Learning outcomes
After completion of this course, the student is expected to be able to:
- argue on a variety of existing software techniques and tools and provide different classifications of them;
- critically discuss the strengths and limitations of automation and measurement in problem-solving;
- have knowledge of a variety of evaluation methods, techniques and tools;
- promote and apply the concepts of measurement, metrication and evaluation in research, entrepreneurship and industry;
- facilitate decision making by utilising scientific ways, knowledge and expertise;
- compare and contrast research ideas, software components, constructs, quality properties, and so on;
- predict scientific outcomes with greater precision and accuracy;
- experiment and research with greater accuracy, correctness and consistency;
- create and utilise appropriate metrics and measures in different application domains e.g. in business innovation, development strategies and other;
- help associates to expand their knowledge through different problem solving strategies.
Contents
See learning outcomes.
Teaching methods
Will not be organized yearly.
Modes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Evaluation
Numeric 1-5.Belongs to following study modules
2018–2019