Archives
Current issue
About
About us
Aims and Scope
Abstracting and Indexing
Editorial Office
Open Access Policy
Publication Ethics
Journal History
Publisher
Follow us: Twitter
Contact
For Authors
Editorial Policy
Peer Review Policy
Manuscript Preparation Guidelines
Copyright & Licencing
Publication Fees
Fee Waiver Policy for Doctoral Students
EJMSTE Language Editing Service
More
Statistics
Special Issues
Special Issue Announcements
Published Special Issues
RESEARCH PAPER
Analyzing the Impact of Video Representation Complexity on Preservice Teacher Noticing of Children’s Thinking
1
University of Illinois at Chicago, Chicago, Illinois, USA
Publication date: 2018-10-31
EURASIA J. Math., Sci Tech. Ed 2018;14(11):em1650
KEYWORDS
ABSTRACT
Despite the growing research base on preservice teacher noticing of children’s mathematical thinking in video, few, if any studies consider the complex nature of the video representations themselves. Drawing from cognitive load theory, we developed a rubric to code the complexity of the salient teaching and learning events captured in video, and analyzed the relationship between video complexity and preservice teacher (n = 233) noticing. Results indicate that two categories significantly highlight children’s mathematical thinking and two categories significantly mask children’s mathematical thinking for preservice teachers. We discuss the implications of these results for the design of our instructional platform and other video-based learning environments used in preservice teacher education settings.
REFERENCES (40)
1.
Alsawaie, O. N., & Alghazo, I. M. (2010). The effect of video-based approach on prospective teachers’ ability to analyze mathematics teaching. Journal of Mathematics Teacher Education, 13(3), 223-241. https://doi.org/10.1007/s10857....
2.
American Statistical Association. (2007). Using statistics effectively in mathematics education research. Washington, DC: American Statistical Association.
3.
Ball, D., & Cohen, D. (1999). Developing practice, developing practitioners. In L. Darling-Hammond & G. Sykes (Eds.), Teaching as the learning profession (pp. 3-32). San Francisco, CA: Jossey-Bass Publishers.
4.
Ball, D., Thames, M., & Phelps, G. (2008). Content knowledge for teaching: What makes is so special? Journal of Teacher Education, 59, 389-407. https://doi.org/10.1177/002248....
5.
Blomberg, G., Sturmer, K., & Seidel, T. (2011). How pre-service teachers observe teaching on video: Effects of viewers’ teaching subjects and the subject of the video. Teaching and Teacher Education, 27, 1131-1140. https://doi.org/10.1016/j.tate....
6.
Brophy, J. (2004). Using video in teacher education. New York, NY: Emerald Group Publishing.
7.
Castro Superfine, A., Fisher, A., Bragelman, J., & Amador, J. (2017). Shifting perspectives on preservice teachers’ noticing of children’s thinking. In E. Schack, M. Fisher, & J. Wilhem (Eds.), Teacher Noticing: Bridging and Broadening Perspectives, Contexts and Frameworks (pp. 409-426). Springer International Publishing.
8.
Castro Superfine, A., Li, W., Bragelman, J., & Fisher, A. (2015). Examining the use of video to support preservice elementary teachers’ noticing of children’s thinking. Journal of Technology and Teacher Education, 23(2), 137-157.
9.
Chamberlin, M. (2005). Teacher discussions of students’ thinking: Meeting the challenge of attending to students’ thinking. Journal of Mathematics Teacher Education, 8(2), 141-170. https://doi.org/10.1007/s10857....
10.
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62(2), 233-246. https://doi.org/10.1111/j.2044....
11.
Fitzmaurice, G. M., Laird, N. M., & Rotnitzky, A. G. (1993). Regression models for discrete longitudinal responses. Statistical Science, 8(3), 284-309. https://doi.org/10.1214/ss/117....
12.
Hatch, T. & Grossman, P. (2009). Learning to look beyond the boundaries of representations: Using technology to examine teaching. Journal of Teacher Education, 60, 70-85. https://doi.org/10.1177/002248....
13.
Homer, B. D., Plass, J. L., & Blake, L. (2008). The effects of video on cognitive load and social presence in multimedia-learning. Computers in Human Behavior, 24, 787-797. https://doi.org/10.1016/j.chb.....
14.
Inan, G., & Wang, L. (2017). PGEE: An R package for analysis of longitudinal data with high-dimensional covariates. The R Journal, 9(1), 393-402.
15.
Jacobs, V. R., Lamb, L. L. C., & Philipp, R. A. (2010). Professional noticing of children’s mathematical thinking. Journal for Research in Mathematics Education, 41(2), 169-202.
16.
Kazemi, E., & Stipek, D. (2001). Promoting conceptual thinking in four upper-elementary mathematics classrooms. The Elementary School Journal, 102(1), 59-80. https://doi.org/10.1086/499693.
17.
Kenward, M. G., Lesaffre, E., & Molenberghs, G. (1994). An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random. Biometrics, 50(4), 945-953. https://doi.org/10.2307/253343....
18.
Lee, H., Plass, J. L., & Homer, B. D. (2006). Optimizing cognitive load for learning from computer-based science simulations. Educational Psychologist, 902-913.
19.
Masats, D. & Dooly, M. (2011). Rethinking the use of video in teacher education: A holistic approach. Teaching and Teacher Education, 27, 1151-1162. https://doi.org/10.1016/j.tate....
20.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43-52. https://doi.org/10.1207/S15326....
21.
Paa, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1-4. https://doi.org/10.1207/S15326....
22.
Pang, J. (2011). Case-based pedagogy for prospective teachers to learn how to teach elementary mathematics in Korea. ZDM Mathematics Education, 43, 777-789. https://doi.org/10.1007/s11858....
24.
Santagata, R., Zannoni, C., & Stigler, J. W. (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....
25.
Sharpe, L., Hu, C., Crawford, L., Gopinathan, S., Khine, M., Moo, S., & Wong, A. (2003). Enhancing multipoint desktop video conferencing (MDVC) with lesson video clips: Recent developments in pre-service teachers practice in Singapore. Teaching and Teacher Education, 19, 529-541. https://doi.org/10.1016/S0742-....
26.
Sherin, M. G., & van Es, E. (2009). Effects of video club participation on teachers’ professional vision. Journal of Teacher Education, 60(1), 20-37. https://doi.org/10.1177/002248....
27.
Sherin, M. G., & van Es, E. A. (2005). Using video to support teachers’ ability to notice classroom interactions. Journal of Technology and Teacher Education, 13, 475-491.
28.
Sherin, M. G., Jacobs, V. R., & Phillip, R. (2011). Mathematics teacher noticing: Seeing through teachers’ eyes. New York, NY: Routledge. https://doi.org/10.4324/978020....
29.
Sherin, M. G., Linsenmeier, K., van Es., E. (2009). Selecting video clips to promote mathematics teachers’ discussion of student thinking. Journal of Teacher Education, 60(3), 213-230. https://doi.org/10.1177/002248....
30.
Star, J. R., & Strickland, S. K. (2008). Learning to observe: Using video to improve preservice teachers’ ability to notice. Journal of Mathematics Teacher Education, 11, 107-125. https://doi.org/10.1007/s10857....
31.
Star, J., Lynch, K., & Perova, N. (2011). Using video to improve preservice mathematics teachers’ abilities to attend to classroom features. In M. G. Sherin, V. Jacobs, & R.
32.
Stein, M. K., Engle, R., Smith, M., & Hughes, E. (2015). Orchestrating productive mathematics discussions: Helping teachers learn to better incorporate student thinking (pp. 375-388). In L. Resnick, C. Asterhan, & S. Clarke (Eds.), Socializing intelligence through academic talk and dialogue. Washington, DC: American Educational Research Association. https://doi.org/10.3102/978-0-....
33.
Stein, M., Smith, M., Henningsen, M., & Silver, E. (2000). Implementing standards-based mathematics instruction. New York, NY: Teachers College Press.
34.
Sweller, J. (2003). Evolution of human cognitive architecture. In B. H. Hoss (Ed.), The psychology of learning and motivation: Advances in research and theory (pp. 216-266). San Diego, CA: Academic Press.
35.
Tekkumru Kisa, M., & Stein, M. K. (2015). Learning to see teaching in new ways: A foundation for maintaining cognitive demand. American Educational Research Journal, 52(1), 105-136. https://doi.org/10.3102/000283....
36.
van Es, E. & Sherin, M. (2008). Mathematics teachers’ “learning to notice” in the context of a video club. Teaching and Teacher Education, 24, 244-276. https://doi.org/10.1016/j.tate....
37.
van Es, E. (2011). A framework for learning to notice student thinking. In M. G. Sherin, V. R. Jacobs, & R. Phillip (Eds.), Mathematics teacher noticing: Seeing through teachers’ eyes (pp. 165-180). New York, NY: Routledge.
38.
van Merriënboer, J. J. G., Kirschner, P. A., & Kester, L. (2003). Taking the load off a learner’s mind: Instructional design for complex learning. Educational Psychologist, 38(1), 5-13. https://doi.org/10.1207/S15326....
39.
Zeger, S. L., & Liang, K. (1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics, 42(1), 121-130. https://doi.org/10.2307/253124....
40.
Zorn, C. J. (2001). Generalized estimating equation models for correlated data: A review with applications. American Journal of Political Science, 45(2), 470-490. https://doi.org/10.2307/266935....
Share
RELATED ARTICLE
| eISSN: | 1305-8223 |
| ISSN: | 1305-8215 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
