TY - BOOK
T1 - Engineering Research Mastery: From Defining the Problem to Delivering Result
T2 - Comprehensive Methods, AI-Driven Tools, and Practical Roadmaps for Modern Researchers
AU - Ma, Zheng Grace
PY - 2025
Y1 - 2025
N2 - Engineering Research Mastery provides a concise, step-by-step roadmap to transform real-world challenges into validated engineering solutions. Whether you’re a graduate student shaping a thesis, an industry professional steering an R&D team, or a researcher embracing AI, this guide equips you with the critical frameworks, best practices, and ethical considerations needed for impactful results.Plan and Scope: Differentiate broad challenges from precise problems, defining research aims and objectives with clear stakeholder focus.Select Methods Wisely: Utilize qualitative, quantitative, or mixed methods—from simulation to user acceptance testing—for diverse engineering contexts.Build and Validate: Turn conceptual designs into prototypes or simulations, then employ scenario-based testing to ensure feasibility and innovation.Integrate AI: Boost efficiency in literature reviews, data analysis, and scenario design with AI tools, uncovering hidden insights and supporting adaptive testing.Communicate with Impact: Present findings in articles, reports, or conferences using structured templates and a self-evaluation approach that ties your narrative to authentic data.Achieve mastery in engineering research—fusing academic rigor with real-world practicality—and tackle both foundational and advanced projects with confidence.
AB - Engineering Research Mastery provides a concise, step-by-step roadmap to transform real-world challenges into validated engineering solutions. Whether you’re a graduate student shaping a thesis, an industry professional steering an R&D team, or a researcher embracing AI, this guide equips you with the critical frameworks, best practices, and ethical considerations needed for impactful results.Plan and Scope: Differentiate broad challenges from precise problems, defining research aims and objectives with clear stakeholder focus.Select Methods Wisely: Utilize qualitative, quantitative, or mixed methods—from simulation to user acceptance testing—for diverse engineering contexts.Build and Validate: Turn conceptual designs into prototypes or simulations, then employ scenario-based testing to ensure feasibility and innovation.Integrate AI: Boost efficiency in literature reviews, data analysis, and scenario design with AI tools, uncovering hidden insights and supporting adaptive testing.Communicate with Impact: Present findings in articles, reports, or conferences using structured templates and a self-evaluation approach that ties your narrative to authentic data.Achieve mastery in engineering research—fusing academic rigor with real-world practicality—and tackle both foundational and advanced projects with confidence.
KW - Engineering research methods
KW - AI-driven engineering
KW - Scenario-based testing
KW - Verification and validation
KW - Quantitative & qualitative synergy
KW - Product design & development
KW - Practical R&D roadmaps
M3 - Monograph
SN - 979-8305757439
BT - Engineering Research Mastery: From Defining the Problem to Delivering Result
PB - Amazon.co.uk
ER -