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Final Reflection. Week 12

Reflection: Looking through a lens (Image: @bodzofficial Instagram)

A hundred years after Dewey published his book Democracy and Education (1916) championing education as a communal process, I wonder how the process of being a scholar of education in the digital age compares now to how it did then. The key principle of reflection in Dewey’s theory is still relevant today. Dewey claims that ‘[e]ducation, in its broadest sense, is the … social continuity of life.’ (p 4), since we live so much of our lives online it makes sense that educational communities have evolved and that we study them there.

The pressure on academics to publish using different mediums shows that scholars are required to do much more than thinking and writing alone. They are tasked with ‘new ways of working and new ways of imagining [themselves]’ (Fitzpatrick, 2011, p 3). This was certainly true in the use of a lifestream blog as a scholarly record. The constant pressure to be creative by publishing in a range of mediums and working quickly to meet tight deadlines is what it means to be a scholar in a digital world.

In Cybercultures we discussed how discourse contributed to instrumentalism (Bayne 2014) in relation to digital education. The discourse around ‘enhancement’ evolved into how our bodies are being changed by technology this was echoed in my visit to a Learning Technologies Conference on Health Education. We looked at how we are no longer limited to text when trying to portray scholarly thought (Sterne 2006) and I was able to do this by creating digital artefacts. It was interesting to see how other participants were able to construct meaning in ways I did not anticipate.

Community Cultures allowed us to see how educational communities are constantly evolving. The Massive Open Online Courses in which we participated supported our roles as researchers and students. Here we could see how digital education is changing and how cMOOCs have morphed into more individualistic xMOOCs over the last few years and have evolved to be smaller, less focused on community and more geared towards promoting participating universities and encouraging employability.

In Algorithmic Culture we reviewed how algorithms relate to pedagogical issues like sequencing, pacing and goal setting and evaluation of learning (Fournier 2014) and how these algorithms help our machines ‘remember’ us thereby determining the content we access. The discourse around Learning Management Systems (LMS) and their effectiveness to capture data (Siemens 2014) about students and their learning was reminiscent of discourse mentioned in Cyberculture.  The way in which institutions track and monitor students by using data echoed the issues around discrimination and invisibility I looked at earlier in the course.

I was daunted and anxious about my lifestream at the beginning of the course; having to do so much, so publicly was overwhelming. Seeing what other people did also inspired me. Having a reflective piece of work to map my learning is helpful as I can see how my development in my lifestream progressed. I feel it highlights not only my reflection (Dewey 1916), but my creativity and my technical skill. It has given me a new way of imagining myself as a student (Fitzpatrick 2011).

References

Bayne, S. (2014). What’s the matter with ‘Technology Enhanced Learning’? Learning, Media and Technology 40(1): pp. 5-20.

Dewey, J. (1916). Democracy and Education: An Introduction to the Philosophy of Education. Retrieved: 4 April 2017. https://s3.amazonaws.com/arena-attachments/190319/2a5836b93124f200790476e08ecc4232.pdf

Fitzpatrick, K. (2011). The Digital Future of Authorship: Rethinking Originality. Culture Machine 12: pp. 1-26.

Fournier, H., Kop, R. and Durand, G. (2014). Challenges to Research in MOOCs. Journal of Online Learning and Teaching, 10(1), pp. 1–15.

Siemens, G. (2013). Learning Analytics: the emergence of a discipline. American Behavioral Scientist, 57(10): pp. 1380-1400.

Sterne, J. (2006). The historiography of cyberculture. In Critical cyberculture studies. (New York University Press.) pp. 17-28.

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What to do? Week 11

Could I use this as a post-human metaphor?

I have enjoyed my blog more as I have been going through it. I feel like it is something I can be proud of but I’m still struggling with what I would like to do for my final assignment.

I am not one of these people who has an idea of what they want to write about half way into the course. This week I’ve trawled through my blog to find inspiration. I was hoping that something that I’d written or posted would set my imagination alight and I would find a topic, formulate a question and criteria on which I would like to be graded. I thought by the end of the week I would least have a topic. Unfortunately, I don’t. I’ve looked through other’s blogs and have seen the amazing creativity of my peers! But I’m still wondering what to write.

There’s PDF on how to develop academic writing and I plan to start doing some of the exercises to formulate my question and help develop my ideas. I can’t help but be reminded of the Hemmingway quote, ‘There is nothing to writing. All you do is sit down at a typewriter and bleed.’ I’m sure I could work wonders with that metaphor and post-humanism, especially considering we covered the body and its relation to technology in Block 1. The Dory meme is to remind me what to do. All the while also thinking that writing isn’t the only option of submitting my work. Alas, I feel overwhelmed again.

I saw that Audrey Watters was at Edinburgh, I really wish I could have attended her talk! There’s always something magical about being able to experience something like that in context. Maybe I would have found the inspiration I need. Most of my feed was in relation to my assignment and blog. I just need to write now.

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Do we really need to measure everything? Week 10

It is seldom if ever that my professional life and my studies amalgamate so whole-heartedly. I don’t really know if this is a good or a bad thing because inevitably the short snippets in which my studies present surpass my professional life and leave it behind while I’m still grappling with the issues at hand.

Last week I posted about going on training on Moodle analytics. I thought this would really help me make sense of one of the courses I work on as well as contribute to my understanding of this course.

Unwieldy data, how do we manage it?

How does one make sense of a course that has over 2480 pages and 12 thousand students enrolled on it?

The Tweetorial was much easier to manage but it did make me wonder if there was any purpose to recording students’ activity in open educational spaces. How can we really know that they are engaged? What struck me in our hangout this week is that one of the participants had a different handle and gender than what I have come to recognise. Since he was not in the tutorial as himself, does that mean he didn’t participate?

I went to London and South East Learning Technologies Conference for Health Education. A lot of the discourse centred on ‘technology enhanced learning’. The first seminar I attended was on wearable technology. The speaker spoke of physiolytics, the study of the information retrieved from a device worn on one’s body such at a staff ID card and Fitbit. The doctor presenting spoke of a “smart condom” that measured one’s performance and then fed that information back to an app on a phone. I had to wonder at this point whether man’s obsession with measuring his performance has gone a step too far.

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Red, amber, green: Learning analytics. Week 9

Is there any benefit to rating students’ success?

I started this week still stuck on how algorithms worked and how they might be seen to influence education. Which lead me to send my first tweet out about asking whether database results could shape research. I tweeted my question and it was in this vein of thought I went looking for any academic papers that could support what I suspected. There were a lot about  bias but I found an example which I saved on Diigo. This article focused on some of the issues around systematic reviews with regards to database searches. It prompted my thinking on how research could be adversely affected by search results but more importantly highlighted the human element of how important information literacy is for scholarly processes.

It was only during the tweetathon I finally felt like I had joined the party with regards to how data and learning analytics play a role in shaping education, but it was quite difficult making sense of what was going on. I felt I was more active than I demonstrated.

I pinned a graphic from Pinterest promising that data mining and learning analytics enhance education which was reminiscent of the instrumentalism around discourse (Bayne 2014) in Block 1.

The TED talk presented how big data can be used to build better schools and transform education by showing governments where to spend their money in education. It made me realise that, when looked at quite broadly, data can revolutionise education.

Finally, I reflected on the traffic light systems that track and rate students, something I’d like to explore further. Ironically, on the first day of week ten, while I was playing catch up in Week 9, I attended some staff training on Learning Analytics, ‘Utilizing Moodle logs and recorded interactions’, where I was shown how to analyse quantitative data to monitor students’ use and engagement.

Bayne, S. (2014). What’s the matter with ‘Technology Enhanced Learning’? Learning, Media and Technology, 40(1): pp5-20.

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Co-constructed ecosystems Week 8

ecosystem
Photo: Flickr @giveaphuk

I started my week trying to find out what exactly algorithms were. I had a vague understanding that they were part of the coding that looks for patterns and then changes functionality of certain online spaces, usually to do with shopping and social media. I’ve mostly come across them through social media feeds where influencers are usually advocating for you to turn notifications on about their posts. What surprised me when I started looking for information about how algorithms work, almost as often information on how to manipulate them popped up.

I was trying think about how algorithms may influence education and where they might fall short when I stumbled upon the amazing Joy Buolamwini. She highlighted the real consequences of how having a lack of diversity in programming can impact technology in ways we do not expect. It was evident from her experience that technology rendered her invisible by not being able to read her features. I wonder how many other invisibilities are not yet evident.

We met for our weekly Skype group and some of the bigger themes emerging from that conversation were about how algorithms are used for control and surveillance. We wondered if this might cause students from certain, ethnic, socio-economic backgrounds to be marginalised.

The TED talk on How algorithms shape our world. Was really insightful on how algorithms link. The ‘ecosystem’ metaphor Slavin used echoed Active algorithms: Sociomaterial spaces in the E-learning and digital cultures MOOC (Knox 2014).

It was in this vein I found Hack Education’s article about the Algorithmic Future of Education. Watter’s highlights how the marketization of education and how important ‘care’ is when dealing with students.

I rounded the week off working with Stuart by comparing how algorithms work in different online spaces.

Knox, J. 2015. Algorithmic Cultures. Excerpt from Critical Education and Digital Cultures. In Encyclopedia of Educational Philosophy and Theory. M. A. Peters (ed.). DOI 10.1007/978-981-287-532-7_124-1

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Communities. Week 7

The Indignados used social media to mobilise. Photo: @thecommenator

I attended a Digital Cultures seminar, The People’s Memes: Populist Politics in a Digital Society held at King’s College London. There were interesting comments about how political movements developed out of what were the inequalities and disenfranchisement felt by those outside of the political elite. Digital communities like the Indignados who were the birthplace of Podemos, a Spanish party to form a more accessible alternative. What I found particularly interesting about the research being done in this field, is that much of the hierarchical systems that these new movements were responding to with regards to inequalities and inaccessibility, is now being replicated online. I thought this example linked well to the Knox (2015) paper and how technology is seen to become ‘anti-institutional and emancipatory’ but in fact just continues to replicate what is already present in society.

After receiving feedback, I commented on other participants’ blogs, trying to get inspiration so I could link more feeds with IFTTT to my lifestream.

On Wednesday, a few of the participants had a Skype chat to share what feedback they had received about their lifestream. It was here, talking to others, that I realised that a narrative for my lifestream synthesis was more about what I had posted and less about what I was thinking.

This interaction with my peers and my dabbling within my MOOCs lead me to question how communities are built? Which is why I bookmarked the Abbott (1995) paper Community participation and its relationship to community development on Diigo.

Most experiences of MOOCs seemed to be negative which lead me to question if they are sustainable.

Finally, I browsed the ethnography posts within MSCEDC so get inspiration for exhibiting my own.

References

Abbott, J (1995). Community participation and its relationship to community development. Community Development Journal 30(2): pp158-168.

Knox, J. (2015). Community Cultures. Excerpt from Critical Education and Digital Cultures. In Encyclopedia of Educational Philosophy and Theory. M. A. Peters (ed.). DOI 10.1007/978-981-287-532-7_124-1

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Lessons learnt: What micro-ethnography has taught me about research. Week 6

So many MOOCs

I persevered with the Internet of Things (IoT). I tried to become part of the community and searched for meaning in the comments. I did not find anything that was able to inspire me. I was bored and found myself avoiding the course. I did some of the activities to try and gain a better understanding but ultimately focused on participation or lack thereof. Whilst reading the comments in the IoT, I struggled to make sense of what was written. I was frustrated. I did not interact with others or actively participate in situated learning and I was not interested enough to apply critical perspectives to my participation (Stewart 2013).

I wondered why I found it so difficult to engage. I decided to try another course. I enrolled on to two other MOOCs; FutureLearn’s Teaching Literacy Through Film (TLTF) and Coursera’s Writing in English at University.  I chose these because I have knowledge of the content and I could focus more on the community and participation. I realised quickly that Writing in English at University was a poor choice and not ‘open’ as participants are required to pay for interaction.

TLTF appealed to me as I have used films in class to assist with literacy. I noticed a difference in the course almost immediately, it was more transparent, participants were encouraged to share personal information, there was discussion between participants, the atmosphere was friendlier and community more generous with their interaction. I was surprised to find that I wanted to be there. It did not feel like a chore unlike the IoT.

By changing MOOCs I discovered:

  1. being engaged with what we are researching makes it so much more meaningful
  2. if something is not working while you research, try something new
  3. communities can be both selfish and generous
  4. by comparing and contrasting information, we can make sense of it

Stewart, B., (2013). Massiveness + Openness = New Literacies of Participation? MERLOT Journal of Online Learning and Technology, 9(2), pp.228–238.

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Community in the private space. Week 5

Community within the same space? Photo: @The Mirror

I’ve been delving deeper into the Internet of Things (IoT) MOOC and I find it ironic that a course essentially about the communication between devices doesn’t champion communication between participants. I am surprised at how little interaction there is between participants. It is difficult to connect with others as there isn’t any social media space connected to the course. It seems the only contact people have with each other is if they ‘like’ a comment, to which doesn’t happen very often. The most ‘likes’ I’ve seen on a post, so far, is four. Participants have the ability to reply to a comment and while this occasionally does happen it seems to happen in a void where people who posted the first comments don’t reply to the thread. There is such limited potential to develop autonomous channels of communication (Stewart 2013) that much of what is communicated is repetitive and limits inquiry outside the content presented on the course.

This apparent lack of communication has led me to question the whether educational communities can be established in an xMOOC. I wonder how communities might be built without extended connectivity. How do those communities go about interacting if they aren’t assisted through the platform via social media?  Is FutureLearn as the private platform, where the IoT MOOC is hosted, discouraging communities from connecting? Social media sites like Twitter are not being exploited, this makes connecting with others more difficult. The limited contact participants have with each other does not promote an environment of community learning.

It is also very difficult to find people with whom to connect. Comments are presented in Facebook wall fashion but it’s quite difficult to see how active a person has been. There is no search function for why they might be interested in the topic. There is no way of knowing whether they a product developer, researcher, business, or just interested in finding out more? Even once ‘following’ another participant there is no way of directly communicating with them.

Geographical location seems important for the course content because the capabilities of connectivity for the IoT is dependent on connectivity. Again, there is no way to search for people who might be able to offer suggestions or alternatives for specific geographic locations because finding out where people are based is impossible unless they put it in their profile, which most don’t.

As a participant, I have a feeling of being blind to the community in IoT because can’t see individuals. It is similar to standing in a crowded station blindfolded. I can hear the announcements (from the teacher), I can hear specific comments from other participants, but don’t know how they fit into the greater context or whether there are any real conversations happening.  Which leads me to question whether people at the same train station can be considered part of a community? Ultimately they have the same place/space in common, they all will have travelled by train but eventually they will be travelling to different destinations, probably with their headphones on and trying to avoid eye contact.

FutureLearn (2017). The Internet of Things. Retrieved: 6 February 2017. https://www.futurelearn.com/courses/internet-of-things/

Stewart, B., (2013). Massiveness + Openness = New Literacies of Participation? MERLOT Journal of Online Learning and Technology, 9(2), pp.228–238.

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Finding meaning in things or flings. Week 4

How do we construct meaning in online exchanges?

How do we express what we really mean? Especially when there is much depth to the topic we are discussing. The expression of depth and meaning was quite challenging when making our visual artefact. This is evident through the conversations that have subsequently transpired. The intention of the creator is not always the same as the interpretation of the reader or viewer. Getting meaning across is no small feat! I struggle with this when writing academically and it was exacerbated further when I tried to portray my critical thinking in a picture.

It was while I was grappling with ‘online interaction’, ‘initial assumptions’ and ‘developing nuanced understandings of the online social world’ (Kozinets 2010) of participating in the online community that is Education and Digital Cultures, that I had a discussion with two other participants that left me utterly perplexed. Perhaps this is what Kozinets (2010) meant about ‘interpretive social cues'(p 24) developing between communities. The discussion is below:

What ultimately left me perplexed is how a conversation started by discussing MOOCs ended up with ‘[t]he sex industry’ being ‘an early adopter of new tech’. Did I miss something? Some earlier conversation where this would make sense? Is this part of the heirachy of our own online community of which I am not a part? Perhaps I’m looking too hard for meaning and this is simply an effort to build rapport in our online community. It’s lead me to question; how do we construe meaning from online exchanges that are less than 140 characters long? Is what we are trying to express being accurately conveyed? Do our readers/viewers understand what we mean? How do we record and interpret qualitative data objectively if a) the meaning is not clear; b) if we are part of that community ourselves?

I suppose what I’m wondering, as we head off to do our own ethnographic studies in our MOOCs, is how to construct meaning out of comments and behaviour online when it is clear that we cannot take all information we see at face value. I look forward to finding out.

Kozinets, R. V. (2010) Chapter 2 ‘Understanding Culture Online’, Netnography: doing ethnographic research online. London: Sage. pp. 21-40.

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Prevent (and) discrimination. Week 3

Students protesting Prevent Duty Photo: @BeMedia

I’ve been grappling with how Donna Haraway’s utopian metaphor of the cyborg relates to our relationship with technology and contemporary politics, as well as how it fits in with digital education.

If we are to live as cyborgs as Haraway’s metaphor suggests, we cannot divorce our own nature and history from that of our future selves. This seems implausible, unachievable and very much like an allegorical fairy tale from bygone times. But much like those fairy tales about power and loss, we see the dominations of ‘race’, ‘gender’, ‘sexuality’ and ‘class’, by those in positions of power, evident throughout our technological world.

There are countless examples of oppression in relation to technology. There are examples of the disparities; of how wealthy (white) companies still exploit poor (black) countries and their people for their resources without supporting the connectivity needs of those countries. Since The Cyborg Manifesto was published we have seen the gender gap in careers in technology widen. The digital divide is persistent in developed countries with regards to location and income and ethnic background; while undeveloped countries struggle to find alternative ways to access information with the lack of infrastructure.

In relation to education, Watters in her article Ed-Tech in the Time of Trump gives examples of how universities can use data to carry out surveillance on students and staff. She demonstrates how this happens through the collection of data. Using data, universities, big companies, governments and powerful individuals are able to control what we see, where we go and how we access information. This is evident in the UK with the Government’s Counter-Terrorism Strategy and how universities are tasked with monitoring extremism with the Prevent Duty agenda. Students are being monitored more than ever before.

The ‘ubiquity’ and ‘invisibility’ of the cyborg that Haraway dreams of is simply not possible because the technology and the spaces that we inhabit when online, have been taught to recognise us. Technology has been taught to read us, tasked to find out what we like, see what we look like and with whom we engage. It knows what we buy, sell, watch, read, and search for. It knows where we worship and who we love. It knows us. Most importantly technology has been taught to remember this information, this information then shapes our experiences online.

The control universities, companies and governments have over our information perpetuates the injustices and exclusions that occur in the physical world. If individuals are not aware of the information that is being collected, and of how that information is being used, they could marginalised without knowing it.

Haraway, D (1991). “A cyborg manifesto” from Bell, David; Kennedy, Barbara M (eds), The cyber cultures reader pp.34-65, London Routledge

Watters, A (2017). Ed-Tech in a time of Trump. Retrieved: 6 February 2017 http://hackeducation.com/2017/02/02/ed-tech-and-trump