Sepm Unit 8

Learning Outcomes Achieved

1. Explore the implications of computer and network architectures for system-level design and development, as appropriate for risk and quality management

ePortfolio Activity/Seminar

I wasn’t able to attend the seminar due to a scheduling conflict, but I’ve created a slide presentation and attached it below (this included completing some work in Jupyter notebooks, and I incldued this as well). In the slides, I omitted NISTR 8062 from discussion because it’s not relevant to my group’s scenario- NISTR 8062 is intended for federal systems. By completing this activity, I achieved learning outcome 2 because I learned more about frameworks, tools, and methodologies which can be applied to manage risk in a software engineering project management scenario. I think it would be a good idea to have a group discussion on risks we may encounter in future, and manage those- I’ll try to action this.

Summary Post

This week, the discussion regarding user experience reached its conclusion. My thinking was challenged by the posts of my peers, thus I re-evaluated my initial stance and came to the conclusion that perhaps it’s not ideal to update the CUE model- rather, it should be kept as-is, and it is better to use a different model if something else needs to be represented (e.g. time).

By completing this activity, I have achieved learning outcome 2, because user experience is a product of computer applications, and I have learned how academic models provide lenses through which the field can be seen, however, not all academic models should accommodate all elements of a field, which is why I changed my view and instead suggested not extending the CUE model.

This discussion was slightly more abstract than most- it dealt with the subject matter from an academic point of view, but I think it has real world value regardless. Academic models provide perspectives that change based on the model used. CUE is a static model based on early stage, short term interactions with an application- time matters less in this scenario. Other models (like PLUX), would have different factors mentioned as influential ones because they’re based on long-term interactions. If we manage to get some UAT from the other team, CUE will be useful for integrating their feedback into later versions of our application- using CUE, we’ll be able to know which concepts to focus on by mapping their feedback to those concepts.

Artefacts

Codio Activity- Jupyter Notebook with estimation methods
Seminar Slides
Summary Post
Meeting Minutes