The quality of prospective mathematics teachers' dynamic geometry tasks in terms of the coordination between mathematical depth levels and technological actions.

Background: Teachers must have the skills to find, select, design and use technology‐based mathematical activities that focus on high‐level cognitive demands—supporting student reasoning. However, they experience various difficulties in creating, planning and making decisions about how and when to u...

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Detalles Bibliográficos
Publicado en:Journal of Computer Assisted Learning Vol. 40; no. 5; pp. 2261 - 2278
Autores principales: Ulusoy, Fadime, Girit‐Yildiz, Dilek
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell Oct2024
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Background: Teachers must have the skills to find, select, design and use technology‐based mathematical activities that focus on high‐level cognitive demands—supporting student reasoning. However, they experience various difficulties in creating, planning and making decisions about how and when to utilize technological affordances. Objectives: This study aims to examine the quality of prospective school mathematics teachers' (PMTs) tasks containing the use of dynamic geometry software through the analysis of the coordination between mathematical depth levels (MDLs) and technological actions (TAs), according to Trocki and Hollebrands', Digital Experiences in Mathematics Education, 2018, 4, 110–138, Dynamic Geometry Task Analysis Framework. Methods: Within groups, PMTs designed lesson plans that included dynamic geometry tasks (DGTs) based on the learning outcomes of the middle school mathematics curriculum. They then created micro‐teachings of these tasks. The participants' DGTs and transcripts of their microteaching videos were the main data sources. Results: We found that many prompts included no TA or a single TA, regardless of the prompts' MDLs. Moreover, the results showed that the high‐depth prompts aimed to contribute to students' reasoning processes on geometric concepts through the TAs, which required specific tools such as dragging and sliding to get generalizations. Although the groups differed in the quality and number of DGTs, the groups' lesson plans mostly contained low‐ or medium‐quality DGTs regarding the coordination between MDLs and TAs. Conclusions: Informing PMTs about high‐quality technology tasks and increasing their awareness on this matter is a priority to encourage them to incorporate innovative technological activities in their mathematics instruction. Lay Description: What is already known about this topic: The use of dynamic geometry software (DGSs) contents positively affects students' mathematical reasoning skills and motivation towards mathematics.Effective utilization of DGSs is possible through the quality of implementation of teachers' pre‐planned lesson designs. Many mathematics teachers experience various difficulties in creating, planning and making decisions about how and when to utilize DGS tasks.In teacher training processes, examining prospective teachers' lesson plans, including DGS tasks, is a practical way to understand how they will incorporate technology in mathematics teaching processes. What this paper adds: Giving prospective teachers the opportunity to design and present DGS tasks within the scope of the teacher training program is beneficial to improve their understanding of quality DGs tasks that will support mathematical reasoning.To understand the quality of prospective teachers' DGS tasks, it is useful to examine the relation between types of technological actions and mathematical depth levels rather than the frequency of them in the DGS tasks. Implications for practice and/or policy: Analysing prospective mathematics teachers' interventions in real classroom settings to effectively assist students in achieving the desired mathematical learning outcomes in various DGS tasks would be a valuable endeavour.The groups' DGS tasks varied in number and quality levels. Future studies can analyse the effects of a collaborative learning environment by comparing groups' and individuals' DGS task quality.