Activity
You have most likely disagreed with a colleague, friend or online review about whether a film, television show or event was ‘good' or ‘bad'. Everyone has his or her own unique biases and ways of judging quality, which affect interpretations. When you interpret the findings of your research, you make value judgements and report what you feel is important given your particular context. Examining other researchers' data analyses and interpretations can give you a glimpse into their value judgements and thought processes. Additionally, you may disagree with their interpretations and think of alternative analyses that would have been more appropriate or yielded better outcomes.
In this Shared Activity, you will find a method for displaying data (eg table, graph or diagram) from a published article and critically evaluate its approach. Additionally, you will comment on alternative approaches and recommend improvements on a variety of data display examples. In the second week of the unit, you will continue your work on your research proposal by sharing ideas with your colleagues about how best to approach data analysis and presentation in your own research proposals.
To prepare for this Shared Activity:
Use the following management research articles, and evaluate the methods used to analyze and present the data.
1. Moving from traditional to agile software development methodologies also on large, distributed projects.
2. Empirical studies of agile software development: A systematic review
3. Adopting Agile Software Development: Issues and Challenges
To complete this Shared Activity:
- Post your data display exemplar and present an analysis of its characteristics:
- What analytical strategies and tools were used to analyze the data? Can you suggest alternative strategies and tools? How would analyzing the data in a different manner alter the data presentation?
- Critically analyze how the data are summarized. Do you detect any bias in how the data are presented?
The solution must be as follows:
Article 1 Moving from traditional to agile software development methodologies also on large, distributed projects.
1) What analytical strategies and tools were used to analyze the data?
2) Suggest alternative strategies and tools and explain them in detail
3) How would analyzing the data in a different manner alter the data presentation?
4) Critically analyze how the data are summarized.
5) Do you detect any bias in how the data are presented?