The view that data and analytics offer a new mode of thinking and a new model of discovery is at least partially rooted in the artificial intelligence and machine learning fields. Halevy, Norvig, and Pereira (2009) argue for the “unreasonable effectiveness of data” (p. 8), stating that machine learning and analytics can help computers to tackle even the most challenging knowledge tasks, such as understanding human language. Hey, Tansley, and Tolle (2009) are more bold in their assertions, arguing that data analytics represent the emergence of a new approach to science.(p. 1381-2).

Here we have a connection between the android/cyborg of section one, the post-human ethnography of section 2, and the algorithms of section 3.

There are many fields that Siemens covers, but the developments described in E-learning are less speculative, they are happening now in Universities.

E-learning: The growth of online learning, particularly in higher education (T. Anderson, 2008; Andrews & Haythornthwaite, 2007; Haythornthwaite & Andrews, 2011), has contributed to the advancement of LA as student data can be captured and made available for analysis. When learners use an LMS, social media, or similar online tools, their clicks, navigation patterns, time on task, social networks, information flow, and concept development through discus- sions can be tracked. The rapid development of massive open online courses offers additional data for researchers to evaluate teaching and learning in online environments (Chronicle of Higher Education, 2012). (p.1384).

I personally have an issue with using learning analytics to tell us anything except about the interface with machine learning. We can look at our data, considering bounce rates, load times, click throughs etc, and we can decide that students are using the pages as intended… or not. But we really can’t know anything about how much students learn or understand. Even if we test students, we can only know how students respond to the tests—from my own experience, this is often more useful to demonstrate that I designed the test badly, or phrased the questions ambiguously, than to demonstrate student’s understanding or recall. (Frequent small stakes questions are very useful to prompt students to recall information and reproduce it, helping them to reflect and aiding memory. But it’s the actions and reactions prompted by the learning interface but taking place outside of it, that really matters.)

Siemens also notes that this kind of data is “academic analytics” not “research challenges in learning”, that is, it “involved the adoption of business intelligence (BI) to the academic sector (Goldstein, 2005).” For this reason “Commercial tools are the most developed… Research and open analytics tools are not as developed” (p. 1836).

Siemens (2013) Fig 1, p. 1837.

Siemens reminds us that algorithmic or machine data is more useful when it is supporting “human effort”:

To be effective, holistic, and transferable, future analytics projects must afford the capacity to include additional data through observation and human manipulation of the existing data sets. (p. 3987)

I was horrified to read:

Curriculum in schools and higher education is generally preplanned. Designers create course content, interaction, and support resources well before any learner arrives in a course (online or on campus). Through the use of analytics, educational institutions can restructure learning design processes. When learning designers have access to information about learner success following a tutorial or the impact of explanatory text on student performance during assessment, they can incorporate that feedback into future design of learning content.

*begin rant*

Online teaching and blended learning requires hours of preparation that makes it hard to change a class mid-lesson. I now lecture without powerpoint, or with only images if possible, as then I can read the room, take questions, realise the lecture is not meeting the student’s needs, and draw on my knowledge to re-form the teaching content. In small group teaching, I do the same. One semester I taught four tutorials in a row: I would plan a single lesson, but each time I delivered it, I would amend, react, expand or contract parts of the class. I sometimes gave four radically different classes (because I wasn’t delivering pre-planned content, but the group and I were exploring the content together).

For this reason, the ‘personalisation’ of student learning is also problematic. Human beings are social animals, and we learn as a social interaction. This means that personalisation alone is insufficient for effective learning. We need to be able to alter teaching to support groups, and realise that students will behave differently in different cohorts. The personality of the teacher has been demonstrated to have an enormous influence on student engagement (Shelvin et al 2000, Williams and Ceci 1997, Murray, Rushton, & Paunonen, 1990), and the personality of other students in a class is also significant. While there are ‘lone wolf’ students, this does not invalidate the need to explore group dynamics, but rather demonstrated that there are multiple factors that should be explored in learning analytics for them to be useful for learners.

An empathetic human teacher doesn’t need to wait till after a tutorial to incorporate feedback into the design of learning content, but can (and should) be redesigning the learning content in the classroom. Every human teacher should be looking at “the impact of explanatory text on student performance during assessment” as they mark, and this should be, as I understand teaching (and have been doing for the last decade), incorporated into the next iteration. The question that 30% of students clearly misunderstood? The LMS quiz that was aced by native English speakers and tanked by international students? These things we are already quantifying without big data and without E-learning. In fact, we’re waiting for E-learning to catch up with the speed that an experienced teacher can manage with a whiteboard and marker, or document camera (another modern technology).

*rant the second*

More importantly,

Concerns about data quality, sufficient scope of the data captured to reflect accurately the learning experience, privacy, and ethics of analytics are among the most significant concerns (see Slade & Prinsloo, 2013). (p. 1392)

Privacy is, I think, one of the most significant issues with modern learning analytics. I used to teach a class that required the production of a weekly ‘learning journal’. However, the journal was only viewed twice in the semester. If a student decided to write in larger chunks, or individually, if they journalled before or after class, if they did it all in a big go just before handing it in… I didn’t know. I could tell the students who did it badly—and it was designed to help students reflect and engage as they went. But students had privacy to produce assessment at their own pace.

This meant that students didn’t have to tell me they were sick, they were busy at work, that their children were home from school with chicken pox. They did have to attend my tutorials, but that was 1 hour a week. Other than that, they could learn privately.

I work in blocks and then distribute my learning across the week though scheduling and back dating. I found IFTTT meant that learning intruded too far into my private space. I had to act to suit the assessment and the algorithm, rather than learn. I chose to learn.

A public blog means that I have to be public about my health, my busyness, my business. Or at least the markers of those interruptions are publicly available.

Siemens quotes two scholars writing in 1964, 50 years later, their concerns remain pertinent:

Ellul (1964) stated that technique and technical processes strive for the “mechanization of everything it encounters” (p. 12).
“Most of our institutions of higher learning are as thoroughly automated as a modern steel plant” (Mumford, 1964, p. 274). (p. 1395)

Seimens suggests:

The learning process is creative, requiring the generation of new ideas, approaches, and concepts. Analytics, in contrast, is about identifying and revealing what already exists. (p. 1395)

Ellul and Mumford might also remind us that the purpose of the mechanised plant is to repeat the same process over and over again, as quickly and consistently as possible. Humans, as I have argued above, are not very good at being consistent, and as Adorno and Foucault might argue, any attempt to make students into machine-goods is an act of oppression. What’s more, Foucault would suggest that the assessing gaze of the teacher is another form of coercion.

Unlike Facebook or Amazon, who track our clicks, absences and contributions to give us more of what we want, teachers judge our clicks, absenses and contributions against a regime and rubric of value judgments.

*rant trails off, need to go make tea*

Every semester, there are three weeks that are absolute hell: O-week to the end of week 2. Week 3 is busy, but less stressful. Every year, I make sure I see my friends before O-week starts, and then tell them I’ll see them again in a month.

This blog has had the same problem. It’s not that I haven’t been doing anything, but it’s been out of synch, late, or patchy.

I’ve updated the things I was supposed to have done, or had started but not published, in week 8 only this weekend, as we turn the corner into week 9. I managed a couple of tweets in the tweetorial (and neither of them had space for the hashtag, #fail).

I did have a fascinating conversation with Nicholas and Jeremy earlier:

https://storify.com/katrinafee/foucault-and-algorithms

I had trouble finding an algorithim I could play with, so after a few abortive attempts, I finally worked out I could look at Twitter’s Discovery timeline. I commented on Jin’s and PJ’s bogs.

Posting less often means that some of my posts have been longer. I’ve been continuing to document the places where I study (and increasingly, the food I eat as I study), including my first video:

Anyway, week 3 is coming up. Busy, but no longer crazy. Hopefully that means I’ll have a chance to catch up.

Hand, Martin, (2008) “Hardware to everyware: Narratives of promise and threat”, Making digital cultures : access, interactivity, and authenticity pp.15-42, Aldershot: Ashgate

Pages 15-19 are a great overview of some of the debates we’ve already covered elsewhere (I recognised some of the readings from IDEL, and some articles that Hand cites which cover similar content to Hannam et al (2006), Leander et al (2010) and Licoppe (2004)). This is a useful place to come back to when starting some of my own research.

First Generation Web studies: the 1990s.

Hand deconstructs the binary that “‘first generation’ Web studies” (1990s) constructed of ‘cyberspace’ and meatspace (19-20). The new world of ‘cyberspace’ was an imagined utopia: democratic, post-national (or trans-national), anarchic, interactive, globalised. (Later, he will show a second generation characterising this as a ‘de-democratic e-topia’, p. 32).

Hand suggests that governments perceive that

globally dispersed information represents a threat to traditional stragetegies of information ownership and policing (such as copyright, intellectual property, censorship, surveillance).

As Andrejevic (2013) and others argue, however, new forms of data enables greater control of information: greater censorship, greater surveillance, more draconian control of intellectual property and copyright. I regularly buy novels on my Kindle and then buy a second hard copy so I can loan it to a friend; I can only make 5 copies of a song I bought on iTunes and often lose older songs from too many versions ago; my employer is able to see every article I read, even the stuff I read wirelessly on my tablet in my lunch break; they are able to read the content of every piece of e-mail I send or recieve via my work account, even email I read and write from home.

Hand (2008) p. 23

All of this talk, on page 23-24, of the end of’ vertical’ governance drives me wild. Even in the most seemingly ‘top down’ totalitarian states, various kinds of networks and interactions were taking place. While broadcast communications may have seemed ‘vertical, hierarchical and one-directional’, they were being informed by multiple kinds of interaction, interferrance, and backchannel. The content of the BBC propagandist radio broadcasts during World War II, for example, (the subject of my PhD) was subject to reader surveys, commentary articles, reviews, and correspondence. Moreover, there was a lively analogue backchannel of theatrical reperformance, of in-person discussion, and of personal networks of correspondence. And this is just the things that we know about from archives: all kinds of unrecorded ‘multi-centred, networked and decentralized’ interactions were almost certainly going on. Even in Nazi Germany there is some evidence of this kind of interferrance (I am drawing both on my own research, and Fox (2006) here).

I am completely confused about the idea that it is the Net that will enable a participatory governement. I can’t quite think what people thought we were doing in the ‘old days': not going to sit in Parliament, not reading newspapers, not going to Town Hall meetings, not writing to the editor of the local paper, not printing out flyers, or door knocking, or signing petitions, or protesting. In the same way, I am confused by the argument that the Net enables a new participatory writing culture. I’ve ranted about this before. Hand later calls this ‘digital enchantment’ (p. 36).

I must read Castells, 1996, and 1997a. I think there is a very interesting connection between the trans-national cyberspace utopia, and the neo-liberal utopia of transnational corporations of

restructuring… through governmental efforts to deregulate, privatize, and dismantle the social contract betweeen capital and labour. p. 25.

Hand addresses some of the concerns I raise here in his next section (pp.29-30). For example, he characterises Borja and Castells’ (1996) argument as ‘a fusion of the Greek polis with the technologies of the 21st century’ (29) and cites Brown (1997) linking networked surveillance to Foucault’s panopticon prison.

Finally: on the one hand  Poster 2006 suggests that ‘digital conditions of culture mean thte the creation of works, their unlimited reproduction, and infinite distribution are functions at the disposal of everyone who has access to networked computers’. On the other hand, as pointed out above, DRM. (Hand does talk about DRm, on p. 37). Also, something to do with Borges and the Infinite Library. (I found this fascinating pre-Kindle blog from 2009 while searching for another article (some sort of think-piece in something like the New Yorker, I read some years ago, that I now can’t find.) I’m sure this is significant–even with Google things can be lost).

Second-generation Web studies: the 2000s. 

Digital information does not circulate outside of material structures. p. 28

The internet is incredibly slow in Australia, even in cities. In Melbourne, some suburbs now have fibre-optic cables, but where we live it’s still working on an old telephonic network of copper wires. In rural Australia it is even more problematic. (And the roll out of a National Broadband Network has been stalled for political reasons.) (See hand pp. 33-4 discussing such ‘social informatics’ in the US, UK and Canada. The catagories used for Canada (Erickson, 2002) are most useful to describe the Australian experience).

The imminent explosion of the Internet of Things promises to make this more the case than less (and also underlines some of the inherent risks of a network that is not purely imaginary).

Hands (2008), p. 30

At this moment, Hands uses the term ‘Orwellian': and it is instructive to remember that one of the most terrifying aspects of Orwell’s novel 1984 was the way that as well as  you watching the television, the television watched you.

Bauman’s ‘liquid modernity’ (2000) is invoked here, and Bauman reminds us that web-interactivity is hugely asymmetrical. The 1:10:90 rule (see van Mierlo (2014)) reminds us that even in apparently ‘democratic’ and interactive platforms like forums, wikis and social media, only about 1% of users will actually create content; most people will ‘lurk’, or consume the content ‘pure and unalloyed watching is thier lot’ (Bauman, 1998, p. 53)–their contribution limited to upvoting, liking, or just being recorded as clickthroughs. The other 10% are ‘curators’, collecting and sharing the content  created by the 1% out to the consuming 90%. See p.39 for a discussion of how this maps onto digital citizenship vs ‘the “push-button” nature of digitally mediated political life’ (Street 1997).

Like Bauman, Dawson and Foster (1998) agree with Andrejevic (these are the ‘others’ mentioned above):

new technologies actually increase the possibilities of centralized control for some, maintaining existing consertvative sociopolitical practices, rather than undermining or disrupting them. p. 31

This ‘technophobic’, pessimistic view leads into a series of ‘moral panics’ (see Danah Boyd’s work on networked teens, as well as the IoT malware panic linked above).

I’m once again confused through by the historicity of the arguments. The dystopian views of the future imagines ‘monadic citadels’ with ‘neo-feudal’ (Umberto Eco) ghettos (p. 33). This is apprently caused by ‘digital technologies… stripping away the mutual face-to-face bonds of pre-modern forms of community and civility’ (p. 33). PRE-MODERN IS FEUDAL, GUYS. Pre-modern can be good or bad, feudal can be good or bad–I don’t care, but you can’t have your historical cake and eat it too.

I would like to see some discussion of digital citizenship that takes into account major hacks and leaks: most notably Wikileaks (though I realise this only came into global prominence 2 years after Hand’s article was published).

On page 38, Hand finally acknowledges the ‘line of thought weaving through Heidigger, Benjamin and Baudrillard’ (Taylor and Harris, 2005). The age digital reproduction, we might see, as an age of ‘atomized anti-society of privitized consumers of inauthentic simulacra’–concerns we see actively explored in eighteenth-century plays, Victorian novels, 1920s essays, and mid-century films.

***

Unlike earlier live blogs, I wrote this is a circular way, interspersing new references from the article into earlier paragraphs. Hand’s article was subtly parallell, and dialogic, so it made sense to write about it in a mix of referrings back (lots of ‘above’s, which I briefly considered linking as anchors), and interpolating new text.

 

Sian Bayne (2015) What’s the matter with ‘technology-enhanced learning’?, Learning, Media and Technology, 40:1, 5-20, DOI: 10.1080/17439884.2014.915851

I remember enjoying the Bayne articles that I read last year, so I’m going into this with some expectation of enjoyment. I’m also aware that this is a blog post with a primary audience of … maybe a dozen people, one of whom is the author of the article. I wonder how much that is going to influence my reading?
[I am using ‘reading’ here in the technical ‘critical analysis put down in writing’ sense; rather than the ‘actual looking at and understanding the words on the page’ sense. This is my literary training coming through, but also the fact that I’m listening to jazz on the radio–where a performance of a composition can be called a ‘reading’ (as Garry Koster does on one of my favourite jazz radio shows). ]

***

Anyway, on to the article!

Getting started

The first paragraph is interesting to read in the context of the change of the name of this course from ‘MSc in E-Learning’ to ‘MSc in Digital Education’. I certainly, in Australia, have not seen the term ‘Technology-Enhanced Learning’ used–I would assume it was a particularly tech-heavy example, perhaps using robotics, or the Occulus Rift. Here, I would use ‘e-Learning’ in general contexts, or something like or ‘instructional design’ to talk about specific jobs in very industry-centric contexts.

I frame the paper around three core questions: What is wrong with ‘technol- ogy’? What is wrong with ‘enhanced’? And finally, what is wrong with ‘learning’? I draw on three different frameworks in addressing each question: first I use insights from science and technology studies to draw into question what we mean by ‘technology’ within this context; I then adopt a position from critical posthumanism to look again at ‘enhancement’; and finally I refer to Biesta’s (2005) work on ‘learnification’ to emphasise what might be problematic in our too-ready use of the ‘language of learning’. (p.8)

Bayne attacks the issue from a multitude of angles. This is effective in an article intended to demonstrate a range and variety of weaknesses, not all of them fatal. From the abstract, I know her intention is to suggest “that we need to be more careful with, and more critical of, the terminology we adopt to describe and determine the field.”

Were Bayne’s intention to make a case for a usable alternative, or to propose that TEL be abolished, this ‘promiscuous’ approach would be more problematic. I’m not sure there is any ‘right’ answer here, though, so a messy ‘cluster’-ing is about right. It is also an example of what Braidotti has suggested, in The Posthuman,  will be the new post-Humanities, ‘web-like, scattered and poly-centred’ (p.164).

What’s wrong with ‘technology’?

In Haraway’s ‘A Cyborg Manifesto’, she suggests that ‘writing is pre-eminently the technology of cyborgs’. I’m going to use this to read this section.

Haraway argues:
‘Writing is pre-eminently the technology of cyborgs, etched surfaces of the late twentieth century. Cyborg politics is the struggle for language and the struggle against perfect communication, against the one code that translates all meaning perfectly, the central dogma of phallogocentrism. 

Fenwick, Edwards, and Sawchuck (2011) (qtd in Bayne) are arguing something similar:
Learning is an effect of the networks of the material, humans and non-humans, that identify certain practices as learning, which also entails a value judgement about learning as something worthwhile. This teaching is not simply about the relationships between humans, but is about the networks of humans and things through which teaching and learning are translated and enacted. (6)

Learning and technology have been intertwined for millenia. The invention of writing now seems to us ‘natural’, but was of course an extraordinarily disruptive technology. The invention of new kinds of architecture that enabled more people to hear the message (from amphitheatres to lecturns to raked seating); the invention of the blackboard, or the mnemonic…

Or this:

Which kind of suggests we don’t get what ‘learning’ is.

But first we have to deal with ‘enhancement’. 

Enhancement suggests that the underlying thing is generally good, but can be made better, it is ‘simply open to a little improvement and further consolidation via the ministration or utilisation of technology’ (Bayne 2015, p. 11).

What counts as ‘improvement’ is, as Hauskeller (2013) points out, highly context- dependent:
We always need to ask what a better performance in a specific context is good for and, of course also for whom it is good . . . The context determines whether a change is, overall, an enhancement or not. That is why forgetting can be as much an enhancement as remembering. (14–15)

It also suggests that technological intervention improves things, by default. The initialism TEL could be written out ‘technology-enchanced learning’. The hyphen links the adjectival phrase which modifies the noun ‘learning’. In a sentece, it is ‘learning’ that will be the grammatical subject.

Okay, finally, what’s wrong with ‘learning’?

In most instances, when we speak of ‘TEL’ we are in fact referring to technology enhanced teaching, and to institutional goals, rather than to the aims or cognitive gains of individual learners  … To reduce ‘education’ to ‘learning’ prevents us from asking critical questions about how educational goals are negotiated and how its power relations are constituted. (p.15-16)

The discussion here all still rather assumes that it is the education-machine that is getting in the way of learners learning, and not asking some even more basic questions. I quite understand that this isn’t the point of the article, but they are questions I have.

What is learning the opposite of? Is it the opposite of ‘ignorance’ or the opposite of ‘illiteracy’ or the opposite of ‘teaching’?

Is learning always a good thing? We like learning, especially in higher education, and have often made huge sacrifices to have it. I often wonder if those sacrifices are worth it. What disciplinary ground have I gained (and yes, I am using Foucault’s militarised, bodily, training image on purpose), what other kinds of movement and knowing and being have I lost?

Is learning a thing where we get more skills and information? Or more wisdom? Or more kindness? Is there a point where we have enough knowledge (there is ‘information overload’, can there also be a ‘wisdom overload’)?

How do we count what is learning, what is learned, how well it is learned? Might these forms of counting mean that others can be discounted?

Conclusions
Bayne ends:

It is time to re-think our task as practitioners and researchers in digital education, not viewing ourselves as the brokers of ‘transformation’, or ‘harnessers’ of technological power, but rather as critical protagonists in wider debates on the new forms of education, subjectivity, society and culture worked-through by contemporary technological change. (p. 18)

Returning to Haraway:

That is why cyborg politics insist on noise and advocate pollution, rejoicing in the illegitimate fusions of animal and machine. These are the couplings which make Man and Woman so problematic, subverting the structure of desire, the force imagined to generate language and gender, and so subverting the structure and modes of reproduction of ‘Western’ idendty, of nature and culture, of mirror and eye, slave and master, body and mind.

***

To Read:

Biesta, Gert. 1998. “Pedagogy without Humanism: Foucault and the Subject of Education.” Interchange 29 (1): 1–16.

Biesta, Gert. 2005. “Against Learning. Reclaiming a Language for Education in an age of Learning.” Nordisk Pedagogik 25 (1): 54–66.

Biesta, Gert. 2006. Beyond Learning. Democratic Education for a Human Future. Boulder, CO: Paradigm Publishers.

Biesta, Gert. 2010. Good Education in an Age of Measurement: Ethics, Politics, Democracy. Boulder, CO: Paradigm Publishers.

Biesta, Gert. 2012. “Giving Teaching Back to Education: Responding to the Disappearance of the Teacher.” Phenomenology & Practice 6 (2): 35–49.

Biesta, Gert. 2013. “Interrupting the Politics of Learning.” Power and Education 5 (1): 4–15.