Reflections on my Lifestream Blog

My lifestream blog is a good example of how participatory and algorithmic cultures can shape education today. Within these two dimensions, my learning experience felt very authentic, stress-free and natural. Unlike some more traditional forms of education, crafting a lifestream blog suggests freedom, creativity and personalization. However, learning with technology has many nuances that are not on the surface.

It can be argued that my lifestream blog is a blueprint of participatory culture ‘with relatively low barriers to artistic expression and civic engagement, strong support for creating and sharing one’s creations, and some type of informal mentorship’(H. Jenkins). Thus, my blog aggregates interactions with other EDC students, random people on the Net as well as my digital artefacts and web content I engaged with.

It is noteworthy that I often found my peers’ posts more relevant than mine, that’s why I spent a lot of time reading their blogs. Maybe, it was because their algorithms were ‘better trained’ due to my peers’ location or occupation. Like for most of my peers, Twitter turned out to be the most popular network for me. Not only did it guarantee some feedback on my posts, but it also enabled me to follow ed tech gurus and learn from them. Importantly, a lifestream blog was also a means of communication with my course tutor and a record of my learning journey.

Before week seven, I saw myself as the one and only creator of my blog even though some of its content was co-constructed with the community. However, in block three I started to realize that automated non-human agents were also shaping my WordPress space. Google search that sorted and prioritized data for me obviously showed some things and concealed others. For instance, western publishers and speakers produced most of the content I encountered.

The notoriously famous for their commercial agenda Youtube and Ted Talks were among the top recommender systems I used. Presumably, the materials they offered were either pushed up by corporations or by other web users or by personalization algorithms. As J. Knox puts it, ‘because these systems enmesh automated, individual, and communal decision-making in highly complex, and usually hidden ways, the results cannot easily be reduced to the intentional agency of one human person (whether user or programmer), or non-human algorithm’. Hence, it would be fair to speak about ‘shared’ agency and ‘shared’ authorship (student-tutor-algorithms-community) in relation to my blog.

Interestingly, ‘digital nudging’ is a two-way street. Whilst various algorithms push me towards definite choices, my own ‘learning is learned by machine learners’(Knox et al, p.35). In other words, I was also teaching the algorithms during my explorations and could observe how their predictions became more accurate within time. This fact demonstrates the ‘co-constitutive relations between human and non-human in education’ (Knox, p.1).

Today I am planning to ‘cut the cord’ and disconnect all my accounts from the lifestream blog, thus losing my share of agency in the future of this learning space and granting it all to the Web.


Knox, J. 2015. Algorithmic Cultures. Excerpt from Critical Education and Digital Cultures. In Encyclopedia of Educational Philosophy and Theory. M. A. Peters (ed.)

Knox, J., Williamson, B. & Bayne, S. 2020. Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologiesLearning, Media and Technology, 45:1, 31-45, DOI: 10.1080/17439884.2019.1623251

Kulowiec, G. 2015. I’ve been thinking…It is time to revisit Jenkins’ Participatory Culture. Retrieved from:

Comment on Algorithmic Play by ialtukhova

That’s a fascinating piece of work, Jon! The auto complete is fun, many comedians build their shows around this algorithm. It was very wise of you to search both for a kind of neutral topic and a more politically coloured. I didn’t expect the results to be so ‘diplomatic’ either. They must be location-specific too. I tried the same collocations from here and there were zero matches.

You intrigued me by the fact that Spotify can ‘read you’. I feel I need to try it. Your idea to relate a similar algorithm to education is really trendy.This is exactly what recommender systems within LMSs or MOOC platforms try to do, not always successfully though. Since machines are insensitive to the context and human intent, I think it’ is still a long way to go until they’ll always ‘get it right for us’.

Thanks for sharing your discoveries with us, very insightful!

Comments for Jon Jack’s EDC lifestream

Comment on block 3 artefact – my Eurafrican Youtube algorithmic play by ialtukhova

I really loved your artefact, JB! It demonstrates how biased, discriminating and limiting technology can be. I was particularly impressed by the fact that personalization graded the language. This is where the notorious loop comes into play. Your English is not ideal, and it will stay the same, because you are never exposed to authentic speech. And who said it was not ideal after all?

It is also a deep thought that 1 account is not necessarily equal to one user or one identity, and this can be misleading. Inspired by your research, I made a few searches in my Youtube and saw that 99% of everything on offer are products where white people are involved. I’m sure that the same search in Africa would have given opposite results. So how barrier-free is the Internet space? It’s a fat question. Maybe, within time search engines will stick to the same principle as films in the US, when they will fight for diversity and include people of different gender, age, race and abilities in the same search, who knows? We are not talking about the best quality content coming at the top again.

Thank you for such a thought-provoking piece!

Comments for JB’s EDC lifestream

Comment on Algorithmic play artefact : teaching@digital podcast: by ialtukhova

Great podcast, David! I have never encountered such pop-ups before – is it how algorithms protect themselves from other algorithms?

It’s an interesting point that most tagging is still performed by people and the current autonomy of AI is slightly overblown. At my work, we also use algorithms and machine learning for some simple operations, and I have to admit, they are primitive and have a long way to go to understand context and people’s intents.

Perhaps the most prominent conclusion of yours is that the quality of content is secondary. Rather, it’s the network that defines your popularity on the web. This is indeed, something that is observed in the offline world too. Maybe, it can even be related to IQ and EQ, where the latter proves to be more important for your success.

Thanks for all these ideas! And the lovely soundtrack…

Comments for Teaching@DigitalCultures

Brief 9

This was the toughest week of the course for me: corona virus, switching to online education at work, working on the artefact.

While reading B. Williamson, I simultaneously tried to extend my understanding of new educational products and initiatives offered by the Silicon Valley and flashy ed companies, with which they aim to save the decaying traditional world of education, like TeacherMatch, Altschool,, computerized tutors, etc. As a teacher, I felt skeptical of the idea that technologists know which way the education should go. However, when in the middle of the week, the pandemic hit the country and the tech companies smoothly switched to online classes, whilst the largest university announced that they wouldn’t, because they didn’t believe it would work, I remembered the behavioral scientists who claimed that ‘most human decision-making is inherently irrational, habitual and predictable. (from J. Knox et al p.38)’…

I was also playing with the Google search algorithm within the task we had to perform. Hence, I tried to find out how google search operates, at least what’s on the surface, and what aims the company owners pursue. As an additional bonus, through my little research I had a chance to virtually visit 26 friends from different countries in this time of crisis.

The topic of digital nudges was exciting too. I was surprised to learn that AI predicted the outbreak of the virus, but the nudge was not strong enough. It means that there’s no trust in tech decision-making yet.

@SusanneMMacleod When your government refuses to start quarantine at university where several students proved positive, you really want AI to take important decisions instead of humans…

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