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

dc.contributor.authorUlusoy, Fadime
dc.contributor.authorGirit‐Yildiz, Dilek
dc.date.accessioned2026-01-04T20:29:13Z
dc.date.issued2024-06-03
dc.description.abstractAbstractBackgroundTeachers 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.ObjectivesThis 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.MethodsWithin 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.ResultsWe 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.ConclusionsInforming 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.
dc.description.urihttps://doi.org/10.1111/jcal.13029
dc.description.urihttps://hdl.handle.net/20.500.14551/28706
dc.identifier.doi10.1111/jcal.13029
dc.identifier.eissn1365-2729
dc.identifier.endpage2277
dc.identifier.issn0266-4909
dc.identifier.openairedoi_dedup___::f4ff0b13e62e59f490ec5219e3b33e11
dc.identifier.orcid0000-0003-3393-8778
dc.identifier.orcid0000-0003-3406-075x
dc.identifier.scopus2-s2.0-85195221154
dc.identifier.startpage2261
dc.identifier.urihttps://hdl.handle.net/20.500.12597/41836
dc.identifier.volume40
dc.identifier.wos001237514200001
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofJournal of Computer Assisted Learning
dc.rightsOPEN
dc.subjectprospective mathematics teacher
dc.subjecttechnological action
dc.subjectmathematical depth
dc.subjecttask design
dc.subjectdynamic geometry software
dc.subject.sdg4. Education
dc.titleThe quality of prospective mathematics teachers' dynamic geometry tasks in terms of the coordination between mathematical depth levels and technological actions
dc.typeArticle
dspace.entity.typePublication
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However, they experience various difficulties in creating, planning and making decisions about how and when to utilize technological affordances.</jats:p></jats:sec><jats:sec><jats:title>Objectives</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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. 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