This paper is from Session 8G: Theoretical frameworks in statistics education research

which comes under Topic 8: Research in statistics education

About central issues of mental model theory in context of learning statistics

Presenter

• Markus Vogel (University of Education Heidelberg, Germany)

Co-author

• Andreas Eichler (University of Kassel, Germany)

Abstract

Learning to draw right conclusions and to make well-founded decisions on base of data is a goal being at the core of statistics education. Because of its central characteristics and underlying concepts the theory of mental model is well suited for describing and reflecting on these processes of statistics learning in two respects: On the one hand the concepts of structure and function of mental model theory allow for adequately capturing data-based situations which require drawing conclusions. On the other hand the concept of mental model is an essential part of widely accepted information processing theories which are currently at the forefront of research. Thus, students’ processing of data-based problem situations and making decisions can be highlighted in terms of this theoretical approach. Beside a survey of fundamentals of mental model theory the presentation focuses on these aspects. Theoretical insights will be underlined by empirical research results.