254
Views
0
CrossRef citations to date
0
Altmetric
Original Articles

Learning algebra through motion: An examination of pre-service teachers’ misconceptions when using motion detectors for the first time

&
Pages 44-55 | Published online: 02 Oct 2017
 

ABSTRACT

Elementary pre-service teachers in an upper-division algebra mathematics content course explored graphing through the use of Calculator-Based Rangers™ (CBRs). This study explores how they used the Distance Match feature of the technology to engage in algebraic thinking. Operating CBR technology, pre-service teachers’ perceptions regarding how position/time graphs represent algebraic concepts was explored with an emphasis on physical movement. Using an inductive approach for qualitative data, the pre-service teachers’ reflections regarding the use of CBRs were analyzed. Specifically, patterns and structures were discovered through coding of the pre-service teachers’ raw descriptions of their movements. Using the data sources (a reflection and assignment), the results showed increased understanding and beneficial affordances with the use of CBRs. However, the pre-service teachers failed to connect the graphs thoroughly to numeric representations and described slope only superficially. For example, movement was not contextualized using numbers but rather using verbal descriptions. Implications are provided for the integration of CBRs as tools for enhancing pre-service teachers’ knowledge for teaching mathematics with technologies.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 88.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.