Curriculum Overview
DScIT Program
Components
The Doctor of Science in Information Technology comprises 15 graduate courses organized into three focused components — Topics, Leadership, and Research — each designed to build doctoral-level expertise.
Topics Component
5 courses — advanced IT domains and emerging strategies
Data Science & Analytics Strategy
Strategic application of data science tools and analytics pipelines to drive evidence-based organizational decision-making at the doctoral level.
Organizational Strategy for Cybersecurity Management
Enterprise-level frameworks for managing cybersecurity risk, governance structures, and resilience strategies across complex organizations.
Information Technology Policy, Compliance, and Legal
IT governance, regulatory compliance frameworks, and the legal landscape governing technology deployment and data management.
Information Technology Project and Program Management
Advanced methodologies for leading large-scale IT initiatives, program portfolios, and cross-functional technology projects.
Contemporary Issues in Information Technology
An examination of rapidly evolving technologies — AI, cloud computing, digital transformation — and their organizational and societal impact.
Leadership Component
4 courses — executive leadership and organizational strategy
Design Thinking & Innovation
Human-centered approaches to problem-solving, rapid prototyping, and driving technology innovation within organizational and research contexts.
Leading Disruptive Technology in Organizations
Strategies for championing, managing, and sustaining disruptive technological change at the institutional and enterprise level.
Leadership Development
Building the executive presence, communication, and decision-making skills required of doctoral-level IT professionals and organizational leaders.
Information Technology Strategic Planning
Long-range IT planning methodologies aligned with organizational vision, competitive positioning, and institutional business strategy.
Research Component
6 courses — from foundational methods to doctoral research
These 6 courses form the backbone of the DScIT program. See the full sequence and progression on the Research Courses & Sequence page.
Research for Decision Making
Foundations of research methodology — types of research, literature reviews, and applying scholarly inquiry to real-world IT challenges.
Statistical Analysis for Decision Making
Quantitative methods, statistical inference, and data analysis tools for producing evidence-based technology and organizational decisions.
Advanced Research for Decision Making
Advanced research design, mixed-methods approaches, and critical analysis techniques for complex, multi-layered IT problems.
Qualitative Analysis for Decision Making
Qualitative research paradigms — interviews, case studies, thematic analysis — and their application within information technology contexts.
Research Design Proposal
Developing, writing, and defending the doctoral research proposal — the gateway milestone before proceeding to the Doctoral Research Project.
Doctoral Research Project
The culminating doctoral milestone — original, independently conducted research that makes a meaningful contribution to the information technology field.