Agoraphobia and the modern learner

Abstract:Read/write social technologies enable rich pedagogies that centre on sharing and constructing content but have two notable weaknesses. Firstly, beyond the safe, nurturing environment of closed groups, students participating in more or less public network- or set-oriented communities may be insecure in their knowledge and skills, leading to resistance to disclosure. Secondly, it is hard to know who and what to trust in an open environment where others may be equally unskilled or, sometimes, malevolent. We present partial solutions to these problems through the use of collective intelligence, discretionary disclosure controls and mindful design.

Address of the bookmark: http://www-jime.open.ac.uk/jime/article/viewArticle/2014-03/html

Learning in an introductory physics MOOC: All cohorts learn equally, including an on-campus class | Colvin | The International Review of Research in Open and Distance Learning

Thanks to Tony Bates for pointing to and providing a fine review of this interesting article which shows evidence of learning gain in people who were taking an xMOOC.

I have little to add to Tony’s comments apart from to mention the very obvious elephant in this room: that the sampling was skewed by the fact that it only considered considerably less than 10% of the original populace of the MOOC that actually got close to finishing it. It is not too surprising that most of those who had the substantial motivation demanded to finish the course (a large percentage of whom were very experienced learners in related fields) actually did pretty well. What it does not tell us is whether, say, a decent open textbook might have been equally or more effective for these manifestly highly motivated and proficient students. If so, it might not be a particularly cost-effective way of learning.

The study does compare performance of a remedial class of students (ie that had failed an initial course) who received plentiful further face to face support with that of the voluntarily subscribed online students. But the authors rightly note that it would be foolish to read anything into any of the differences found, including the fact that the campus-based students seemed to gain nothing from additional remedial tuition (they may be overly pessimistic about that: without that remedial effort, they might have done even worse) because the demographics and motivations of these students were a million miles removed from the rest of the cohort. Chalk and cheese.

One other interesting thing that is worth highlighting: this is one in a long line of articles focusing on interventions that, when looked at closely, suggest that people who spend more time learning learn more. I suspect that a lot of the value of this and indeed many courses comes from being given permission to learn (or, for the campus students, being made to do so) along with having a few signposts to show the way, a community to learn with, and a schedule to follow. Note that almost none of this has anything to do with how well or how badly a specific course is designed or implemented: it is in the nature of the beast itself. Systems teach as much as teachers. The example of the campus-based students suggests that this may not always be enough although, sadly, the article doesn’t compare the time on task for this group with the rest. It may well be that, despite an extra 4 hours in class each week, they still spent less time actually learning. In fact, given a prima facie case that these students had already mostly demonstrated a lack of interest and/or ability in the subject, then even that tutorial time may have not been dedicated learning time.

A small niggle: the comparison with in-class learning on different courses conducted by Hake in a 1998 study, which is mentioned a couple of times in the article, is quite spurious. There is a world of difference between predominantly extrinsically motivated classroom-bound students and those doing it because, self-evidently, they actually want to do it. If you were to extract the most motivated 10% of any class you might see rather different learning patterns too. The nearest comparison that would make a little sense here is with the remedial campus-bound students though, for aforementioned reasons, that would not be quite fair either.

Little or none of this is news to the researchers, who in their conclusion carefully write:

“Our self-selected online students are interested in learning, considerably older, and generally have many more years of college education than the on-campus freshmen with whom they have been compared. The on-campus students are taking a required course that most have failed to pass in a previous attempt. Moreover, there are more dropouts in the online course (but over 50% of students making a serious attempt at the second weekly test received certificates) and these dropouts may well be students learning less than those who remained. The pre- and posttest analysis is further blurred by the fact that the MOOC students could consult resources before answering, and, in fact, did consult within course resources significantly more during the posttest than in the pretest.”

This is a good and fair account of reasons to be wary of these results. What it boils down to is that there are almost no notable firm conclusions to be drawn from them about MOOCs in general, save that people taking them sometimes learn something or, at least, are able to past tests about them. This is also true of most people that read Wikipedia articles.

For all that, the paper is very well written, the interventions are well-described (and include some useful statistics, like the fact that 95% of the small number that attempted more than 50% of the questions went on to gain a certificate), the research methods are excellent, the analysis is very well conducted, and, in combination with others that I hope will follow, this very good paper should contribute a little to a larger body of future work from which more solid conclusions can be drawn. As Tony says, we need more studies like this.

Address of the bookmark: http://www.irrodl.org/index.php/irrodl/article/view/1902/3009

Political Polarization & Media Habits | Pew Research Center's Journalism Project

The Pew Research Center is responsible for some of the most fascinating and well-conducted research about America and Americans today. In this study, they looked at the relationships between political learnings (conservative vs liberal) and media. It is packed with fascinating details: a lot of the media have picked up on the rather limited range of news channels consumed by those with strong conservative leanings, the polarized trust of many news outlets, and so on. This is not surprising because anything that makes claims about you or your competitors will likely excite interest. But what most fascinates me is the way that social media (Facebook in particular, the generality and ubiquity of which tends to make it a more popular source for news than most other social media, at least in general) contribute to the polarizing effect. Notably, Conservatives tend to see fewer dissenting voices among their feeds. This is not surprising because, though self-reportedly more likely to come across dissenting views,  liberals show a greater tendency to defriend people who express conservative views. The self-organizing network effect caused by this double whammy makes for some dangerous filter bubbles, especially if the main alternative sources of news for American conservatives then appear to be Fox News and Rush Limbaugh.

The trust spectrum is interesting, especially at the extremes. Buzzfeed is trusted by no one, while the Wall Street Journal is trusted by all four of its remaining subscribers. I’d say that it is mighty useful to have a news source that you absolutely do not trust: there’s nothing better to hone your critical faculties. It is most dangerous to trust any media source because it dulls sensibility to stuff and nonsense. At least when you expect limited reliability you are aware of alternative perspectives and the possibility that you are hearing lies, filtered truths and biases.

One of the benefits of old fashioned newspapers, even those with notable biases, is that serendipity always played a role when reading them. Now, with the best of intentions, we get more of the news we explicitly want. When we visit pages, we tend to get recommendations for more of the same (the Landing is ‘guilty’ of this too – we offer recommended content that may be similar whenever you view a page). This is great if you are a learner investigating a topic, not so great if you are hoping to get a well-rounded view of the world. I’m pleased that some people are taking heed of these problems and, rather than reinforcing filter bubbles, they are deliberately bursting them. The Random App (Apple only, sadly) is a good example of a concerted approach to this, mixing random stuff with things that we explicitly express an interest in. We need more of this. It is possible to restore a bit of sane diversity manually: for instance, I get a lot of my news via Pulse, which I have configured with well over 100 feeds, some of which are chosen because they match my interests and leanings, but a lot of which are chosen precisely because they don’t. Crowds are brilliant to learn from if and only if they are sufficiently diverse. 

 

Address of the bookmark: http://www.journalism.org/2014/10/21/political-polarization-media-habits/

Here’s Why Public Wifi is a Public Health Hazard

A nice clear and very graphic explanation of why wifi, especially public wifi, is a very dangerous thing to use. And no, it has nothing whatsoever to do with radiation – if that worries you, and it absolutely shouldn’t, you should be a lot more worried about your TV or radio and positively scared stiff by cellphones, heat lamps and electric stoves. Or light, for that matter. Dangerous stuff, light. 

But, back to the article, most of the more frightening issues it illustrates can be dealt with using a good VPN, use of secure sites (like this one) and very careful attention to what you are clicking and what you are sharing. Others, especially those involving man-in-the-middle attacks and password cracking, can be much trickier to deal with. 

If you are worried by this, and you absolutely should be if any of your devices uses wifi, including your home system, then there are numerous articles that will reassure you that you have some basic safeguards in place, such as: 

  • http://www.forbes.com/sites/amadoudiallo/2014/03/04/hackers-love-public-wi-fi-but-you-can-make-it-safe/ (good basic advice, but does not address some of the issues raised here)
  • http://www.gizmag.com/how-to-stay-secure-on-public-wireless-hotspots/28694/ (a little more complex but a little better informed and offering a little more protection)
  • http://www.watchguard.com/infocenter/editorial/27061.asp (for the geeks or those with a serious interest – a more detailed pair of articles on how wifi evil twins work and what can be done to avoid them, as well as other risks)

If you’ve not thought much about such things, now is a good time.

Address of the bookmark: https://medium.com/matter/heres-why-public-wifi-is-a-public-health-hazard-dd5b8dcb55e6

x-literacies

There is an ever-growing assortment of x-literacies. Here are just a few that have entered the realms of academic discourse:

  • Computer literacy
  • Internet literacy
  • Digital literacy
  • Information literacy
  • Network literacy
  • Technology literacy
  • Critical literacy
  • Health literacy
  • Ecological literacy
  • Systems literacy
  • Statistical literacy
  • New literacies
  • Multimedia literacy
  • Media literacy
  • Visual literacy
  • Music literacy
  • Spatial literacy
  • Physical literacy
  • Legal literacy
  • Scientific literacy
  • Transliteracy
  • Multiliteracy
  • Metamedia literacy

This list is a small subset of x-literacies: if there is some generic thing that people do that demands a set of skills, there is probably a literacy that someone has invented to match.  I’ll be arguing in this post that the majority of these x-literacies miss the point, because they focus on tools and technologies more than the reasons and contexts for using them. 

The confusion starts with the name. ‘Literacy’, literally, means the ability to read and write, so most other literacies are not. We might just as meaningfully talk about ‘multinumeracy’ or ‘digital numeracy’ as ‘multiliteracy’ or ‘digital literacy’ and, for some (e.g. ‘statistical literacy’), ‘numeracy’ would actually make far more sense. But that’s fine – words shift in meaning all the time and leave their origins behind. It is not too hard to see how the term might evolve, without bending the meaning too much, to relate to the ability to use not just text but any kind of symbol system. That sometimes makes sense – visual, media or musical literacy, for example, might benefit from this extension of meaning. But most of the literacies I list above have at best only a partial relationship to symbol systems. I think what really appeals to their inventors is that describing a set of skills as ‘x-literacy’ makes ‘x’ seem more important than just a set of skills. They bask in the reflected glory of reading and writing, which actually are awfully important. 

I’m OK with a bit of bigging up, though. The trouble is that prefixing ‘literacy’ with something else infects how we see the thing. It has certainly led to many silly educational initiatives with poorly defined goals and badly considered outcomes. This is because, all too often, it draws attention far too much to the technology and skills, and far too far away from its application in a specific culture. This context-sensitive application (as I shall argue below) is actually what makes it ‘literacy’, as opposed to ‘skill’, and is in fact what makes literacy important.

So this is my rough-draft attempt to unravel the confusion so that at least I can understand it – it’s a bit of sense-making for me. Perhaps you will find it useful too. Some of this is not far off the underpinnings of the multiliteracy camp (albeit with notably different conclusions) and one of my main conclusions will be very similar to what many others have concluded too: that literacy spans many skills, tools and modalities, and is highly contextualized to a given culture at a given time. 

Culture and technology

When they pass a certain level of size and complexity, societies need more than language, ritual, stories, structures and laws passed by word of mouth (mostly things that demand physical co-presence) in order to function. They need tools to manage the complexity, to distribute cognition, replicate patterns, preserve structures, build new ones, pass ideas around, and to bind a dispersed society together. Since the invention of printing, most of the tools that play this role have been based on the technologies of text, which makes reading and writing fundamental to participation in a modern society and its numerous cultures and subcultures.

To be literate has, till recently, simply meant that you can do text. There may also be some suggestion of the ability to use text that relate to abilities to decipher, analyze, synthesize and appreciate: these are at least the product of literacy if not a part of it, and they are among the main reasons we need literacy. But the central point here is that people who are literate, in the traditional sense, are simply able to operate the technology of writing, whether as consumers, producers or both. Why this is ‘literacy’ rather than simply a skillset like any other, is that text manipulation is a prerequisite for people to participate in their culture. It lets them draw on accumulated knowledge, add to it, and be able to operate the social and organizational machinery. At its most basic, this is a pragmatic need: from filling in forms and writing letters to reading signs, labels on food, news, books, contracts and so on. Beyond that, it is also a means to disseminate ideas, challenges, and creative thought in a society. It is futhermore a fundamental technology for learning, arguably second only to language itself in importance. More than that, it is a technology to think with and extend our thinking far beyond what we could manage without such assistance. It lets us offload and enhance our cognition. This remains true, despite multiple other media vying for our attention, most of which incorporate text as well as other forms. I could not do what I am doing right now without text because it is scaffolding and extending the ideas I started with. Other media and modalities can in some contexts achieve this end too and, for some purposes, might even do it better. But only text does it so sweepingly across multiple cultures, and nothing but text has such power and efficiency. In all but the most limited of cultures, text performs culture, and text makes culture: not all of it, by any means, but enough to matter more than most other learned technology skills.

Other ways to perform culture

There have for countless millenia been many other media and tools for cultural transmission and coordination, including many from way before the invention of writing. Paintings, drawings, sculpture, dance, music, rituals, maps, architecture, furniture, transport systems, sport, games, roads, numbers, icons, clothing, design, money, jewellery, weapons, decoration, litany, laws, myths, drama, boats, screwdrivers, door-knobs and many many more technologies, serve (often amongst their other functions) as repositories of cognition, belief, structure and process. They are not just the signs of a culture: they play an active role in its embodiment and enactment. But text, maybe hand in hand with number, holds a special place because of its immense flexibility and ubiquitous application. Someone else can make roads or paintings or door-knobs and everyone else can benefit without needing such skills – this is one of the great benefits of distributed labour. But almost everyone needs skill in text, or at least needs to be close to someone with it. It is far from the only fruit but everyone needs it, just to participate in the cultures of a society.

Cultures and technologies

There are many senses in which we might consider technology and culture to be virtually synonymous. Both are, as Ursula Franklin puts it, ‘the way things are done around here’. Both concern process, structure and purpose. However, I think that there are many significant things about cultures  – attitudes, frames of mind, beliefs, ways of seeing, values, ideologies, for instance – that may be nurtured or enacted by technology, but that are quite distinct from it. Such things are not technological inventions – they are the consequence, precursors and shapers of inventions. Cultures may, however, be ostensively defined by technologies even if they are not functionally identical with them. Archeologists, sociologists and historians do it all the time. Things like language, clothing, architecture, tools, laws and so on are typically used to distinguish one culture from another.

One of the notable things about technologies is that they tend to evolve towards both increasing complexity and increasing specialization. This is a simple dynamic of the adjacent possible. The more we add, the more we are able to add, the more combinations and the more new possibilities that were unavailable to us before reveal themselves, so the more we diversify, subdivide, concatenate and invent. Thus it goes on ad infinitum (or at least ad singularum). Technologies tend to continuously change and evolve, in the absence of unusual forces or events that stop them. Of course, there are countless ways that technologies, notably in the form of religions, can slow this down or reverse it, as well as catastrophes that may be extrinsic or that may result from a particularly poor choice of technologies (over-cultivation of the land, development of oil-dependency, nuclear power, etc). There are also many technologies that play a stabilizing rather than a disruptive role (education systems, for example). Overall, however, viewed globally, in large cultures, the rate of technological change increases, with ever more rapid lifecycles and lifespans.  This means that skills in using technologies are increasingly deictic and increasingly short-lived or, if they survive, increasingly marginalized. In other words, they relate specifically to contexts outside of which they have different or no meaning, and those contexts keep changing thanks to the ever-expanding adjacent possible. Skills and techniques become redundant as contexts change and cultures evolve. That’s a slight over-simplification, but the broad pattern is relentless.

Towards a broader definition of ‘literacy’

Literal literacy is the ability to use a particular technology (text) to give us the ability to learn from, interact with and add to our various different cultures. The label implies more than just reading and writing: to be literate implies that, as a consequence of reading and writing, stuff has been and will be read – not just reading primers, but books, news, reports and other cultural artefacts. In the recent past, text was about the most significant way (after talking and showing) that cultural knowledge was disseminated. In recent decades, there have been plentiful other channels, including movies, radio, TV, websites, multimedia and so on. It was only natural that people would see the significance of this and begin to talk about different kinds of literacy, because these media were playing a very similar cultural role to reading and writing. The trouble is that, in doing so, the focus shifted from the cultural role to the technology itself. At its most absurd, it resulted in terms like ‘computer literacy’ that led to initiatives that were largely focused on building technical skills messily divorced from the cultures they were supporting and of little or no relevance to being an active  member of such a culture.

So here’s a tentative (re)definition of ‘literacy’ that restores the focus: literacy is the prerequisite set of technological skills needed for participation in a culture.  And, of course, we are all members of many cultures. There are other things that matter in a culture apart from technological skills, such as (for example) a playful spirit, honesty, caring for others, good judgement, curiosity, ethical sensibility, as well as an ability to interpret, synthesize, classify, analyze, remix, create and seek within the cultural context. These are probably more important foundations of most cultures than the tools and techniques used to enact them. But, though traits like these can certainly be nurtured, inculcated, encouraged, shown, practiced, learned and improved, they are not literacies. These are the values and valued traits in a culture, not the skills needed to be a part of it, though there is an intimate iterative relationship between the two. In passing, I think it is those traits and others like them that education is really aimed at developing: the rest, the literacy part, is transient and supportive. We don’t have values and propensities in order to achieve literacy. We learn most of them at least partly through the use of literacies, and literacies are there to support them and let them flourish, to provide mechanisms through which they can be exercised.

My suggestion is that, rather than defining a literacy in terms of its technologies, we should define it in terms of the particular culture it supports. If a culture exists, then there is a literacy for it, which is comprised of a set of skills needed to participate in that culture. There is literacy for being a Canadian, but there is equally literacy for being part of the learning technologies community (and for each of its many subcultures), being a researcher, a molecular scientist, a member of a family or of a local chess club. There is literacy for every culture we belong to. Some technological skillsets cross multiple cultures, and some are basic to them. The first of these is nearly always language. Most cultures, no matter how trivial and constrained, have their own vocabularies and acceptable/expected forms of language but, apart from cases where languages are actually a culturally distinguishing factor (e.g. many nations or tribes) they tend to inherit most of the language they use from a super-culture they are a part of. Reading and writing are equally obvious examples of skills that cross multiple cultures, as are numeracy skills. This is why they matter so much – they are foundational. Beyond that, different technologies and consequent skills may matter as much or more in different cultures. In a religious culture these might include the rules, rituals, principles, mythologies and artefacts that define the religion. In a city culture they could include knowledge of bylaws, transit systems, road layouts, map-reading, zones, and norms. In an academic culture it might relate to (for instance) methodologies, corpora, accepted tenets, writing conventions, dress standards, pedagogies, as well as the particular tools and methods relating to the subject matter. In combination, these skills are what makes someone in a given culture literate in that culture.

For instance

Is there such a thing as computer literacy? I’d say hardly at all. In fact, it makes little sense at all to think in those terms. It’s a bit like claiming there is pen literacy, table literacy or wall literacy.  But there might be computing literacy, inasmuch as there may be a culture of computing. In fact, once upon a time, when dinosaurs roamed the earth and people who used computers had to program them themselves, it might have been a pretty important culture that any people who wished to use computers for any purpose at all would need to at least dip their toes in and, most likely, become a part of. That culture is still very much there but it is not a prerequisite of owning a computer that one needs to be a part of it any more – computing culture is now the preserve of a relatively tiny band of geeks who are dwarfed in number by those that simply use computers. The average North American home has dozens of computers, but few of their users need to or want to be part of a computing culture. They just want to operate their TVs, drive their cars, use their phones, take photos, browse the Web, play the keyboard, etc. This is as it should be. Those in a computing culture are undoubtedly still an important tiny band who do important things that affect the rest of the world a lot, but they are just another twig at the end of a branch of the cultural tree, not the large stem that they once were. Within what is left of that computing culture there are a lot of overlapping computing sub-cultures: engineers, bricoleurs, hardware freaks, software specialists, interaction designers, server managers, programmers, object-oriented programmers, PHP enthusiasts, iOS/Mac users, Android/Windows users, big-endians, little-endians. Each sub-culture has its own literacy, its own language, its own technologies on which it is founded, as well as many shared commonalities and cross-cutting concerns. 

Is there such a thing as ‘digital literacy’? Hardly. There is no significant distinctive thing that is digital culture, so there is no such thing as digital literacy. Again, like computing culture, once upon a time, there probably was such a thing and it might have mattered. I recall a point near the start of the 1990s, as we started to build web servers, connect Gopher servers, use email and participate in Usenet Newsgroups, at which it really did seem that we were participating in a new culture, with its own evolving values, its own technologies, its own methods, rules, and ethics. This has almost entirely evaporated now. That culture has in part been absorbed and diffused, in part branched into subcultures. Being ‘digital’ is no longer a way of defining a culture that we are a part of, no longer a way of being. Unless you are one of the very few that has not in the last decade or so bought a telephone, a TV, a washing machine, a stove, or one of countless other digital devices, you are ‘digital’. And, if there were such a thing as a digital culture, you would almost certainly be a part of the digital culture if you are reading this. This is too tenuous a thing – it has nothing to bind it apart from the use of digital devices that are almost entirely ubiquitous, at least in first world cultures, and that are too diverse to bind a culture together. There are, as a result, insufficient shared values to make it meaningful any more. It is, however, still possible to be anti-digital. Some digital luddites (I mean this non-perjoratively to refer to anyone who deliberately eschews digital technologies) do very much have cultures and probably have their own literacies. And there might well be literacies that relate to specific digital technologies and subsets of them. Twitter has a culture, for instance, that implies rules, norms, behaviours, language and methods that anyone participating should probably know. The same may be (and at some point certainly was) true of Facebook, but I think that is less obvious now.

Network culture is probably still a thing, but it is already fading in much the same way that digital culture has already faded, with ubiquity, diversity and specialization each taking bites out of it. We have seen network culture norms develop and spread. New vocabularies have been developed with subtle nuances (LOL, ROFL, LMFAO) that often branch into meanings that may only be deciphered by a few sub-cultures but that may subsequently spread into other cultures (TIL, RT, TLDR, LPT).   We have had to learn new skills, figuring out how to negotiate privacy, filter bubbles, trolls, griefing, effective tagging, filtering, sorting, unfriending and friending, and much much more, in order to participate in a social network culture, one that is (for now) still a bit distinct from other cultures. But that culture has already diversified, spread, diffused, and it is getting more diffuse every day. As it becomes larger and more diverse it ceases to be a relevant means of identifying people, and it ceases to be something we can identify with.

Much of the reason for network culture’s retreat is technological. It was enabled by an assembly of technologies and spawned new ones (norms, conventions, languages, etc) but, as they evolve, other technologies will render it irrelevant. Technologies often help to establish cultures and may even form their foundation but, as they and the cultures co-develop, the technologies that helped build those cultures stop being definitional of them. Partly this results from diffusion, as ways of thinking creep back into the broader super-culture and as more and more diverse cultures spread into it. Partly it is because new technologies take their place and diversify into niches. Partly it is because, rather than us learning to use technologies, they learn to use us. This sounds creepier than it really is: what I mean is that individual inventors see the adjacent possibles and grab them, so technologies change and, in many cases, become embedded, replacing our manual roles in them with pre-orchestrated equivalents. Take, for example, a trivial thing like emoticons, images built from arbitrary text characters, that take some of the role of phatic communication in text communication – like this :-). Emoticons are increasingly being replaced by standardized emojis, like this Smile. Bizarrely, there are now social networks based on emoji that use no text at all. I am intrigued by the kind of culture that this will entail or support but the significant point here is that what we used to have to orchestrate ourselves is now orchestrated in the machine. Consequently, the context changes, problems are solved, and new problems emerge, often as a direct result of the solution. Like, how on earth do you communicated effectively with nothing but emojis Undecided?

Where do we go from here? 

Rather than constantly sub-divide literacies into ever more absurdly-named niches named for the tools to which they relate, or attempt to find bridging competences or values that underly them and call those multiliteracies (or whatever), I propose that we should think of a literacy as being a highly situated set of skills that enable us to play a role as an operator in any given social machine, as creators and/or consumers of a culture – any culture and every culture.  The specificity we choose should be determined by the culture that interests us, not by any predetermined formula. Each subculture has its own language, tools, methods, and signs, and each comes with a set of shared (often contested) attitudes, beliefs, values and passions, that both drive and are driven by the technologies they use.  As a result, each has its own history, that branches from the histories of other subcultures, helping to make it more distinct. This chain of path dependencies helps to reinforce a culture and emphasize its differences. It can also lead to its demise.

In most if not all cases, literacy is an assembly of skills and techniques, not a single skill. ‘Literacy’ is thus simply a label for the essential skills and techniques needed to actively participate in a given culture. Such a culture may be big or small. It may span millenia or centuries but it may span only decades, years or (maybe) months or even weeks or days. It may span continents or exist only in a single room. I have, for example, been involved with courses, workshops and conferences that have evolved their own fleeting cultures, or at least something prototypical of one. In my former job I shared an office with a set of colleagues that developed a slightly different culture from that of the office next door. Of course, the vast majority of our culture was shared because we performed similar roles in the same department in the same organization, the same country, the same field, the same language, the same ethos. But there were differences that might, in some contexts and for some purposes, be important. For most contexts, they were probably not.

Researching literacies 

Assuming that we know what culture we are looking at, identifying literacy in any given culture is simply (well…simply-ish) a question of looking at the technologies that are used in that culture.  While technology use is far from a complete definition of a culture, what makes it distinct from another may be described in terms of its technologies, including its rules, tools, methods, language, techniques, practices, standards and structures. This seems a straightforward way of thinking about it, if seemingly a bit circular. We identify cultures by their technology uses, and define literacy by technology use in a culture. I don’t think this apparent circularity is a major issue, however, as this is an iterative process of discovery: we may start with coarse differentiators that distinguish one culture from another but, as we examine them more closely, will almost certainly find others, or find further differentiators that indicate subcultures. A range of methods and methodologies may be used here, from grounded theory to ethnography, from discourse analysis to Delphi methods, simple observation, questionnaires, interviews, focus groups, and so on. If we want to know about literacy in a culture, we have to discover what technologies are foundational in that culture.

Most of the cultures we belong to are subcultures of some other or others, while others straddle borders between different and otherwise potentially unrelated cultures.  Some skills that partially constitute a given literacy will cross many other cultural boundaries. Almost all will involve language, most will involve reading and writing, many will involve number, lots will involve visual expression, quite a few will involve more or less specific skills using machines (particularly software running on computers, some of which may be common). The ability to create will usually trump the ability to consume although, in some cultures, prosumption may be a defining or overwhelmingly common characteristic (those that emerge in social networks, for instance).

This all implies that a first concern when researching literacy for a given culture, is to identify that culture in the first place, and decide why it is of interest. While this may in some cases be obvious, there may often be subcultures and cross-cultural concerns that could make it more complex to define. One way to help separate out different cultures is to look at the skills, terminology, technologies, implicit and explicit rules, norms, and patterns of technology use in the subset of people that we are looking at. If there are patterns of differences, then there is a good chance that we have identified a cultural divide of some kind. A little more easily, we can also look both at why people are excluded from a culture, and seek to discover the things people need to learn to become a part of it – to look at the things that distinguish an outsider from an insider and how people transition from one to the other.

For example, the literacy for the culture of a country is almost entirely defined by invention. Countries are technologies, first and foremost. They have legislated (if often disputed) borders and boundaries, laws, norms, language, ways of doing things, patterns, establishments, and institutions that are almost entirely enshrined in technology. It is dead easy to spot this particular culture and mostly simple enough to figure out who is not in it and, normally, what they need to do to become a part of it. To be literate in the context of a country is to have the tools to be able to know and to actively interact with the technologies that define it. To give a simple example, although it is quite possible to be Canadian with only a limited grasp of English and/or French, part of what it means to be literate in Canadian culture is to speak one or (ideally) both languages. Other languages are a bonus, but those two are foundational. It is also possible to see similar patterns in religious cultures, academic cultures, sports cultures, sailing cultures and so on. We can see it in subcultures – for example, goths and hipsters are easily identified by a set of technologies that they use and create, because many of them are visible and definitional.  It gets trickier once we try to find subcultures of such easily identified sets but, on the whole, different technologies mark different cultures.

What makes all this technical detail worth knowing is not that different sets of people use different tools but that there are consequences of doing so. Technologies have a deep impact on attitudes, values, beliefs and relationships between people. In turn these values and beliefs equally impact the technologies that are used, developed, and valued. This is what matters and this is what is worth investigating. This is the kind of knowledge that is needed in order to effect change, whether to improve literacy within a culture or to change the culture itself. For example, imagine a university that runs on highly prescriptive processes and a reward structure based on awards for performance. You may not have to look far to find an example. Such a university might be dysfunctional on many counts, either because of lack of literacy in the technologies or because the technologies themselves are poorly considered (or both). One way to improve this would be to ensure that all its members are able to operate the processes and gain awards. This would be to improve literacy within the culture and would, consequently, reinforce it and sustain it. This might be very bad news if the surrounding context changes, making it significantly harder to adapt and change to new demands, but it would be an improvement by some measures. Another, not necessarily conflicting, approach would be to change or eliminate some of the processes, and get rid of or change the nature of rewards for performance: to modify the machinery that drives the culture. This would change the culture and thus change the literacy needed to operate within it. It might do unexpected things, especially as the existing attitudes and values may be at odds with the new culture: people within it would be literate in things that are not relevant or useful any more, while not having literacy needed to operate the new tools and structures. Much existing work surrounding x-literacies fails to clearly make this crucial distinction. By focusing largely on the technological requirements and ignoring the culture, we may reinforce things that are useless, redundant or possibly harmful. For instance, multimedia literacy might be great, sure. But for what and for whom? And in what forms? Different skillsets are needed in different contexts, and will have different value in different cultures.

To conclude

I have proposed that we should define literacy as the skills needed to operate the technologies that underpin a particular culture. While some of those skills are common to many cultures, the precise set and the form they take is likely different in almost every culture, and cultures evolve all the time so no literacy is forever. I think this is a potentially useful perspective.

We cannot sensibly define a set of skills or propensities without reference to the culture that they support, and we should expect differences in literacies both between different cultures and across time and space in any given culture. We can ask meaningful questions about literacy in a culture of (say) people who use Twitter for learning and research as opposed to those needed by people that only use Twitter to stay in touch with one another.  We can look at different literacies for people who are Canadian, people who are in schools, people of a particular religion, people who like a particular sport, people who research learning technologies, people in a particular office, people who live in Edmonton, not to mention their intersections and their subsets. By looking at literacy as simply a set of skills needed for a given culture we can gain large insights into the nature of that culture and its values. As a result, we can start to think more carefully about which skills are important, whether we want to simply support the acquisition of those skills, or whether we want to transform the culture itself.

This is just my little bit of sense making. I have very probably trodden territory that is very familiar to a lot of people who research such things with more rigour, and I doubt very much that any of it is at all original. But I have been bothered by this issue for a while and it now seems a little clearer to me what I think about this. I hope it has encouraged you to think about what you think too. Feel free to share your thoughts in the comment box!

Dining with an overweight person makes you eat more

It looks like one mechanism for the already observed spread of obesity through social networks may be extremely simple: people tend to eat more when dining with people who are fatter. Thanks to an ingeniously simple experimental design, this paper shows that it’s not due to any difference in the fatter people’s behaviour. It’s solely due to their size. Interesting.

The study deliberately used eating companions for the study, making this a clear network effect in which people are influenced by those with whom they share a reciprocal connection. I’d be intrigued to discover whether it would make any difference if the fatter people (wearing body prostheses) were simply strangers sitting in the same restaurant, not eating together. I’d hypothesise that the effect would still show up, probably more weakly, but that it might be proportional to the number of people who appeared to be obese. In fact, I am guessing it would probably be more complex than that: for instance, that we might be more influenced by those that we thought were more like us or that we took more of a shine to. If so, this would be more of a set than a network effect. It would be not unlike flocking behaviour in birds: until quite recently it was thought that birds flocked due to a simple network effect that spread from neighbour to neighbour but, as it turns out, they are simply counting the birds nearby that are behaving in a particular way, and going with the majority. Memes may work the same way.

This is about as far from intentional communication as it can get – it’s not even a behaviour that is being copied here but some imagined and possibly inaccurate belief about someone’s past behaviour – and yet the effects may be quite profound and, spread through a society, might have massive large scale effects that spread over into many different aspects of many people’s lives, affecting everything from population health to the economy. It’s one of the reasons that schools and universities are a good idea, quite apart from, and independently of, any intentional teaching that might or might not be having an effect. When you see people around you behaving in a particular way, you are more likely to behave similarly. If it seems normal to be actively learning, there’s a much greater chance that you will do so too. Behaviours (even imagined ones) are highly infectious.

Address of the bookmark: http://blogs.discovermagazine.com/seriouslyscience/2014/09/22/dining-overweight-person-makes-others-eat/

StudentLife: Assessing Mental Health, Academic Performance and Behavioral Trends of College Students using Smartphones

A totally fascinating study of students conducted using a massive amount of automatically collected data from smartphones along with other data collected from other systems and via surveys to come up with a large set of correlations relating to everything from mood to GPA. This would win a top paper award in any conference I can think of.

Too much to summarize here, and many more questions emerging from it than it answers, but this should keep a load of researchers busy for years to come. I’m certainly going to be picking this over carefully now that I’ve read it through once. I highly recommend that anyone involved in education (staff or students) should read this! But it should be read with great care and with all critical faculties on full alert. This was a very specific group of students in a very specific context and it would be highly dangerous and irresponsible to extrapolate any generalizations at all from any of this, though I bet some people will. There are lots of things that warrant further investigation – active students were happier and did better but lack of activity, especially at night, seems correlated with higher GPAs, for example, and there are some big fuzzy areas in the sampling that involved a lot of interpretation that was unlikely to be particularly accurate much of the time. The finding that I find particularly appealing is the discovery that classroom attendance had no correlation with academic performance at all: I almost laughed out loud at this one. As always, however it’s not what but how that matters. This suggests to me that someone really needs to work on their classroom activities rather than that classroom teaching does no good, and I would really like to know a lot more about the students who skipped classes before even drawing conclusions from this small dataset let alone more broadly. The other big issues here surround the need for careful interpretation and more qualitative data to explore causes: all this shows are correlations, some of which seem to imply obvious things (e.g. students that study rather than party tend to get better grades but they tend to be lonelier) but many of which are more complex and should be considered in context and at a whole systems level.

The anonymized dataset is available for downloading.

Address of the bookmark: http://studentlife.cs.dartmouth.edu/studentlife.pdf

Professor forces students to buy his own $200 textbook

This article is actually purportedly about the very unsurprising discovery that students who can’t afford textbooks are downloading them illegally, even for ethics classes. Shocking! Not. However, the thing that really shocks me about this article is the example given of the professor demanding that his students purchase his own $200 etextbook. Piracy seems a pretty minor crime compared with this apparently outrageous, blatant, extortionate abuse of power. 

 

Address of the bookmark: http://www.washingtonpost.com/blogs/answer-sheet/wp/2014/09/17/more-students-are-illegally-downloading-college-textbooks-for-free/

The Serious Limitation of Rote Memorisation You Probably Don't Know About (And It's Undermining Learning)

Report on an interesting study showing how rote learning of some things results in increasingly creative interpretations of what we have tried to learn, which means it actually gets in the way of remembering, even though more details are recalled. The researchers note that this is not an issue with simple memorization of numbers, words, etc, but it can be an issue where more complex and relational things need to be recalled – the report mentions understanding the solar system as an example and the researchers used recollection of things in pictures for their study for their testing. In such cases, repetition means more things are remembered, but more things are remembered wrong. I’m wondering whether this affects different kinds of rote memorization, such as the muscle memory used when playing a musical instrument, or learning lines in a song or a play. I’m guessing these are more akin to simple recollections of words because they are a linear sequence, whereas the ways we perceive pictures rely on us choosing where to focus. 

Address of the bookmark: http://www.opencolleges.edu.au/informed/news/limitation-of-rote-learning/

Teaching Crowds: Learning and Social Media

The free PDF preview of the new book by me and Terry Anderson is now available from the AU Press website. It is a complete and unabridged version of the paper book. It’s excellent value!

The book is about both how to teach crowds and how crowds can teach us, particularly at a distance and especially with the aid of social software.

For the sake of your health we do not recommend trying to read the whole thing in PDF format unless you have a very big and high resolution tablet or e-reader, or are unusually comfortable reading from a computer screen, but the PDF file is not a bad way to get a flavour of the thing, skip-read it, and/or to find or copy passages within it. You can also download individual chapters and sections if you wish. 

The paper and epub versions should be available for sale at the end of September, 2014, at a very reasonable price. 

Address of the bookmark: http://www.aupress.ca/index.php/books/120235