Research suggests that using technology in mathematics education help gain insight and intuition, discover relationships, make conjectures and suggest approaches for formal proofs (Borwein and Bailey, 2003). However, many teachers believe that providing technology is not enough to use it effectively in their classrooms (Cuban, Kirkpatrick & Peck, 2001). As Koehler and Mishra (2005) emphasize teachers need to have Technological Pedagogical Content Knowledge (TPCK), which requires technology integration into pedagogical and content knowledge. Research shows that in teaching and learning geometry and solving problems related to geometry concepts dynamic geometry is the most appropriate tool (Kokol-Voljc, 2007). Geogebra is one of the dynamic software tools that combine both algebra and geometry and Cabri 3D is another dynamic software tool used for 3D shapes. This study focuses on two preservice teachers who took dynamic geometry course during Fall 2012 semester. During this course, preservice teachers learned how to use Geogebra and Cabri 3D as well as different hands-on manipulative in the solution of geometry problems from different topics.  

As stated earlier, it is important to know how to use dynamic geometry tools effectively. However, there is a lack of literature that investigates the relationship between preferences of the student and the use of a technological tool (Harskamp, Suhre & Van Streun, 2000; Yerushalmy, 2006). Nonetheless, it is important to understand how visual/nonvisual preferences of teachers affect their use of dynamic software. In this way, educators can support the difficulties of these teachers in the courses once they were categorized using the instruments from the literature. In this study, preservice teachers’ were categorized by using Suwarsono’s (1982) Mathematical Processing Instrument (MPI) to determine students’ preferences for being visual or nonvisual. According to Swarsono (1982) visual methods involve visual imagery, whereas non-visual methods are devoid of imagery. He defines imagery as representations either on the paper or in the mind.

During data analysis, Krutetskii’s (1976) framework is used. According to him, students can be categorized as analytic, geometric, and harmonic thinkers. He defined these categories by comparing students’ verbal logical and visual-pictorial components of mathematical abilities. Thus, whether these thinking styles affect the use of dynamic software is an important question.

In this study, once the students’ preferences were categorized based on Suwarsono’s instrument, their problem solving strategies with Geoebra and Cabri 3D in the classroom were compared to each other. Additionally, during the course the preservice teachers were asked to select two geometric topics for their individual and group presentations. In the analysis, these presentations were used in order to investigate how they used the dynamic software in the solution of the geometric problem that they found from the curriculum or other sources.

Borwein, J. M. & Bailey, D. H. (2003). Mathematics by experiment: Plausible reasoning in the 21st Century. Natick, MA: AK Peters. Cuban, L., Kirkpatrick, H.,& Peck C. (2001). High access and low use of technologies in high school classrooms: Explaining an apparent paradox. American Educational Research Journal, 38(4), 813-834. Harskamp, E. Suhre, C. & Van Streun, A. (2000). The graphics calculator and students‘ solution strategies. Mathematics Education Research Journal, 12(1), 37-52. Koehler, M.J. & Mishra, P. (2005). What happens when teachers design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2) 131-152. Kokol-Voljc, V. (2007) Use of mathematical software in pre-service teacher training: The case of GeoGebra. Proceedings of the British Society for Research into Learning Mathematics, 27(3), 55-60. Krutetskii, V. A. (1976). The Psychology of Mathematical Abilities in Schoolchildren. In J. Kilpatrick & I. Wirszup (Eds.). Chicago: The University of Chicago Press. Suwarsono, S. (1982). Visual imagery in the mathematical thinking of seventh-grade students. Unpublished doctoral dissertation, Monash University Yerushalmy, M. (2006). Slower algebra students meet faster tools: Solving algebra word problems with graphing software. Journal for Research in Mathematics Education, 37(5), 356-387.