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 decisionmaking.
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