Fostering Mathematics Teachers for a New Era

A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Teacher Education".

Deadline for manuscript submissions: closed (1 May 2024) | Viewed by 4718

Special Issue Editors


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Guest Editor
Instituto de Educação, Universidade de Lisboa, 1649-013 Lisbon, Portugal
Interests: teacher knowledge; teacher professional development; lesson study; mathematical reasoning

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Guest Editor
Werklund School of Education, University of Calgary, Calgary, AB T2N 1N4, Canada
Interests: teacher knowledge; teacher professional development; problem-solving
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Special Issue Information

Dear Colleagues,

Society is evolving at an ever-increasing pace, experiencing profound changes. Children and young people use digital technologies for entertainment, for reaching contacts on social networks, and have free access to powerful tools such as ChatGPT. Migratory and demographic movements have dramatically altered the living conditions of social groups around the world. Climate change and pollution, as well as the defense of social rights and the escalation of conflicts between countries, pose serious challenges to our survival as a human species. All of this requires a response on the part of the school, with a change in the teacher–student relationship, in the nature of classes and other learning activities, in teaching methodologies and in assessment. The discipline of mathematics, with a central place in all educational systems, has an unavoidable responsibility to reflect on these issues and find ways to face them. In the era we are entering, what will be the role of the discipline of mathematics? How will teaching and learning take place? This Special Issue aims to contribute to the debate on this topic. Reasoned essay articles and empirical articles with relevant studies will be published, hopefully reflecting a variety of viewpoints and authors from different parts of the world.

Prof. Dr. Joao Pedro Da Ponte
Prof. Dr. Olive Chapman
Guest Editors

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Keywords

  • teacher knowledge
  • teacher professional development
  • lesson study
  • mathematical reasoning
  • problem solving

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Published Papers (2 papers)

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Research

16 pages, 1410 KiB  
Article
Professional Support in Teaching Mathematics through Guided Discovery: The Role of Agency on Multiple Levels
by Péter Juhász, Réka Szász, Gábor Szűcs and Eszter Varga
Educ. Sci. 2024, 14(7), 769; https://doi.org/10.3390/educsci14070769 - 15 Jul 2024
Viewed by 975
Abstract
The paper describes a case study of mentoring support provided to a novice mathematics teacher in using Guided Discovery in her classroom. The study used qualitative methods: thematic analysis of interviews and discussions. A central theme that emerged in the results was agency, [...] Read more.
The paper describes a case study of mentoring support provided to a novice mathematics teacher in using Guided Discovery in her classroom. The study used qualitative methods: thematic analysis of interviews and discussions. A central theme that emerged in the results was agency, and we observed that the high level of student and teacher agency in Guided Discovery results in the importance of teacher agency within and over the mentoring framework. We conclude that when supporting teachers in using Guided Discovery in their mathematics classrooms, teacher educators need to put an increased focus on teacher agency within and over the mentoring process. Full article
(This article belongs to the Special Issue Fostering Mathematics Teachers for a New Era)
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41 pages, 6995 KiB  
Article
Mathematical Modelling Abilities of Artificial Intelligence Tools: The Case of ChatGPT
by Carina Spreitzer, Oliver Straser, Stefan Zehetmeier and Katja Maaß
Educ. Sci. 2024, 14(7), 698; https://doi.org/10.3390/educsci14070698 - 26 Jun 2024
Viewed by 2712
Abstract
This work explores the mathematical modelling capabilities of various iterations of ChatGPT, focusing on their performance across tasks of differing complexity and openness. The study examines the abilities of GPT-3.5, GPT-4.0, and a more instructed version, GPT-MM, in multiple scenarios. It is observed [...] Read more.
This work explores the mathematical modelling capabilities of various iterations of ChatGPT, focusing on their performance across tasks of differing complexity and openness. The study examines the abilities of GPT-3.5, GPT-4.0, and a more instructed version, GPT-MM, in multiple scenarios. It is observed that all versions demonstrate basic mathematical problem-solving skills. However, their effectiveness varies with increasing task complexity. While GPT-4.0 and GPT-MM show marginal improvements in providing detailed solutions, significant challenges persist, especially in moderate to complex modelling contexts where comprehending the nuances of tasks becomes challenging. Additionally, the study suggests that the openness of modelling tasks has a limited impact on performance, highlighting that mathematical and contextual complexities play more critical roles. The implications of these observations are discussed in terms of potential enhancements to teaching methodologies and the integration of AI tools like GPT in educational settings. This reiterates the importance of further research to fully understand the capabilities and limitations of AI tools and ensure their effective use in education. Full article
(This article belongs to the Special Issue Fostering Mathematics Teachers for a New Era)
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