Using general-mathematical and content-specific elements to assess the quality of prospective mathematics teachers' problems in a problem-posing context.

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Title: Using general-mathematical and content-specific elements to assess the quality of prospective mathematics teachers' problems in a problem-posing context.
Authors: Ulusoy, Fadime1 (AUTHOR) fadimebayik@gmail.com
Source: Journal of Mathematics Teacher Education. Jun2026, Vol. 29 Issue 3, p497-529. 33p.
Subject Terms: *Mathematics teachers, *Pedagogical content knowledge, *Evaluation methodology, *Mathematics education
Abstract: The open-ended nature of problem-posing tasks causes a serious diversity in learners' responses. This diversity presents a variety of difficulties in assessing the quality of the problems posed. This study aimed to assess the quality of problems that prospective mathematics teachers' (PMTs) posed about linear graphs through a combination of general-mathematical and content-specific elements. Additionally, this study concentrated on the PMTs' declarations about their difficulties in posing problems on linear graphs. In this study, the data sources were PMTs' problems, their own solutions to them, and reflection papers. The results revealed that integrating general-mathematical and content-specific elements in assessing the quality of problems provided a better understanding of PMTs' problem posing performances. In terms of general-mathematical elements, posed problems were mostly solvable, situated in a real-world context, and linguistically precise. However, the problems mostly failed to reflect content-specific elements related to key mathematical ideas about linear graphs. Moreover, the results showed that the mean score for general-mathematical elements was significantly higher than the mean score for content-specific elements in the problems. In their written explanations, PMTs also said that task-related components (like prompts and situations) and teacher-related components (like lack of experience, weakness in subject knowledge, and pedagogical content knowledge) made it challenging for them to pose problems about linear graphs. It was concluded that the inclusion of both general-mathematical and content-specific elements in evaluating the quality of the posed problems paves the way for future empirical and theoretical studies that seek to develop a systematic approach to problem assessment. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Mathematics Teacher Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Using general-mathematical and content-specific elements to assess the quality of prospective mathematics teachers' problems in a problem-posing context.
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  Data: <searchLink fieldCode="AR" term="%22Ulusoy%2C+Fadime%22">Ulusoy, Fadime</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> fadimebayik@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Mathematics+Teacher+Education%22">Journal of Mathematics Teacher Education</searchLink>. Jun2026, Vol. 29 Issue 3, p497-529. 33p.
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  Data: *<searchLink fieldCode="DE" term="%22Mathematics+teachers%22">Mathematics teachers</searchLink><br />*<searchLink fieldCode="DE" term="%22Pedagogical+content+knowledge%22">Pedagogical content knowledge</searchLink><br />*<searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematics+education%22">Mathematics education</searchLink>
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  Label: Abstract
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  Data: The open-ended nature of problem-posing tasks causes a serious diversity in learners' responses. This diversity presents a variety of difficulties in assessing the quality of the problems posed. This study aimed to assess the quality of problems that prospective mathematics teachers' (PMTs) posed about linear graphs through a combination of general-mathematical and content-specific elements. Additionally, this study concentrated on the PMTs' declarations about their difficulties in posing problems on linear graphs. In this study, the data sources were PMTs' problems, their own solutions to them, and reflection papers. The results revealed that integrating general-mathematical and content-specific elements in assessing the quality of problems provided a better understanding of PMTs' problem posing performances. In terms of general-mathematical elements, posed problems were mostly solvable, situated in a real-world context, and linguistically precise. However, the problems mostly failed to reflect content-specific elements related to key mathematical ideas about linear graphs. Moreover, the results showed that the mean score for general-mathematical elements was significantly higher than the mean score for content-specific elements in the problems. In their written explanations, PMTs also said that task-related components (like prompts and situations) and teacher-related components (like lack of experience, weakness in subject knowledge, and pedagogical content knowledge) made it challenging for them to pose problems about linear graphs. It was concluded that the inclusion of both general-mathematical and content-specific elements in evaluating the quality of the posed problems paves the way for future empirical and theoretical studies that seek to develop a systematic approach to problem assessment. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Mathematics Teacher Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10857-025-09697-z
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        Text: English
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      – SubjectFull: Evaluation methodology
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              Text: Jun2026
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