@Digeded Keyhole analytics of #mscedc showing sentiment, gender split etc. https://t.co/qMGag1zvcS pic.twitter.com/2M2gL4Eqj5
— Nigel Painting (@nigelchpainting) March 24, 2017
I’ve added my comments on the above in my Tweetorial analysis
@Digeded Keyhole analytics of #mscedc showing sentiment, gender split etc. https://t.co/qMGag1zvcS pic.twitter.com/2M2gL4Eqj5
— Nigel Painting (@nigelchpainting) March 24, 2017
I’ve added my comments on the above in my Tweetorial analysis
Not quite what you might think from the title, more mathematics and the humanities https://t.co/7ssIzlt3mm #mscedc
— Nigel Painting (@nigelchpainting) March 14, 2017
Great video, Clio Cresswell talks about how “mathematics lies right at the root of human culture”.
https://t.co/tEYYcCW7a7 #mscedc
— Nigel Painting (@nigelchpainting) March 9, 2017
Andreas Schleicher talks about the PISA test. This is a global measurement that ranks countries against one another and uses the data to help schools improve.
“Measuring how much time people spend in school or what degree they’ve got is not always a good way of seeing what they can actually do”
PISA tests whether students can extrapolate what they’ve learned and apply their knowledge in novel situations. Apparently we’re so, so in the rankings of the readiness of our young people for today’s economy.
Most relevant to this algorithmic cultures block “Data can be more powerful than administrative control or financial subsidy through which we usually run education”
Finding unexpected results with Amazon's algorithms, expected high ticket price searches to be privileged, but appears they're not #mscedc
— Nigel Painting (@nigelchpainting) March 9, 2017
Adchoices from the advertiser's perspective https://t.co/jZl4UWDjOB #mscedc
— Nigel Painting (@nigelchpainting) March 6, 2017
A rather telling quote from the opening of this blogged article reads “The good news for advertisers is that [the Adchoices] icon is fairly small and unobtrusive; most consumers don’t even notice it.” However, the closing remarks are more positive from both a consumer and advertiser perspective. “I’d love to see Google go the extra mile and offer additional information to advertisers. Sharing information gleaned from muted ads could be a game changer for PPC advertisers. […] Analyzing the results from this would allow advertisers to understand whether their ads simply aren’t resonating with their audience, or if they are too repetitive. Armed with this information, they will know when they need to create fresh ads or adjust their ad delivery settings.” This feels like a good example of how analytics can be used to drive improvements, although it appears in this case that the data isn’t being made available to those who could make the best use of it.
Incidentally, in a moment of pure serendipity, while tweeting the above I noticed a link to follow my nephew’s partner on Twitter – algorithms in action!
Algorithmic cultures and how ad-retargetting ruined Christmas https://t.co/vIGza43JyL #mscedc
— Nigel Painting (@nigelchpainting) March 6, 2017
A great example of when ‘making visible the invisible’ isn’t necessarily a good thing.
Apologies if this has already been linked. https://t.co/95Og37X375 #mscedc
— Nigel Painting (@nigelchpainting) February 28, 2017
This quote from NY Times columnist and Pulitzer Prize winner Thomas Friedman sets the scene for this TED talk from Daphne Koller, co-founder of Coursera.
The talk is relevant to both the community culture and algorithm cultures of this course. From a community perspective Koller describes cultural norms in MOOCs that we have also seen develop during this course, including students asking and answering each others questions and forming into smaller study groups of their own volition.
From an analytics perspective Koller talks about the way massive open online courses have enabled turning “the study of human learning from a hypothesis driven mode to the data driven mode”. Koller states that the data Coursera collects enables fundamental questions such as “what are good learning strategies versus ones that are not” to be examined. She also talks about the personalisation that is possible by virtue of having large volumes of data available, making it easier to spot anomalies and address them with targeted guidance for students.
Interestingly she doesn’t see MOOCs making traditional universities obsolete, but calls upon them to move away from the lecture based format and embrace active learning.
She finishes with a vision of the possibilities that online education brings for fundamental change in the world.