Andreas Eichler

Professor

University of Kassel

Germany

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About

Andreas Eichler is a Professor at the University of Kassel in Germany. His research focuses on Bayesian reasoning, covariational reasoning, and the development of diagnostic competencies in prospective mathematics teachers. He has published numerous articles exploring the intersections of teaching methodologies and teacher beliefs in mathematics education.

Articles (17)

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2025

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2025

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2024

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2023

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2023

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2023

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2020

Collaborators (3)

Stefan Krauss

University of Regensburg

GERMANY

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Karin Binder

Professor

LMU Munich

GERMANY

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Günter Törner

Universität Duisburg-Essen

GERMANY

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Andreas Eichler

Research Interests

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About

Articles (17)

On students’ covariational reasoning in Bayesian situations: do calculation strategies and visualizations play a role?

How to teach Bayesian reasoning: An empirical study comparing four different probability training courses

Covariational reasoning in Bayesian situations

Measuring changes in mathematics teachers' belief systems

Das Beurteilen von Lernprodukten als Facette diagnostischer Kompetenz fördern

Improving Prospective Teachers’ Beliefs About a Double Discontinuity Between School Mathematics and University Mathematics

Measuring people’s covariational reasoning in Bayesian situations

Fostering diagnostic competence in prospective mathematics elementary teachers through epistemic activities

Development of Prospective Elementary Teachers´ Beliefs About Mathematics During Their First Semester at University, and the Impact of Inquiry-Based Tasks

Cultural values and prospective teachers’ beliefs about success in mathematics and in its teaching

Measuring changes in mathematics teachers' belief systems

Designing Visualisations for Bayesian Problems According to Multimedia Principles

Developing Prospective Teachers’ Beliefs about Digital Tools and Digital Feedback

How to Train Novices in Bayesian Reasoning

Changing between representations of elementary functions: students’ competencies and differences with a specific perspective on school track and gender

Investigating Motivational and Cognitive Factors which Impact the Success of Engineering Students

Different Visualizations Cause Different Strategies When Dealing With Bayesian Situations

Collaborators (3)

Stefan Krauss

Karin Binder

Günter Törner

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