International Journal of Mathematical Education in Science and Technology

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International Journal of Mathematical Education in Science and Technology

Rethinking what is valuable in mathematics and statistics education

The current rapid development of generative AI is creating an existential crisis in mathematics and statistics education similar to the one in which the electronic calculator replaced the slide rule and logarithm tables. If everything that we teach in undergraduate mathematics and statistics can be done by the average smartphone, then why are we teaching it? As a part of a larger study into educators' opinions on how mathematics and statistics should be taught and assessed, we asked them what students should gain from their studies in the subject. In this paper we use thematic analysis to analyse the responses. Four primary themes emerged from the interview data, namely content mastery, mathematical thinking, mathematical communication and appreciation of mathematics and statistics. Content mastery was divided into two sub-themes of computational mastery and conceptual understanding. These are discussed in light of the development of generative AI and the current practices of teaching mathematics and statistics. We suggest a refocusing of mathematics and statistics education to place more explicit emphasis on the conceptual and higher thinking aspects of courses and begin a discussion of how this could be achieved within the time constraints faced by educators.

One. Introduction

Two. Purpose of the study

Three. Methodology

Four. Educator and subject profiles

Five. Thematic analysis

Six. Emergent themes

Six point two. Mathematical thinking

Six point three. Mathematical communication

Six point four. Appreciation of the discipline

Six point five. Other objectives raised by educators

Seven. Discussion

Seven point two. Valuable skills in an AI world

Seven point three. Computational skills

Seven point four. Rethinking the relationship between computational mastery and conceptual understanding

Seven point five. Study limitations

Eight. Conclusion

Disclosure statement

Data availability statement

Overview

The paper analyzes educators' perspectives on the future of mathematics and statistics education amidst the rise of generative AI, suggesting a shift towards emphasizing conceptual understanding and higher-order thinking. It is based on a thematic analysis of interviews with mathematics and statistics educators across various institutions.

Key Points

1Generative AI challenges traditional methods of teaching mathematics and statistics
2Educators emphasize the significance of content mastery and mathematical thinking
3There is a need for a shift towards conceptual understanding in the curriculum
4The paper identifies four primary themes from educator interviews regarding educational priorities
5Future curricula should adapt to technological advancements while fostering critical thinking skills.

Details

Authors: Merryn Horrocks, Don Shearman
Category: Education

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