Paper Title
Optimizing Dashboards Effectiveness using Learning Styles Theories

Abstract
The amount of data is increasing in an astonishing rate. However, managers at all levels are not concerned with the quantity of data, rather they are constantly searching for relevant high quality and meaningful information that can help them make high quality decision at the minimum cost and at the lowest possible risk. Business analytics software that include Dashboards are the most popular and attractive current tools that managers use in support to their business decision-making. Research from cognitive and psychology theories have demonstrated that people have preferences in the way they learn. The aim of this theoretical paper is to use existing theories in cognitive sciences and develop a model that explains how Business Analytic Software particularly Dashboards can be more effective, which in turn would help the users learn better and make better decisions. We argue that Dashboards must be smart and be able to display informational content based on the user’s learning preferences. Keywords - Learning Style, Dashboard Effectiveness, Decision Making