I’ve been thinking a lot about how to design a system for computational ethnography. I think the least intrusive method would be to employ machine learning and computer vision to analyze a video stream in realtime. Something like the amazing cognitive APIS coming out of Microsoft – and the projects by Microsoft Research.

I’m thinking of building a prototype with a Windows laptop running a webcam or maybe a Kinect camera.

I’m compiling some links…

Hollands, F. M., & Bakir, I. (2015). Efficiency of Automated Detectors of Learner Engagement and Affect Compared with Traditional Observation Methods. http://doi.org/10.13140/RG.2.1.1332.8082

A really interesting article, looking at direct human observation, video observation, sensor-light and sensor-heavy observations. For small projects, direct human observation seems to work best (for now), but costs too much to use at scale (or for long). Technology-mediated observations cost more to develop, have lower reliability, but are able to be deployed at much higher scales and for much lower costs over time. The tools will get better, but I think focusing on log files is shortsighted – they only track what software has been adapted to log.

Nelson, R. (2013). Practice as Research in the Arts: Principles, Protocols, Pedagogies, Resistances. Palgrave Macmillian UK. DOI 10.1057/9781137282910

Much of the book is dedicated to legitimizing PaR as a field.

Documentation is often conflated with evidence – not the same thing. Documentation of a performance or practice is not the performance itself. (Well, duh). Examination? Audit?

Practice as research provides a way to “house the mix” of research methods and data – combining textual and discourse as well as other methods to tell a full(er) story of the performance.

Stephen Downes points to some new regulations that may require people (celebrities and others) to declare when something they're posting has been sponsored by a third party. He also suggests (rightly) that edubloggers and pundits should have similar declarations, to point out any possible conflicts of interest or bias.

Not that I expect any major change, but it would be interesting to see all education and technology pundits declare their sponsorships and affiliations. "The new rules, expected to be implemented by early 2017, will require such individuals to disclose whether they've received payment — either in the form of cash, free products or other considerations — in exchange for the mention. Bloggers will need to include statements within their posts or videos while users of social media platforms such as Twitter, Instagram and Snapchat will have to include hashtags such as #sponsored, #spon or #ad."

Wordfence automatically blocks IP addresses that repeatedly attempt to brute-force logins on UCalgaryBlogs. After a few attempts, they aren't able to try again for a few minutes (in case it's a legitimate person trying to log in, it doesn't banish them entirely right away). If they knock it off, the ban gets lifted. If they keep hammering, the ban gets escalated, eventually putting them in a permanent penalty box (identified by their IP address - not perfect, but it's all we have).

Patel, V. L., Kannampallil, T. G., & Kaufman, D. R. (2015). Cognitive Informatics for Biomedicine.

Notes:

p.128: Computational Ethnography: Automated and Unobtrusive Means for Collecting Data In Situ for Human–Computer Interaction Evaluation Studies — Highlighted Aug 21, 2016

p.132: Combining the ‘thickness’ of ethnographical methods with the strength of automated computational approaches is thus a natural next step for HCI researchers. This new way of collecting behavioral and social data not only forms the basis of the computational ethnography methodology described this chapter, but also the emerging field of “computational social science” at large (Lazer et al. 2009; Giles 2012). In the context of this chapter, we define computational ethnography as “a family of computational methods that leverages computer or sensor-based technologies to unobtrusively or nearly unobtrusively record end users’ routine, in situ activities in health or healthcare related domains for studies of interest to human–computer interaction.” Because computational ethnography is based on data automatically captured through technological means, it by nature provides higher objectivity, less intrusion, more inclusiveness (i.e., into spaces and time where/ when direct observation by human observers is not possible), and better scalability for data collection, aggregation, and analysis. Note that while recording user interactions with a computer system such as keystrokes (Card et al. 1980) and analyzing the behavioral data thus obtained (Ritter and Larkin 1994) have been a widely used study approach in HCI, unless their data are collected in users’ everyday settings via unobtrusive or nearly unobtrusively means (i.e., as opposite to a controlled laboratory environment), such studies do not meet the definition of computational ethnography. Similarly, quantitative observational studies involving independent human observers (e.g., in a time and motion observation) to collect interaction or behavioral data also do not meet the definition of computational ethnography. — Highlighted Aug 21, 2016

Alec Couros posted a quick throwaway on Facebook (I'd link to it, but Facebook doesn't work that way)

It got a lot of likes, and then the comment thread kind of exploded. I posted several comments and replies, and realized that was a silly way to post that particular discussion because it's exactly the kind of thing we are talking about as killing blogging and personal publishing.

A great summary of various bits of tech that made the early blogosphere¹ so alive and vibrant in ways that hasn’t been captured or reproduced since. How can tools give individuals control over what they create, where they publish, who they follow, what they read, and how they share? These are currently controlled almost exclusively by one of two companies for the majority people on the modern internet. Something amazing, powerful, and enabling was lost in that transition.

A million times, this:

You hear a lot of talk about information overload, but I don't feel the amount of information is the problem. For me, the problem comes in with the emotional investment demanded by real-time, and the ultimate toll it can take on your productivity, or just general happiness and well-being. You can see this play out in everything from expectations that you should respond to emails, all the way to social network memes getting your attention when it comes to the election, or for me personally, the concerns around security and privacy using technology.

Humanity as isolated individuals, and how that is a modern/western concept. Humans are not really isolated, and suffer when truly alone. 20th century human exceptionalism has pushed us to a population of sociopaths. Technology has the potential to reconnect individuals. Connectivism, with knowledge and context shared across organic and distributed networks of humans, connecting in different ways for different reasons.

Computer code as a pure, algorithmic, restricted context that can be shared. Only that which has been coded exists within the context. Different languages and environments can make different contexts possible or impossible, depending on the vocabulary, diction, syntax, interaction patterns, etc that are available. A diversity of languages is needed, to be able to share a diversity of contexts.

I started a new blog site, running the fantastic Known blogging platform on a fresh subdomain running on my webspace at Reclaim Hosting. The intention was to give a place to think out loud about stuff I’m working on or thinking about for my PhD program. I started publishing some stuff, and then realized that having a separate site for that was awkward. There was no real need to separate and disconnect that content from the Day Job™ content from the-rest-of-my-life content.