I have been buried this semester with work, teaching two full sections of an education theory class, doing observations of our preservice teachers, and also writing my proposal for my dissertation.
Lets say the first two items in that list got far more priority during the first half of the semester, and I had to kick it into gear the last half. But, I did kick it into gear, took a ‘mental health day’ for the first time in my life, and accomplished a working introduction and literature review for my proposal. In the list above, I have experienced all 6 steps. What is missing to the list is step 7; “Repeat”. You print the introduction, then start the lit review while you wait for feedback on the intro, then print the lit review, and revise, resubmit, and revise again. And again. It is worth the work, but wow. I know now why so few people finish nationwide. Next up, is my methods section.
And, I need to work through some details, so I thought I would post them here. I am not sure anyone will be interested in the lit review, but there may be some small interest by one or two people. I am going to over explain things, because it will help me shape the academic writing I need to do over the next two weeks.
The big idea, is that I am going to do a mixed method analysis of a particular math conference, founded by teachers, created organically from the ground up to create a different type of professional development experience; TMC17.*
Why mixed methods, and what type of mixed method analysis?
The quantitative analysis is going to be Social Network Analysis (SNA) of the tweets which occurred over the week prior, the 4 days of, and the month after TMC17. I used NodeXL to collect the public tweets each day of the 41 days. NodeXL downloads the entire network of tweets, so for a tweet from someone to 3 other people, that creates 4 lines of text in the spreadsheet. It also downloads whether it is a retweet, a reply, or something else. It is very powerful software, which is very inexpensive if you are a student ($29 per year). The software calculates radial measures of centrality, betweenness, density, and other calculated statistics on the data set. These calculations and the resulting graphs will allow influencers, central individuals, and other patterns of tweeting to be discovered.
One type of SNA graph can look like:
Each dot is a node, person, or vertex, and the line between people is a tie, connection, link, dyad, or relationship. The language depends on the book you use to guide the analysis. I need to pick which terms I want to use, and why. Nodes which are larger have a larger influence, the distance between the nodes is a measure of betweenness, and the distance from the center is radial measure of distance. There is a lot of info packed into these graphs. The number of rows in the TMC excel file is over 17,000!** There is a LOT of information to unpack.
I am looking for patterns in the information. Are there groups of individuals who are on the inside? Are those people first time attendees? Experienced attendees? Leaders of morning sessions? Keynote speakers? Etc. A really rough draft of a question for this data set is; “What are the tweeting behaviors of the participants of TMC17?” Or: “What are the online practices of the attendees of TMC17?” I am not sure which way to go yet.
This analysis is sufficient for a dissertation, I think. There is a lot of data here to unpack, to analyze, and to show the online behaviors of the participants. However, this is only the start. I am going to use this data to divide the actual tweet contents into groups for comparisons.
That is the qualitative part of the mixed method design.
That is another post, entirely!
Thanks for reading this far, and please leave any questions in the comments or on Twitter.
*If you are saying, “wait a minute, how can you have data from TMC17, and yet not have written the full proposal yet?” It is because I wrote a mini version, a pre-proposal, which justified to my committee enough to allow me to collect data prior to the full proposal to be written. I have not been allowed to look at any data until the proposal is accepted by my committee. This will allow me to graduate May 2018 instead of 2019.
**A very important point to make clear is that these are only the PUBLIC tweets, that used the hashtag #TMC17. If a conversation was held that never used the hashtag, it never came up in the search. If a person’s twitter feed was private, it was ignored by the search. Only public, hashtagged tweets were allowed into the data set by the search.