Innovative Research Methods in Technology: A Guide to Empirical Inquiry and Analysis

Description:

In an era where technological innovation drives global transformation, Innovative Research Methods in Technology: A Guide to Empirical Inquiry and Analysis provides a comprehensive, doctoral-level foundation for conducting rigorous, methodologically sound research in computing, engineering, and digital systems. Designed for emerging scholars and professionals, this text methodically examines the principles and practices necessary to produce credible, actionable insights in complex technology environments. Beginning with the philosophical underpinnings of empirical inquiry, the book navigates epistemological paradigms such as positivism, interpretivism, pragmatism, and critical realism, establishing how they influence research design and knowledge production in the tech sector. Students are guided through the essential distinctions between empirical and theoretical research, and how emerging technologies reshape inquiry, disruption, and innovation. Building on these foundations, the text explores the full spectrum of research methodologies, from experimental and survey designs to case studies and phenomenological analysis. Readers master the art of crafting research questions, aligning methodological choices, operationalizing constructs, and embedding ethical considerations, particularly in studies involving AI, user experience, and human subjects.

Each chapter offers deep dives into essential domains: quantitative methods (sampling, scale development, experimental controls, regression modeling), qualitative methods (interviews, thematic analysis, grounded theory), and mixed methods strategies that integrate both approaches seamlessly. The text further addresses advanced techniques in computational research, including machine learning applications, natural language processing, agent-based modeling, and big data analytics. Special attention is given to digital research tools, platforms, and automation, preparing students to leverage resources like REDCap, GitHub, NVivo, SPSS, Python, and AI-assisted literature review systems. Critical topics such as bias management, triangulation, reproducibility, and the ethical implications of algorithmic research are rigorously explored, ensuring students develop resilient, transparent research practices. Finally, the book equips readers with strategies for publishing in high-impact journals, presenting at major conferences, and translating research into tangible innovations for policy, education, and industry applications. Through detailed guidance and real-world examples, students learn not just how to conduct research—but how to elevate it to drive meaningful technological advancement.

Key Features:

• Comprehensive coverage of quantitative, qualitative, mixed methods, and computational research techniques.
• Practical strategies for designing valid, ethical, and rigorous technology-focused studies.
• Integration of AI, data science, and digital automation tools in empirical research.
• Frameworks for managing bias, ensuring reproducibility, and enhancing research credibility.
• Detailed guidance on publishing, presenting, and translating research into real-world impact.

Ideal For: Doctoral students in technology, cybersecurity, computer science, engineering, data science, and digital innovation programs; early-career researchers; technology professionals pursuing empirical studies; and doctoral candidates preparing dissertations and applied research projects.

Walsh College Students: This is the required textbook for IT703: APPLIED RESEARCH TOPICS I

ISBN-13 979-8-9987646-6-0

Format: E-Book