Cognitive Load in Data-driven Non-expert Decision Making: How Do Different Types of Data Presentation Impact Non-experts’ Ability to Make Expert-like Decisions?

Ulyana Khoma & Csaba Vendel Póti

Student thesis: Master thesis

Abstract

As the rapid technological advancement shape our world, the importance of data and its transformation into information and knowledge through Business Intelligence or various other data analysis tools has become a widely researched area (KMPG, 2018; Wu, 2000; Niu et. al., 2009). However, only a few researchers chose the perspective of decision making, more specifically, the role of humans in the data-driven decision-making process. According Kahneman’s (2003) theory of the dual process thinking system, human beings do not behave rationally. Using System 2 requires cognitive effort, the volume of which is determined by the individual’s domain specific knowledge according to cognitive load theory by John Sweller (1988). Overall less experience in a domain could lead to higher cognitive load, which would then result in a lower decision quality. The focus of this research is to investigate this process and to further understand how to help novices understand data and make decisions based on it like experts would. The aim is to find specific practices in the presentation of data, which can be used by companies to help data novices, to understand data and enhance their learning processes by reducing their cognitive load in the Business Intelligence setting

EducationsMSc in Business Administration and E-business, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2019
Number of pages108
SupervisorsRob Gleasure