Inhalt des Dokuments
Modelling and Prediction of Mental Calculation Strategies
Location: Zoom link (Please ask Steven Schmidt for access)
Date/Time: 12.04.2021, 14:00-14:30
SPEAKER: Anke Wiebke Jensen (TU Berlin)
Abstract: Many areas of everyday life need mental arithmetic. When verifying discounts in the supermarket or calculating points of a university exam, mental arithmetic itself or in combination with written arithmetic is of great importance. In scientific studies, mental arithmetic tasks are used, for example, to induce mental workload or to examine it. Assessment centers use mental arithmetic tasks to test applicant’s mathematical abilities and concentration skills. Important in these areas is the evaluability of the task regarding its difficulty or complexity in order to be able to evaluate and compare the tasks or the results retrospectively. Comparability of mathematical tasks is not easy. The difficulty of a task depends on its complexity and the abilities of the person performing it. This work aims to identify the mental processes engaged with solving mental arithmetic tasks. The goal is to model and describe all strategies that people use to solve a mathematic task. With this description, respectively model a better overview about the mental processes should be provided. For this purpose, interviews are conducted in which individuals describe how they perform mental arithmetic. Existing literature on mental arithmetic and mental arithmetic strategies has been analyzed and collected. The mental arithmetic strategies are decomposed into defined steps to create a universal framework of describing methods in an algorithmically approachable way. From the results, computational models are developed that describe and list the possible mental arithmetic strategies and the derived steps per task. The developed models provide a list of all mental arithmetic strategies (and their variations) for any given task, including the required number of steps. These lists allow to examine and compare mathematical tasks concerning their complexity.