Technical Communication
Academic writing within Technology constitutes an essential capability enabling practitioners to document systems comprehensively, explain technical concepts to diverse audiences, and develop the systematic analytical thinking that distinguishes thoughtful engineers from merely competent coders.
Academic writing within undergraduate Technology education occupies a particularly instrumental yet intellectually demanding position, serving simultaneously as a means of documenting technical work, explaining complex systems and processes, demonstrating analytical understanding of computational principles, and preparing students for diverse communication challenges in rapidly evolving technical fields.
For students pursuing degrees in Technology and its component subject areas—including technology specialisms—academic writing represents far more than auxiliary skill separate from technical practice. Rather, it constitutes an essential capability that enables you to translate between code and natural language, articulate design decisions convincingly, and participate meaningfully in collaborative knowledge-building that characterizes contemporary technology development.
Constructed Artifacts
What fundamentally distinguishes Technology writing emerges from its relationship to constructed artifacts—the working systems that represent principal evidence of technical capability alongside written explanation.
Unlike disciplines where writing constitutes the primary demonstration of knowledge, in Technology the working artifact itself—functioning code, operational robots, playable games, trained machine learning models—represents the principal evidence of technical capability. Writing serves essential supporting functions including documenting technical decisions, explaining system architecture, and communicating complex concepts to varied audiences.
Beyond traditional academic essays, you must develop facility with technology-specific writing forms that operate according to different conventions regarding tone, structure, technical detail, and audience assumptions.
Technology writing necessarily engages with the tension between technical precision and accessibility. You must learn to maintain technical accuracy whilst explaining concepts at multiple levels of abstraction depending on reader expertise.
Technical project reports constitute the most characteristic written assessment format, documenting significant projects whether developing software applications, building robotic systems, creating games, training machine learning models, or implementing computational solutions. These develop documentation and communication capabilities central to professional technical practice.
These discipline-specific formats define system requirements, describe architectural designs, specify interfaces and protocols, or provide user and developer documentation. Writing effective technical documentation requires systematic thinking about system structure, clear explanation using appropriate technical vocabulary, and attention to different stakeholder needs.
Assignments examining emerging technologies, methodological approaches, or theoretical concepts help students orient themselves systematically in rapidly evolving fields, evaluate technical claims critically, and identify promising research or development directions through systematic source evaluation and synthesis.
Formats requiring articulation of high-level system designs before implementation, explaining overall structure, component organization, technology choices, and design rationale. These develop systematic design thinking and communication capabilities distinguishing thoughtful architects from ad hoc coders.
Extended pieces requiring students to design and conduct original investigations of technical questions, developing research capabilities through comprehensive literature reviews, methodological justification, systematic result presentation, and critical discussion of implications and limitations.
Assignments requiring analysis of development processes, team collaboration, technical decision-making, or critical evaluation of technologies, systems, or methodologies. These develop continuous learning capabilities and critical thinking about technical choices and their implications.
Professional Focus
Assessment criteria reflect the discipline's technical focus and professional orientation, emphasizing clear communication and systematic thinking alongside coding capability, with growing attention to ethical considerations and societal impacts.
Building and evaluating computational systems in areas like operating systems, databases, networking, and distributed systems. Writing requires explaining system design, describing experimental methodology, presenting performance results with analysis, and discussing implications and limitations.
Developing new algorithms, proving properties of computational processes, and advancing theoretical understanding. Writing follows mathematical conventions requiring precision, logical rigor, and ability to explain intuition behind formal results.
Prominent in machine learning, data science, and AI, involving dataset collection, model training, and statistical evaluation. Writing requires describing datasets and preprocessing, explaining models and training procedures, and presenting results with appropriate statistical analysis.
Creating artifacts in areas like game design, HCI, and software engineering, studying their effectiveness through user studies and evaluation. Writing requires explaining design rationale, describing evaluation methodology, and discussing design implications and principles.
Collecting and analyzing data about software systems, development practices, or technology use employing social science methods. Writing requires explaining research questions, describing data collection methods, and presenting findings clearly.
Synthesizing existing research through careful review or replication of prior work. Writing requires systematic description of methodology, fair representation of prior work, and critical analysis of collective evidence.
Engage regularly with well-written technical content including research papers from major conferences, technical blogs, and open-source project documentation. Pay attention to how skilled communicators explain complex concepts, structure technical arguments, and document systems effectively.
Cultivate practices of writing clear inline comments, creating informative README files, documenting APIs comprehensively, and maintaining design notes throughout development. This regular practice builds documentation skills incrementally whilst creating valuable records of technical work.
Practice explaining technical concepts to non-technical audiences through tutoring, blog posts, presentations to family members, or video explanations. This develops ability to identify appropriate explanation levels and create helpful analogies and examples.
Build understanding of established design patterns, development methodologies, testing approaches, and security principles. This knowledge enables discussion of technical work within established frameworks and justification of approaches grounded in accepted practices.
Learn to create clear technical diagrams using appropriate tools. Practice visual communication to convey structural relationships clearly and support written explanation with helpful visual aids.
Develop habits of asking not just whether technical solutions work but also how they affect users, what privacy implications they carry, whether they include or exclude particular populations, and what unintended consequences they might produce.
This section provides a comprehensive list of all key terms used throughout this guide. Hover over any term to see its definition.
technology specialisms translate between code and natural language constructed artifacts technology-specific writing forms technical precision and accessibility technical project reports technical accuracy and precision systematic thinking and analytical rigor visual representations technical diagrams