Monday, 17 December 2018

Summarising Findings

In my teaching work, one of the hardest things is to teach students how to summarise their findings. It is a hard to get them to summarise enough. I do remind them that findings should contain not raw data, but information, clustering, summarising, and coding. 

Putting data into a table or spreadsheet can help us summarise the raw data to look for information, as show in the two small tables below. The first table is raw data. The second table has some emergent codes starting to appear in its simplest form which, once analysed, will become information - and lead to categories - to discuss in the findings section.

Topic
Ren Zing
Jin X
Li W
Zhang Ye
Hiring
prefers to hire experienced people rather than graduates, because Xing needs staff who have social networks to help the company sell more electronic products, and also, experienced people do not need to spend much time learning how to sell the products to customers and potential customers.
prefers to hire people without degrees to be couriers and graduates to be trained as potential managers. Because couriers should be strong and do not need to have much knowledge. On the contrary, managers need to have degrees that can let them be respected and accepted by their subordinates.
prefers to hire a graduate whose major was IT or other related subjects in university, because W’s main business is about IT and it is better if every staff has the professional knowledge related to IT
prefers to hire an experienced person without a degree. Because: She is not a graduate and she is afraid that graduate staffs may not obey her orders; She does not think that graduates are needed in such a small restaurant; Graduate staffs deserve higher salaries but she does not want to pay more money to her staffs as her small restaurant has a limited ability to get profits

Topic
Ren Zing
Jin X
Li W
Zhang Ye
Coding
Hiring
prefers to hire experienced people rather than graduates, because Xing needs staff who have social networks to help the company sell more electronic products, and also, experienced people do not need to spend much time learning how to sell the products to customers and potential customers.
prefers to hire people without degrees to be couriers and graduates to be trained as potential managers. Because couriers should be strong and do not need to have much knowledge. On the contrary, managers need to have degrees that can let them be respected and accepted by their subordinates.
prefers to hire a graduate whose major was IT or other related subjects in university, because W’s main business is about IT and it is better if every staff has the professional knowledge related to IT
prefers to hire an experienced person without a degree. Because: She is not a graduate and she is afraid that graduate staffs may not obey her orders; She does not think that graduates are needed in such a small restaurant; Graduate staffs deserve higher salaries but she does not want to pay more money to her staffs as her small restaurant has a limited ability to get profits
Not management graduatesWant experience + no degree; want graduate + work experience;

We need to look at our data over time and seek emergent codes (the colours), then write up our underlying factors from that (perhaps the green might be a category of protectionism: that the manager doesn’t want to hire anyone smarter than themselves in case the new hire takes over the manager's job), and while we explore the underlying factors in our findings, we may put intermediary analysis tables into our appendices if we feel they add value.

We will graph data, put codes into tables, cross-tabulate answers of different questions about what we know about the similarities and differences of the participants. We can do lots of analysis and really dig into our pot of gold. 


But recently I struck an issue at the other end of the data to information continuum: a student who summarised too much. The student summarised their findings so much that who owned the findings and how they were collected - both key sets of data in themselves - got lost in the process. As a result, the findings read like unevidenced literature review.

I advised the student that they needed to locate the clustered findings alongside their particular participant voices. I took a paragraph that they had written to illustrate what I meant.
I said to the student: "For example, you might preface 'The introduction of performance measures was not at a broad system level, but at a specific organisational level, and looked at how it is that organisations are going to be assessing measures relating to several different dimensions' with 
'A significant number of survey participants at [x] (75%) mentioned that the introduction of performance measures was not at a broad system level, but at a specific organisational level, and looked at how organisations would assess multiple-dimension measures.' 
While I might not have your meaning exactly correct (apologies: I have simplified your last clause as it was overly complex), you can see what I mean. The findings need to relate to those who said them".
I had not encountered over-summarising before. It was an interesting experience, both for myself and the student. At least I have written a blog post about it now, so if I strike it again, I can just direct the student to an example!


Sam

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