teacher characteristics. Journal of Teacher Education, 72(2), 138–151. https://doi.org/10.1177/0022487119899101

  • Copur-Gencturk, Y., & Tolar T. (conditionally accepted). The content-specific knowledge base for teaching: A study on the dimensionality of mathematical knowledge for teaching.

  • Copur-Gencturk Y., Baek, C., & Doleck, T. (conditionally accepted). A closer look at teacher’s proportional reasoning.

  • Copur-Gencturk, Y., Plowman, D., & Bai, H. (2019). Mathematics teachers’ learning: Identifying key learning opportunities linked to teachers’ knowledge growth. American Educational Research Journal, 56(5), 1590–1628. https://doi.org/10.3102/0002831218820033

  • Copur-Gencturk, Y., Jacobson, E., & Rasiej, R. (2021). On the alignment of teachers’ mathematical content knowledge assessments with the common core state standards. Journal of Mathematics Teacher Education, 1–25.

  • Copur-Gencturk, Y., Tolar, T., Jacobson, E., & Fan, W. (2019). An empirical study of the dimensionality of the mathematical knowledge for teaching construct. Journal of Teacher Education, 70(5), 485–497. https://doi.org/10.1177/0022487118761860

  • Cramer, K., & Post, T. (1993). Making connections: A case for proportionality. The Arithmetic Teacher, 40(6), 342–346.

    Article  Google Scholar 

  • Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), 391–407.

    Article  Google Scholar 

  • DTAMS (2020). DTAMS home. https://louisville.edu/education/centers/crimsted/dtams

  • Gordon, R. J., Kane, T. J., & Staiger, D. (2006). Identifying effective teachers using performance on the job. DC: Brookings Institution Washington.

    Google Scholar 

  • Goulding, M., Rowland, T., & Barber, P. (2002). Does it matter? Primary teacher trainees’ subject knowledge in mathematics. British Educational Research Journal, 28(5), 689–704.

    Article  Google Scholar 

  • Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(suppl 1), 5228–5235. https://doi.org/10.1073/pnas.0307752101

    Article  Google Scholar 

  • Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate press releases. Political Analysis, 18, 1–35.

    Article  Google Scholar 

  • Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42(2), 371–406.

    Article  Google Scholar 

  • Hill, H. C., Blunk, M. L., Charalambous, C. Y., Lewis, J. M., Phelps, G. C., Sleep, L., & Ball, D. L. (2008a). Mathematical knowledge for teaching and the mathematical quality of instruction: An exploratory study. Cognition and Instruction, 26(4), 430–511.

    Article  Google Scholar 

  • Hill, H. C., Ball, D. L., & Schilling, S. G. (2008b). Unpacking pedagogical content knowledge: Conceptualizing and measuring teachers’ topic-specific knowledge of students. Journal for Research in Mathematics Education, 39(4), 372–400.

    Article  Google Scholar 

  • Hong, M., Choi, H-J., Mardones-Segovia, C.A., Copur-Gencturk, Y., & Cohen, A.S. (2022). A two-step approach to topic modeling incorporating covariates and outcomes. In M. Wiberg, D. Molenaar, J. González, J.-S. Kim, & H. Hwang (Eds.), Quantitative psychology: The 85th annual meeting of the psychometric society.

  • Izsák, A., & Jacobson, E. (2017). Preservice teachers’ reasoning about relationships that are and are not proportional: A Knowledge-in-Pieces Account. Journal for Research in Mathematics Education, 48(3), 300–339.

    Article  Google Scholar 

  • Kane, T. J., McCaffrey, D. F., Miller, T., & Staiger, D. O. (2013). Have we identified effective teachers? Validating measures of effective teaching using random assignment. Research paper. MET project. Bill & Melinda Gates Foundation.

  • Kersting, N. B., Givvin, K. B., Thompson, B. J., Santagata, R., & Stigler, J. W. (2012). Measuring usable knowledge teachers’ analyses of mathematics classroom videos predict teaching quality and student learning. American Educational Research Journal, 49(3), 568–589.

    Article  Google Scholar 

  • Kim, S., Kwak, M., Cardozo-Gaibisso, L. A., Buxton, C. A., & Cohen, A. S. (2017). Statistical and qualitative analyses of students’ answers to a constructed response test of science inquiry knowledge. Journal of Writing Analytics, 1, 82–102.

    Article  Google Scholar 

  • Kleickmann, T., Richter, D., Kunter, M., Elsner, J., Besser, M., Krauss, S., Cheo, M., & Baumert, J. (2015). Content knowledge and pedagogical content knowledge in Taiwanese and German mathematics teachers. Teaching and Teacher Education, 46, 115–126.

    Article  Google Scholar 

  • Krauss, S., Brunner, M., Kunter, M., Baumert, J., Blum, W., Neubrand, M., & Jordan, A. (2008). Pedagogical content knowledge and content knowledge of secondary mathematics teachers. Journal of Educational Psychology, 100(3), 716.

    Article  Google Scholar 

  • Kwak, M., Kim, S., & Cohen, A. S. (2017). Latent Dirichlet analysis of text constructed response answers. Paper presented at the 4th annual Writing Analytics Conference, St. Petersburg, FL.

  • Lamon, S. (1993). Ratio and proportion: Connecting content and children’s thinking. Journal for Research in Mathematics Education, 24(1), 41. https://doi.org/10.2307/749385

    Article  Google Scholar 

  • Lane, S., & Stone, C. A. (2006). Performance testing. In R. L. Brennan (Ed.), Educational measurement (4th ed.). American Council on Education.

    Google Scholar 

  • Lau, J. H., Collier, N., & Baldwin, T. (2012). On-line trend analysis with topic models:# twitter trends detection topic model online. Proceedings of COLING, 2012, 1519–1534.

    Google Scholar 

  • Lauderdale, B. E., & Clark, T. S. (2014). Scaling politically meaningful dimensions using texts and votes. American Journal of Political Science, 58, 754–771.

    Article  Google Scholar 

  • Learning Mathematics for Teaching. (2020). LMT Project. http://www.umich.edu/~lmtweb/.

  • Mardones Segovia, C. A., Wheeler, J. M., Choi, H. -J., & Cohen, A. S. (2021). Model selection for latent Dirichlet allocation with small numbers of topics. Paper presented at the Annual Meeting of the National Council on Measurement in Education, virtual conference.

  • Misailidou, C., & Williams, J. (2003). Diagnostic assessment of children’s proportional reasoning. The Journal of Mathematical Behavior, 22(3), 335–368. https://doi.org/10.1016/s0732-3123(03)00025-7

    Article  Google Scholar 

  • Monk, D. (1994). Subject area preparation of secondary mathematics and science teachers and student achievement. Economics of Education Review, 13(2), 125–145.

    Article  Google Scholar 

  • Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user’s guide. Eighth Edition. Los Angeles, CA: Muthén & Muthén.

  • National Governors Association Center for Best Practices & Council of Chief State School Officers. (2010). Common core state standards for mathematics. Washington, DC: Authors.

    Google Scholar 

  • National Research Council. (2001). Adding it up: Helping children learn mathematics. Washington, DC: National Academy Press.

    Google Scholar 

  • Nye, B., Konstantopoulos, S., & Hedges, L. (2004). How large are teacher effects? Educational Evaluation and Policy Analysis, 26(3), 237–257.

    Article  Google Scholar 

  • Ottmar, E. R., Rimm-Kaufman, S. E., Larsen, R. A., & Berry, R. Q. (2015). Mathematical knowledge for teaching, standards-based mathematics teaching practices, and student achievement in the context of the responsive classroom approach. American Educational Research Journal, 52(4), 787–821.

    Article  Google Scholar 

  • Parish, L. (2010). Facilitating the development of proportional reasoning through teaching ratio. Mathematics education research group of Australasia.

  • Ramesh, A., Goldwasser, D., Huang, B., Daume III, H., & Getoor, L. (2014). Understanding MOOC discussion forums using seeded LDA. In Proceedings of 9th workshop on innovative use of NLP for building educational applications. 28–33.

  • Rhody, L. (2012). Topic modeling and figurative language. Journal of Digital Humanities, 2(1), 19–35.

    Google Scholar 

  • Rockoff, J. E., Jacob, B. A., Kane, T. J., & Staiger, D. O. (2011). Can you recognize an effective teacher when you recruit one? Education, 6(1), 43–74.

    Google Scholar 

  • Schoenfeld, A. H. (2015). Summative and formative assessments in mathematics supporting the goals of the common core standards. Theory into Practice, 54(3), 183–194.

    Article  Google Scholar 

  • Schofield, A., Magnusson, M., & Mimno, D. (2017). Understanding text pre-processing for latent Dirichlet allocation. In Proceedings of the 15th conference of the European chapter of the Association for Computational Linguistics (Vol. 2, pp. 432–436).

  • Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(5), 4–14.

    Article  Google Scholar 

  • Tatto, M. T., Schwille, J., Senk, S., Ingvarson, L., Peck, R., & Rowley, G. (2008). Teacher education and development study in mathematics (TEDS-M): Policy, practice, and readiness to teach primary and secondary mathematics. Conceptual framework. East Lansing, MI: Teacher education and development international study center, college of education, Michigan state university. Retrieved from https://msu.edu/user/mttatto/documents/TEDS_FrameworkFinal.pdf

  • Tatto, M. T. (2013). The teacher education and development study in mathematics (TEDS-M): Policy, practice, and readiness to teach primary and secondary mathematics in 17 countries. Technical report. International association for the evaluation of educational achievement. Herengracht 487, Amsterdam, 1017 BT, The Netherlands.

  • Van de Walle, J. A., Karp, K. S., Bay-Williams, J. M., & Wray, J. (2010). Elementary and middle school mathematics: Teaching developmentally. Boston, MA: Pearson.

  • Van Dooren, W., De Bock, D., Hessels, A., Janssens, D., & Verschaffel, L. (2005). Not everything is proportional: Effects of age and problem type on propensities for overgeneralization. Cognition and Instruction, 23(1), 57–86. https://doi.org/10.1207/s1532690xci2301_3

    Article  Google Scholar 

  • Wheeler, J. M., Cohen, A. S., Xiong, J., Lee, J., & Choi, H. -J. (2020). Sample size for latent Dirichlet allocation of constructed-response items. In M. Wiberg, S. Culpepper, R. Janssen, J. González, & D. Molenaar (Eds.), Quantitative psychology: The 85th annual meeting of the psychometric society (pp. 263–274).

  • Xiong, J., Choi, H. -J., Kim, S., Kwak, M., & Cohen, A. S. (2019). Topic modeling of constructed-response answers on social study assessments. In M. Wiberg, S. Culpepper, R. Janssen, J. González, & D. Molenaar (Eds.), Quantitative psychology: The 85th annual meeting of the psychometric society (pp. 263–274).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yasemin Copur-Gencturk.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Ratios and proportional relationships assessment

Tasks

A photograph is enlarged to make a poster. The photograph is 10 cm wide and 16 cm high

View full size image

The poster is 25 cm wide, how high is the poster? Explain your answer

If 6 ml of paint was needed for the original photograph, how much paint will be needed for the enlarged photo? Explain your answer

Raymond wanted to know the cost of buying different numbers of songs for his MP3 player. The cost of each song is the same. Let s represent the possible number of songs Raymond could buy Let d represent the amount of money, in dollars, Raymond would need to buy the songs. Fill in the table for all missing values of s and d

Number of songs

s

Amount of money ($)

d

2

2.50

 

5.00

7

 
 

22.50

Yasmin went to the store to buy a new purse. The purse she wanted was on sale for 40% off the original price, and the salesperson offered her an additional discount of 15% off the sale price. The salesperson told Yasmin that this was a great deal and that she was getting a discount of 55% off the original price. Do you agree with the salesperson? Please explain.

A recipe requires \(\frac{1}{4}\) cups of flour for every \(\frac{1}{3}{ }\) batch of cookies. How many batches of cookies can be made with \({5}\frac{1}{2}\) cups of flour? Explain how you solved the problem.

This graph shows the relationship between the number of gallons of gasoline used (g) and the total cost of gasoline (c).

View full size image

1. How much money will be paid if 12 gallons of gasoline are used?

2. Write an equation to find the cost for any given amount of gasoline used. Explain how you found the equation.

Of following word problems, which represent equivalent ratios? Select all that represent equivalent ratios.

If a men paint the outside of a house in b minutes, then how many minutes d would it take c men to paint the same house, if all the men work at the same rate?

A leaky faucet was dripping water into a bucket. There was already some water in the bucket before Latika started collecting data. She found that there were a ounces of water in the bucket after b minutes. How many ounces of water c will be in the bucket after d minutes?

Bob and Marty run laps together because they run at the same pace. Today, Marty started running before Bob came out of the locker room. Marty had run a laps by the time Bob had run b laps. How many laps c had Marty run by the time that Bob had run d laps?

Explain your reasoning.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Copur-Gencturk, Y., Choi, HJ. & Cohen, A. Investigating teachers’ understanding through topic modeling: a promising approach to studying teachers’ knowledge. J Math Teacher Educ 26, 281–302 (2023). https://doi.org/10.1007/s10857-021-09529-w

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10857-021-09529-w

Keywords

Navigation