Every few months, I do Google Scholar searches to see if anyone has published research studies focused on Twitter chats. I am looking for someone who has come up with a way to track the quality of interaction or the value of the content that has been shared.
My opinion of twitter chats has not changed. I take a look at a couple of chats now and then to see what I think. I find it hard to believe there is much learning going on. Perhaps socialization and morale building, but little information shared or issues debated. I thought with the increase in length of tweets that is now allowed there might be more actually happening. The brief comments that could be exchanged was one of my original complaints. More can now be conveyed with a single tweet, but I seldom observe that this extra space is being used.
When I search for published material on Twitter chats, I find plenty of explanations for how to conduct a Twitter chat. I find a few suggestions for how to make chats more productive. I find proposals that chats can fill many specific needs. I just don’t find anyone analyzing what goes on during a chat (process variables) or what changes as a consequence (product variables).
I did locate a paper noting that Twitter chats could be used to support the needs of medical professionals and proposing possible benefits and concerns. My hope has been that researchers would take these potential benefits and concerns, operationalize these possibilities in ways that would be easy to identify, and see what actually happens before, during, and after chats.
Choo, E. K., Ranney, M. L., Chan, T. M., Trueger, N. S., Walsh, A. E., Tegtmeyer, K., … & Carroll, C. L. (2015). Twitter as a tool for communication and knowledge exchange in academic medicine: a guide for skeptics and novices. Medical teacher, 37(5), 411-416.
I keep suggesting that education graduate students take on this type of research. I keep thinking that some useful data should be easy to collect. Chats are often archived and available. There would be some questions best answered by observing chats in real time, but some basic quantitative information should be easy to generate by using archived data.
If this makes little sense, consider that coding systems for classroom interaction have been used for years (e.g., Flanders; Brophy & Good). Consider that Choo, et al. suggest that professionals can benefit from chats by sharing suggestions for practice, identify useful resources that may be unfamiliar to others, request tactics for dealing with an unfamiliar challenge, etc. It should be relatively easy to determine how frequently these things happen within a designated unit of chat time.
Measures of interaction were a major emphasis of the observation systems developed to study classroom interactions. Similar issues are relevant for Twitter chats. What is the frequency of questions asked beyond the standard questions provided to promote chat responses (is there much interaction)? What is the frequency of statements of support, challenges to comments made, requests for clarification?
Perhaps factors might be related to these variables. Have these variables changed when chats before and after the extended format are compared? Do groups selected at random and sampled multiple times have different cultures reflected in this type of variable? Does the use of an announced reading assignment result in different types of interaction than topical chats not involving preparation?
Why are these and related questions worth investigating? I think it is important to determine if the time expended is productive. Should this time be credited as professional development if the benefits are questionable?
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