Date of Award

2013

Document Type

Master Thesis

Degree Name

Masters of Science (Research)

Department

Computer Science

First Advisor

Dr. Paul Walsh

Second Advisor

Paul Rothwell

Abstract

Mobile devices are now truly ubiquitous. Their pervasiveness in all facets of our lives brings many advantages. Principle to these advantages is the notion that mobile devices can be used “Anytime, Anywhere”. The size, portability, battery life and computational power of mobile devices mean that they can be used for a diverse range of uses in an equally diverse range of environments.

Usability is primarily concerned with “ease of use” and “learnability”. Mobile devices are challenging this notion of Usability as they are used in new ways. Firstly mobile devices arc used in complex distracting environments and these distractions interfere with the user’s cognitive resources. Secondly mobile devices arc becoming advanced and powerful and this allows more sophisticated applications to be used on them. An example of this type of application is a learning application. Such an application is cognitively demanding and when the mobile device is used in a distracting environment this leads to scenarios where the user’s cognitive resources become overloaded.

Cognitive Load Theory explains how the human mind interacts with instructional materials and has several guidelines that are used to assist in the design of instructional material used for learning. This material should be focused on learning and should not contain distracting elements. This work investigates whether Cognitive Load Theory can be adopted into Usability Engineering to address the issues of environmental distractions affecting users learning on mobile devices.

Two major obstacles to this adoption were discovered. 1. The theory has ill-defined elements and 2. Cognitive load is difficult to measure. An experiment was conducted that gave insight into these obstacles and a new usability heuristic was developed, “Allow and 111 expect the user to learn”. This heuristic is based on Cognitive Load Theory and can be added to existing usability heuristics to help guide in the design and evaluation of learning software. IV

Access Level

info:eu-repo/semantics/openAccess

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