TECHNOLOGY-05 · Undergraduate · ENGLISH · PLANNED
Follow a real task through a system, then design and troubleshoot it.
Study time is an initial activity estimate, excluding extra reading, revision and extended laboratory or project work. Videos and question bodies have not been produced by adding this outline.
Complete these courses or demonstrate equivalent knowledge. These are recommended prerequisites, not enforced enrolment locks.
YouTube playlist: ARK Technology | Software Engineering and Product Design
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Sign in to save this learning pathPractical outcome: Write acceptance criteria for a small study planner.
Explain user needs using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain functional requirements using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain quality requirements using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain user stories using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Use the first concepts from this section. Write acceptance criteria for a small study planner. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain acceptance criteria using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain wireframes using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain data models using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Explain design tradeoffs using a visual and one worked real-world example. Context: Write acceptance criteria for a small study planner. End with a prediction or check-for-understanding.
Write acceptance criteria for a small study planner. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering User needs, Functional requirements, Quality requirements and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Review a sample change and prepare a safe release checklist.
Explain version control using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain branches using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain commits using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain pull requests using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Use the first concepts from this section. Review a sample change and prepare a safe release checklist. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain code review using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain unit tests using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain integration tests using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Explain continuous integration using a visual and one worked real-world example. Context: Review a sample change and prepare a safe release checklist. End with a prediction or check-for-understanding.
Review a sample change and prepare a safe release checklist. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Version control, Branches, Commits and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Investigate a fictional production incident and propose a measured fix.
Explain configuration using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain dependency management using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain releases using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain logging using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Use the first concepts from this section. Investigate a fictional production incident and propose a measured fix. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain metrics using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain tracing using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain incident response using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain technical debt using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Explain maintenance using a visual and one worked real-world example. Context: Investigate a fictional production incident and propose a measured fix. End with a prediction or check-for-understanding.
Investigate a fictional production incident and propose a measured fix. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Configuration, Dependency management, Releases and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Combine all three sections: Investigate a fictional production incident and propose a measured fix. Submit an original worked artifact, evidence or tests, assumptions and a reflection. Rubric: correctness, method, practical usefulness, reproducibility and communication. Self-reviewed, not certified.
6–12 balanced questions sampling every section of Software Engineering and Product Design, including interpretation, calculation or reasoning, a misconception and a new application. Passing is 70%; review errors before retrying.
System diagrams, design reviews and bounded prototypes. Guided work leads to an independent attempt, with a diagram, explanation, trace, calculation or tested artifact. Question bodies are generated when opened in your private learning path. Programming submissions are stored as text; the platform does not execute submitted code.
Use original or appropriately licensed datasets. Practical science activities use models or supplied data unless a qualified supervisor has reviewed a physical experiment.
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