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Analysis of Data Presentation. Present the most pertinent findings clearly in relation to your chosen theme or themes 9%. Give a rationale for your theme or themes or the question or hypothesis you have chosen to explore 2%
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Present the most pertinent findings clearly in relation to your chosen theme or themes 9% • Give a rationale for your theme or themes or the question or hypothesis you have chosen to explore 2% This is drawing from your introduction – be clear and concise, don’t ramble and spread this out
Present the most pertinent findings clearly in relation to your chosen theme or themes 9% • Give some pieces of interesting verbatim that illustrate an interesting theme sub-theme 5% Show with a few examples how your participants’ responses are categorised in relation to an interesting/important theme or sub-theme. Some may be for and others against and some in the middle – demonstrate this
Present the most pertinent findings clearly in relation to your chosen theme or themes 9% • Make it clear the number of participants that align for or against (or in between) your most important findings 2% Summarise where your participants are in relation to a theme or sub-theme category by giving the percent in each category.
Describe the strengths and weaknesses of a method of analysis needed to do this research 4%. • Explain how useful a method of analysis was in helping you to create coherent ideas or theories about the data. Think about a conclusion that you have reached. What one method of analysis helped (or not) in reaching that conclusion
Methods of Analysis 1 • Creating themes (data analysis categories) • using the demographic and ecological footprint data to select your sample, • using the semiotic square to create opposites and continuums or paradoxes with both/and categories, • using techniques of deconstruction such as looking at power relations, roles, hierarchies, rules, etc, looking for the myths • Categorising the responses on the basis of rules that you have created, • Creating a profile of your sample and using the quantitative data to explore differences that emerged in the analysis, • Using a test of significance - correlations, chi-squares or t-tests - to illustrate a point
Methods of Analysis 2 One of these approaches may have • been much more important in getting you started, • produced a moment of real clarity and excitement, • led you on a wild goose chase, • been more helpful in organising the data, • helped explain a key point of theory supporting your hypothesis, • led you to reconsider the validity of the data • etc. Briefly describe the process and the outcome
Use clear (easily readable) and informative visual and auditory aids and integrate these well with the presentation 2% • If you are using powerpoint don’t go under 24 point font • Make sure that your type stands out on your background • Use at least one image to make it look interesting. • Keep your powerpoint in sync with your presentation
Provide references -2% if not provided • Run to time (you will be stopped when the time runs out) -1% (If you go over/under time )