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<p>Although there has been considerable research on the use of technology in mathematics education, little is known about how it supports or hinders the development of crucial mathematical concepts, such as functions. This study explores the factors behind creating graphs of functions that accurately reflect mathematical concepts using a modeling problem from a Hungarian eighth-grade textbook. We specifically examine the meta-representational aspect of graphing proficiency—the ability to interpret and construct graphs based on deep mathematical understanding. The research involved 53 Hungarian pre-service mathematics teachers to understand how different technological tools influence their solutions to this modeling problem, particularly their representational competence and pedagogical reasoning. Results suggest that while technology can aid in different function representations, it does not negate the need for a strong mathematical background, as evidenced by common misconceptions about continuity and overuse of linearity in our study. This study advocates for a balanced approach that fosters technological proficiency and deep mathematical understanding.</p>

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Beyond Tools: How Technology Shapes Graphing and Pedagogical Reasoning in Mathematics Teacher Education

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月30日

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  • Zoltán Kovács,
  • Ilona Téglási

摘要

Although there has been considerable research on the use of technology in mathematics education, little is known about how it supports or hinders the development of crucial mathematical concepts, such as functions. This study explores the factors behind creating graphs of functions that accurately reflect mathematical concepts using a modeling problem from a Hungarian eighth-grade textbook. We specifically examine the meta-representational aspect of graphing proficiency—the ability to interpret and construct graphs based on deep mathematical understanding. The research involved 53 Hungarian pre-service mathematics teachers to understand how different technological tools influence their solutions to this modeling problem, particularly their representational competence and pedagogical reasoning. Results suggest that while technology can aid in different function representations, it does not negate the need for a strong mathematical background, as evidenced by common misconceptions about continuity and overuse of linearity in our study. This study advocates for a balanced approach that fosters technological proficiency and deep mathematical understanding.