I used Snapchat to document my musings and findings at BETT 2017. I had a plan before I started but due to the livestream nature of Snapchat I digressed slightly. I tried to keep it as coherent as possible while touching on the different themes we’ve been discussing over the past couple of weeks.
I chose to use Snapchat because there was much discussion about how we enhance ourselves online. Snapchat has those features already built-in, without any need for editing tools.
On a technical note:
I was disappointed that IFTTT did not link to my Snapchat account. I suspect the impermanence of Snapchat contradicts IFTTT’s purpose. One of the reasons I like Snapchat is because it is fleeting. I don’t have to catch up or feel the pressure of looking at content I’m not interested in like I do with other social media sites. I tried to get IFTTT to feed into this through You Tube but, alas, my formula only works for vidoes I’ve liked and not with content I’ve created.
Bayne, S. (2014) What’s the matter with ‘Technology Enhanced Learning’? Learning, Media and Technology.
Miller, V. (2011) Chapter 9: The Body and Information Technology, in Understanding Digital Culture. London: Sage.
A brilliant video Chenee and a really interesting area to consider: how we can use technologies to enhance the image of ourselves which we present. One much-discussed element of this is, I guess, how our social media self is a product – often a much improved and ‘enhanced’ version of our RL self.
I’m so pleased that you unpicked and questioned many of the meaningless slogans which surrounded us at BETT: TEL presumptions defined much of what was offered and the discourse around it.
Really enjoyed this Chenée!
This was a fantastic idea – to undertake a bit of a micro-ethnography/discourse analysis of BETT, drawing on Bayne’s TEL critique (2014), and I really like the way you approached it. We’ll be doing more around micro-ethnography in the next block!
Really liked your comments on Snapchat filters too. I think this is such an interesting area (and one we’ll perhaps touch on in block 3 when we look at algorithms): automated visuals that change our appearance. It reminds me of the ‘selfie’ camera on one of my phones (a Xiaomi), which helpfully tells you your gender and your age when you look into it. Of course, its hilarious, because it usually gets it completely wrong. However, really fascinating issues around normalising gender and age appearances.
Great to see that you bumped into my colleague too!