Transforming Formal Knowledge to Language and Graphs to Promote Learning Math: A Repeated-Measures Mixed-Design Experiment

• In Event: Technology, Instruction, Cognition, and Learning in STEM

Abstract

This longitudinal design-experiment aims to promote mathematical learning in higher education by facilitating students’ mental modeling. A new approach (called NaGra) is used to translate math formalism into natural language. Computer-linguist software is then used to automatically create knowledge maps from these specific texts allowing for the use of two different kinds of additional representations to complement traditional instruction in the field. In a six-point repeated-measures control-group design N=139 math undergraduates received either a) a natural language text, b) a knowledge map, c) both the natural language text and the knowledge map, or d) the traditional instruction by mathematical formalism. Results from nonparametric rank-based longitudinal analysis showed the experimental conditions consistently outperforming the control group regarding math performance over time.

Authors

• Clara Luleich, Martin Luther University Halle Wittenberg

• Inka Hähnlein, Martin Luther University Halle Wittenberg

• Pablo Nicolai Pirnay-Dummer, Martin-Luther-University Halle-Wittenberg

• Philipp Reiter, Martin Luther University Halle Wittenberg

• Nils Waterstraat, Martin Luther University Halle Wittenberg