Chapter One — 1.1 Background to the Study

Organizations that depend on attendance management systems are under increasing pressure to modernize, and Explainable AI has emerged as one of the more promising avenues for doing so, given its demonstrated impact in related domains.

Despite this potential, many existing attendance management systems were not originally designed with explainable AI in mind, resulting in persistent gaps in user authentication that limit their overall effectiveness. This study examines how Explainable AI can be applied to help close that gap.

1.2 Statement of the Problem

Current attendance management systems in many organizations struggle with inadequate user authentication, often relying on manual processes or outdated architectures that were not designed for today's operating environment. Without a structured approach to integrating explainable AI, these limitations are likely to persist, exposing organizations to inefficiency, risk, and a poor user experience. This study is motivated by the need to design and evaluate a explainable AI-based approach to addressing this problem.

1.3 Objectives of the Study

1. To design and implement a explainable AI-based approach to improving user authentication in attendance management systems.
2. To evaluate the effectiveness of Explainable AI in enhancing user authentication within attendance management systems.
3. To identify the key requirements and constraints relevant to deploying explainable AI in this context.
4. To assess user and stakeholder perception of the resulting system.

1.4 Research Questions

1. How can explainable AI be applied to improve user authentication in attendance management systems?
2. How effective is Explainable AI at enhancing user authentication within attendance management systems?
3. What requirements and constraints are relevant to deploying explainable AI in this context?
4. How do users and stakeholders perceive the resulting system?

1.5 Significance of the Study

This study is significant to software developers and system architects seeking practical guidance on applying Explainable AI within attendance management systems. It is equally relevant to organizations that rely on these systems, offering a reference point for evaluating whether such an investment is justified, and it adds to the growing body of work on explainable AI applications in software technology / IT.

1.6 Scope of the Study

The study is limited to the design, implementation, and evaluation of a explainable AI-based approach to improving user authentication within attendance management systems. Reflecting its MSc-level scope, it does not extend to a full commercial rollout or long-term post-implementation review beyond the study period.