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Is Thinking Digitally a New Habit of Mind or Simply Old Habits in a New Context?

06 Dec

Thinking Digitally Logo

What makes for good thinking? It is commonly assumed that it is our intelligence or abilities that have the greatest effect on our thinking. Ron Ritchhart (2002), however, makes the case that it is our dispositions, our acquired patterns of behaviour which activate and direct our abilities . More than our abilities themselves, our dispositions afford our capacity for greatness. These dispositions are shaped and formed by our interactions with others, by our culture, society and history (Ritchhart & Perkins, 1997). Dispositions, or habits of mind (Dewey, 2007) are pivotal because they determine when we choose to think, the importance we place on it, and how deeply we question the assumptions and narratives (Bruner, 1991) upon which thought is based, allowing new narratives to emerge.

For example, the habit of mind persisting suggests a disposition towards keeping at it: trying new ways to approach a problem, not being daunted by failure, worrying away at something until you succeed. This disposition applies in many different contexts, including digital spheres, such as computer programming. It is clearly a disposition which affords success. You cannot succeed if you give up too easily!

homLikewise the capacity for finding humour affords success in many different contexts. Costa & Kallick (2008) have identified sixteen such habits of successful thinkers. These habits do not describe the knowledge or skills necessary for success, but the dispositions which enable successful thought and action in the world.

In this article I will be arguing that Thinking Digitally is just such a disposition; a habit of mind which predisposes those who demonstrate it towards success in the same way that persistence or finding humour does. It is a disposition towards using digital tools to aid thought and action in the world; towards deploying algorithmic thinking as a way of generating explanations of reality, and using computational thinking as an approach to problem solving. These ideas will be unpacked below, but it is important to note that they share a concern with the disposition towards using digital devices to create, solve problems and understand the world we live in. I have chosen to use the term Thinking Digitally rather than computational thinking, which is the more commonly used term, because I believe that it describes a wider range of uses of digital devices, beyond how we organise tasks that are going to be automated by machines, mathematical modelling, the use of simulations, and simulators, or calculators and computers to include the ways in which we access and evaluate information, and how we author digital texts and communicate our understandings in the current era.

I will argue that Thinking Digitally is a logically separate habit or disposition rather than the application of any combination of the other sixteen habits in a new context, the digital world. Marc Prensky (2001b) has advanced the idea that people born after a certain date, whom he has dubbed digital natives, carry a natural disposition towards digital technologies. He argues that people born before the advent of the digital era are digital immigrants; that digital technologies are somehow foreign to them, and that while digital natives are able to use digital devices effortlessly, for immigrants there is no such natural facility. In other words digital dispositions are based on age. While this idea has gained widespread traction because it seems to explain why some people seem to take to digital technologies like a duck to water, and others struggle with it, or avoid it entirely, it is a notion that has been roundly critiqued, as we shall see below. I shall argue for the notion of a set of digital dispositions, based on certain characteristics or habits of mind rather than on age, carries weight.

In recent years, within the Computer Science community, teachers have begun to argue that Computational Thinking, often called Algorithmic Thinking should be integrated into the curriculum, not just as a separate discipline, but as a foundational subject. I will argue that Computational Thinking and Algorithmic Thinking forms a new mode of thought, different from the paradigmatic or narrative modes of thought, and that the predisposition towards using this mode of thought forms the basis for arguing in favour of a separate habit of mind. I will argue that a disposition towards using computational and algorithmic thought, and allied to this using digital media to access and legitimate knowledge, forms part of an evolving revolution in thought, which is transforming the world, and towards which some people appear to be more disposed, and others less disposed. Acquiring the habit of digital thinking clearly advantages some, and leaves others floundering in an increasingly digital world.

If we look at recent ideas around epistemology, theories about learning and cognition, pedagogy and literacy, we can begin to discern polar opposites which, while they do not define neat categorizations of analogue and digital thought, do point to ways in which certain polarities are afforded by either analogue or digital modalities. We are living in an Information Age (Castells, 2011), in which the digital storage and processing of information in digital forms is increasingly central to our knowledge and economic survival, and this privileges certain ways of looking at and thinking about the world. Our ability to succeed in this altered landscape is largely dependent upon our dispositions and habits of mind, not just on our knowledge or skills. Some of these dispositions have already been described by Costa and Kallick, but some are unique to digital contexts, and revolve around how we think about our relationship with digital cognitive technologies.

Khaneman (2011) has argued that there are two types of thinking which operate. System I thought is fast, intuitive thinking in which we come to rapid assessments based on our accumulated habits of thought, and received judgements handed down to us. System II thought, on the other hand, is slow thinking in which we carefully reason through a position, considering the evidence and reaching a judgement based on a logical process. We need to rely on System I thought most of the time. We cannot tell life to wait while we carefully reason over a position. System II thought is, however, vital because if allows us to build better instincts, and base our intuitive responses on more solid ground. In other words, it frames our habits and dispositions. Successful critical thinking is based on building solid habits of mind on which we can depend when we don’t have the time to carefully consider our responses.

In much the same way, I want to make the case that the salient feature of our use of digital technologies lies not in the skills and abilities we bring to any given task, but in the dispositions and habits of mind that unlock what we are able to accomplish with technology. Behind digital literacy lies, in other words, a set of mental habits and dispositions which are what allow the power of the technology to be unleashed. My capacity to use a database is one thing, but it is my digital dispositions which determine when I choose to use a database, for what purposes, and to what effect. Their dispositions are what allow some people to use technology to unlock their creativity and solve problems rapidly and effectively, and what constrains others to use it merely for repetitive or largely meaningless tasks, or not to use it at all.

What are the dispositions and habits of mind of successful people when they are using digital devices and media? Do these dispositions form a logically discrete entity or are digital technologies simply a different context in which the habits and dispositions (Costa & Kallick, 2008) that apply to analogue thinking are applied?

In working through this argument I am going to make a number of moves which are intended to present the case that there are indeed a set of uniquely digital dispositions, and that it makes sense to speak about thinking digitally as an overarching approach that successful thinkers bring to their use of technology, which shapes and guides effective digital practice. Indeed I will argue that these digital dispositions may also be brought to analogue contexts. In other words, we human beings, in learning how to think effectively when using digital tools, may have acquired some dispositions which we can carry back into the real, analogue world.

Computational Thinking

computational-thinking-white-bg

The first move is to argue that one set of digital dispositions hinges around the thinking that we do when we interface with machines. A frequently used term is Computational Thinking (Wing, 2006), which is used to describe the “thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information processing agent” (Lee, 2016). It is essentially taken to mean, then, the thought processes of one who is using a machine to solve a problem, and it is normally constituted as being based on three cognitive pillars: abstraction, automation and analysis. When we use cognitive technologies to automate or perform tasks, we need to program the machine, we need to break the task down into sub-routines that can then be automated, and we need to think the task through, understanding it from the point of view of what it is that the machine can and can’t do. The illustration above (“Reading A Book or An Hour of Code?,” 2016) is typical of attempts to break down what constitutes computational thought.

Proponents of Computational Thinking in the curriculum argue that “algorithmic thinking” should form the fourth R of the curriculum: Reading, ‘Riting, ‘Rithmatic & ‘Rithm (Grover & Pea, 2013). The two terms appear to be used interchangeably. What then is Algorithmic Thinking?

Algorithmic Thinking vs Narrative & Paradigmatic Thought

paradigmatic narrative

Bruner (1991) sets out a dichotomy between two modalities of thought: the narrative and the paradigmatic. The paradigmatic mode, the scientific mode, seeks to logically categorize the world and test hypotheses of what is. The narrative mode, on the other hand, is concerned with the meaning that is ascribed to lived experience. When explaining the world, why an apple falls to the ground, for example, one could use paradigmatic thinking, appealing to a concept, the theory of gravity. But one could also use the narrative mode to explain why an apple falls to the ground: the apple falls because I knocked it with my elbow, and it rolled off the table and fell to the ground. There is nothing necessarily superior in either explanation. Both have explanatory power.

The advent of complex calculating machines, however, has furnished us with new ways to go about constructing an explanation of the world. Computer modelling offers ways of constructing a model of how tables, elbows and apples might behave under different sets of circumstances. Using a computer, and inputting slightly different sets of data and observing the outcomes can generate a more complete understanding of how apples roll and fall and allow us to make more accurate predictions. The sheer number of calculations necessary to sustain this mode of thought was largely impossible before the advent of computers, but it allows us to predict weather, and find distant planets.

paradigmatic narrative algorithmic

Those who have advanced the idea of an algorithmic mode of thought would be hard pressed as to where to place this in Bruner’s schema. Algorithmic thinking is not necessarily about categorizing the world, or logically predicting outcomes, nor is it about narrating an explanation, although it may involve both these things. It shares with paradigmatic thought a concern with establishing procedures, but shares with narrative thought a concern with sequencing. It should probably then been seen as a separate mode of thought. In the diagram on the right, I have represented this by placing it off to one side.

But, as we noted, there are considerable overlaps, so it would probably be better to represent this schema as a series of overlapping circles. This schema has the advantage of allowing for greater nuances. Bruner himself, for example shows how narrative thought lies behind much of scientific explanation.

paradigmatic narrative algorithmic 2

Behind the algorithmic mode of thought lies mathematical modelling of the world and the methodology of simulation. Mathematical modelling, enabled by the power of computers represents powerful new ways of acquiring knowledge of the world. Evolutionary Engineering, for example seeks to use comparisons between random designs to reach more efficient designs in the fewest number of steps. Rather than seek to design complex solutions from principle (paradigmatic view), by comparing one design to another, and selecting the better one, repeating this process, optimum designs can be achieved in relatively shorter periods of time.

Cognitive Offloading & Cognitive Technologies

Because we have such small working memories (Sweller, 1988) we constantly need to offload our cognition onto the environment. We use language and writing to achieve most of this, but we also use our fingers when counting, or devices such as calculators, calendars, books, and increasingly these days digital devices such as cell phones, computers or the Internet. Dror (2007) argues that digital tools have become so pervasive and integral to our thinking processes that they cease to be external aids and become internal components in our cognitive processes. Cognitive technologies, in other words, have become instrumental in shaping our cognitive processes. New forms of distributed cognition (Clark & Chalmers, 2010) have arisen, in which our thinking is distributed across machines and across other people (Dror & Harnad, 2008), radically altering our cognitive landscapes.

These new theories about cognition and knowledge, encompassed within what is known as the Second Cognitive Revolution in psychology (Miller, 2003) clearly represent radical new ways of looking at what it means to be human, and how we see the relationship between man and machine.

Computational Thinking & Digital Thinking

Jeanette Wing, who introduced the term Computational Thinking, described it as “a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use” (Wing, 2006). Nevertheless, and despite a growing receptivity to the idea that Computer Science should be considered a core subject in the curriculum (Grover & Pea, 2013), and despite the growing integration of ICTs in our lives, and educational system, Computational Thinking is still seen largely as part of the Computer Science curriculum rather than a mode, or disposition of thought which pervades all subject disciplines. Lee argues that there is a tendency to conflate Computational Thinking with the operational steps involved, with computer literacy or with information literacy (Lee, 2016). This misses the point that Computational Thinking is in essence the dispositions of thought that human beings use when they are using machines to automate thinking process, or doing cognitive offloading onto machines.

I think part of the difficulty lies in the use of the term computational. As Wing stresses, the aim of Computational Thinking is not to get human beings to think like computers, but to describe how human beings think when they are using machines to solve problems. The term computational is so firmly rooted in the mathematical and engineering sciences that it tends to preclude the use of computers for perhaps their most vital task, that of communicating and accessing knowledge. How knowledge is legitimated and disseminated lies at the centre of our cognitive identities, and the new digital technologies are in the process of transforming the rules of the game. I believe that it is more useful to speak of how human beings organise their thought processes around problem solving using machines as digital thinking rather than computational thinking. This semantic change allows us to conceptualise computers as communication as well as computational devices and to see the dispositions of thought as including both purposes.

Digital technologies have transformed our practices in any number of ways, but it is important to note that every shift in practice represents a mental shift as well. It changes how we approach problem solving in subtle but important ways.

Digital Thinking vs Analogue Thinking

The second move is to claim that human thought is undergoing something of a revolution, and that particular aspects of our cognition are being accentuated and transformed by the rapid advances in digital media and what this affords. These changes are sufficiently momentous, and the contours of such change sufficiently discernible that we can begin to talk about a difference between digital and analogue thinking. These differences are not absolute; we have not acquired new brains overnight, but they are polarities which are impacting on our cognitive lives. I believe that those aspects of our thought which are afforded by digital technologies have been growing in importance, in line with the development of the information economy and the new world order, which has altered our discursive landscape (Gee & Lankshear, 2006) and may well be altering our brains as well. Neuroplasticity ensures that changes in practice have an impact on our brains (Prensky, 2001b), and it must be assumed, our cognition also.

analogue v digital

That we are experiencing change is not in contention, but how to characterise that change is. There are perhaps two possible views on this. The first, what we might term the hard view, is that Digital Thinking represents a new mode of thought afforded by the new digital media. This modality of thought has significant points of difference to Analogue Thinking to warrant identifying a range of habits and dispositions of mind which signal successful practice. This view sees cognition as being revolutionised. Stevan Harnad (1991), for example, talks of the Fourth Cognitive Revolution, as described below, and this has obvious ramifications for our behaviour and habits. The soft view, on the other hand, sees cognition as being largely unaltered by digital media, but that new approaches and dispositions are needed for dealing with the differences inherent in using digital media. The illustration above attempts to characterise two polarities of analogue and digital thinking as cutting across the different modalities of thought we discussed previously (Paradigmatic, Narrative and Algorithmic thought).

I do not believe that we can assess either of these views, whether cognition itself is changing, or whether our habits of mind are changing does not essentially alter the schema which can be discerned emerging from the literature around digital literacies, cognitive psychology and computational thinking. In either event it makes sense to differentiate the contours of how we perceive the terrain as altered by the introduction of digital technologies.

In an always-on, always-connected world, as more and more devices become connected in the Internet of things, and as connectivity becomes more commonplace and more integral to our lives, many are asking questions about what this means for our cognitive development. Headlines scream that the Internet is making us dumb (Carr, 2011; Thompson, 2013) and neuroscientsists suggest that our brains are being re-wired (Siemens, 2014; Greenfield, 2014) for good or ill. Psychologists suggest that it is affecting our memories (Sparrow, Liu, & Wegner, 2011) or that it is affecting our social lives (Wooley, 2013). There is a sense in which we stand at a crossroads, uncertain of both the direction and meaning of the rapid changes which are shaping our society. Utopian dreams and dystopian fears permeate the debate around the extent to which technology is driving change. Advances in Artificial Intelligence raise the prospect that we will soon not be the only sentient beings on the planet, and usher in a Brave New World where the difference between Human and Machine may not be that clear cut.

I would argue that never before have we needed a roadmap for navigating the future as much as we do now. Moore’s Law (Gibbs, 2015) which states that the capacity for data storage will double every 18 months, while applying to data, is a metaphor for the rapidity of change, and expresses the sense in which the rate of change is exponential. I would argue that what is required is a new set of habits and dispositions, strategies for dealing with this change, and with the changes associated with the Internet revolution. Our old ways of thinking, the habits and dispositions of centuries may not be enough to guide us in the future.

The advent of the printing press saw the introduction of a medium of mass communication which has had far-reaching implications for our history, society, and thought. When books were only available to a select few, and knowledge dependent upon individual transmission, knowledge was hierarchical and legitimated by an appeal to authority alone. In the thirteenth century Peter Abelard initiated a revolution in knowledge (Campbell, 1991), an appeal to evidentiary support in challenge to authority, where even theology had to bow before reason, but it was only with the invention of the printing press, and the Industrial Revolution allowing for the mass production of books that knowledge could be distributed more widely, ushering in the ideological sea change represented by the Enlightenment. How knowledge is legitimated, disseminated and reproduced changes completely how individuals think, learn, create and solve problems.

I would argue that we are at a similar turning point represented by the new digital media. The ability to self-publish, afforded by the Internet, has changed how knowledge is disseminated, altering legitimation practices. Many academics publish material from their blogs, and the speed of publication ensures peer review, but not in the conventional sense. An example of the future is wikipedia, that repository of crowdsourced knowledge said to be as accurate as Encyclopedia Britannica. Stevan Harnad’s notion of academic “sky-writing” encapsulates the idea of the Internet affording the immediacy of oracy with the reflective power of literacy to bring about the Fourth Cognitive Revolution. Harnad’s (1991) schema is tabulated below.

First Cognitive Revolution Oracy Hundreds of thousands of years ago Communication immediate and interactive Growth of Wernicke’s area and Broca’s area in brain?
Second Cognitive Revolution Literacy Tens of thousands of years ago Allows for reflection between communications Growth of Exner’s area in brain?
Third Cognitive Revolution Printing Press c. 1450 AD Revolution of scale
Fourth Cognitive Revolution Internet c. 1990s AD Near synchronous communication: brings together immediacy and reflection Are our brains being rewired?

This periodisation carries with it a sense of cognitive affordance offered by the new digital media of near synchronous communication. Ideas can be disseminated rapidly, enabling quick responses and affording collaborative thinking, but with enough time for some reflection before responses are made. The last column, linked to possible neural developments is highly speculative, and Harnad himself makes only tentative suggestions in this regard, but feeds into a contemporary literature suggesting that the move from page to screen carries with it some neural rewiring.

News and opinions are shared rapidly across social media, replacing traditional news sources. In a world where breaking news is not mediated by the professional journalistic eye, but blogged, tweeted and facebooked by participants, we need to reassess how we access knowledge about the world. Content is similarly mediated by new mechanisms. In a world where opinions are discussed through the vehicle of the share, the like and the Internet meme, we need to see knowledge as a commodity that is rapidly traded across the globe in relatively unmediated ways.

I think we can begin to discern the basis for an argument that we are seeing a revolution in cognition, a shift away from analogue, towards digital modes of communication and cognition.

Digital media do not replace analogue channels. As a species we still rely on our senses. Nevertheless, digital media represented by Internet and other telecommunication technologies, represent new modes of communication which have far-reaching consequences for how we communicate, think, learn, create and solve problems.

How our thinking is mediated, and the types of cognitive offloading that are afforded by these technologies may be represented by the following chart which compares Digital and Analogue Contexts:

Thinking Digitally Analogue Thinking Discussion
Hyperspace The five senses Push technologies in particular afford the delivery of information from sources not limited to our biological five senses.

 

For example I learn what the weather is outside from my cell phone as opposed to looking out the window.

Fast paced Slow paced Acquiring data in an analogue world is slow and deliberate, gathering data in a digital world is almost immediate and less considered. Speed has advantages and disadvantages and calls for different approaches to evaluating data.

 

I can use a search engine to find out about something rather than going to a public library and finding a book on the subject.

Multi-channel (digital media streams) Single channel (biological senses) While data in the analogue world comes at us via the multiple channels of our senses, the digital world opens up even more channels, some of them referencing analogue channels, others entirely in cyberspace. This has advantages and disadvantages and calls for different approaches towards data collection.

As I type this, I am receiving data from my cell phone, emails and alerts are appearing in my inbox and I am able to use the Internet to search for information. This is on top of what I sense about the world around me through my biological senses, which tends towards a single channel (my senses).

Parallel Processing Serial Processing The speed at which different channels of communication can be accessed affords multi-tasking. Of course, given the severe limitations imposed on our working memory, we can never truly multi-task, we can certainly take on tasks simultaneously in the analogue world. However, the plethora of extra channels extends our ability to work on many levels at the same time.

I tend to take on more tasks in parallel while using digital media. Partly because it is more efficient to do so, but partly because my mind is parcelling out sub-tasks which will require time because they are asynchronous communications – for example posting a query for help in solving a problem on a forum. While I wait for a reply, I write an email and watch a Kitty video on YouTube.

Hypertextual Screen Reading Linear/narrative Page Reading Readings in hyperspace are hypertextual rather than linear or narrative. Hypertextual reading affords rapid synthesis and evaluation. Linear, narrative readings afford a closely argued train of thought.

Using a website I can rapidly skim for relevant information by following links and using the Find or search function. If I want to follow a train of thought I have to read sequentially.

Fast and Wide Thought Slow and Deep Thought Multi-tasking and hypertextual reading affords the rapid synthesis and evaluation of ideas, the identification of patterns and Fast Thought. Linear and narrative readings affords closely reasoned consideration of a train of thought.

Most decisions we make are the result of Fast Thought, but digital media afford this by making more information available and allowing us to find patterns more actively. Page reading, however, affords deep thought because I have to follow the sequence of words in the order they were written.

The Reader Creates The Text The Writer Creates The Text Hypertext is epistemologically predisposed towards a constructivist paradigm where the reader constructs their own meaning from the world around them. Texts are created by the reader, following links.

Text is predicated on an author communicating and transferring a message, and is epistemologically neutral. The text is created by the writer.

Constructivist Pedagogical Paradigm Instructivist Pedagogical Paradigm Theories about how we think and learn have changed considerably over the last hundred years or so, with a shift towards theories stressing how meaning is constructed rather than perceived.
Learning by participation Learning by acquisition Sfard (1998) has argued that there are two metaphors for learning and both are valid – learning by participation, and learning as acquisition.
Symbolic Manipulation Symbolic Creation Fast thought affords rapid symbol manipulation, while slow thought affords the creation of new symbols.

Digital media allow us to rapidly manipulate information in many forms, but page reading allows us to generate new concepts.

Computational (Digital)

(Algorithmic) Thinking

Narrative & Metaphoric Thinking Jerome Bruner has shown the importance of narrative in our cognition. If we think about an issue we tend to do so by relating it. We also think metaphorically, comparing things to something similar in our experience. Computational thinking is something different – it operates at the level of simulation and modelling.

Digital media allow us to create simulations by modelling a problem and playing it out rather than thinking through a solution by relating its contours. This produces unexpected and counterintuitive results.

This schema is presented as polarities of what must inevitably form a continuum. Nor do I believe that they form a rigid dichotomy. Far more accurate to say that there is a dialectical relationship between the two.

The Foundations Of Digital Thinking

This characterization of twin polarities, operating in a dialectical (dialogic) relationship rather than in opposition, allows us to argue that there are several elements in human thought which, if not new, are at least being emphasised and foregrounded by the growing centrality of computers and ICTs in our lives. If we accept that even more important than our abilities and capacities are our dispositions, our ingrained behaviours and responses to the problems and challenges we face, it becomes clear that how we react to this shift in technology from analogue to digital is crucial in what we can accomplish.

What elements then constitute the dispositions of successful users of computational and digital media? If we look at successful use of digital media I think we can start to identify a number of elements.

Embracing Change

We all know that some people seem to embrace change and use it to their advantage, while others appear phased by change and shy away from it, or appear less imaginative and productive in the ways in which they use it. This has been falsely framed as a generational divide (Prensky, 2001a); that those born after 1985 (digital natives) are somehow wired differently, and have a natural affinity with ICTs which older people (digital immigrants) lack. While our brains may well be wired differently, if I am following this debate correctly, neural plasticity implies that all users of new technologies, regardless of age, will experience changes. There is a great deal of research indicating that this notion of a differently wired, differently thinking generation is a myth (Kirschner & van Merriënboer, 2013). There is no evidence to suggest, for example, that a new generation of youngsters are predisposed, somehow, to self-directed, self-paced, collaborative learning because their brains are somehow wired this way.

The divide is really one of disposition. Some youngsters are “immigrants” as much as some older people, and some older people are completely at home with technology. Exposure to, and comfort with a technology does not necessarily imply a capacity to use the technology in the most beneficial ways, in and of itself. For example, technology may afford self-directed learning, but it is one’s dispositions which determine whether or not these opportunities will be taken up. These dispositions generally need to be taught, and herein lies the central paradox of education. Discovery learning, as attractive as it sounds is ultimately a deeply flawed idea because of the scholar’s dilemma; how can you discover something until you know it is there to be discovered?

For example. Our brains, constrained by cognitive load, limit the ability to multi-task (Kirschner & van Merriënboer, 2013; Sweller, 1988). Our dispositions and habits, however, may allow us to handle multiple tasks with greater facility, overcoming the limitations of our biology to some extent.

Successful thinkers tend to embrace change rather than balk at it. Thinking Digitally means that you are constantly ready to adapt to change, and see it as an opportunity rather than a constraint.

Production vs Consumption

They say a picture is worth a thousand words. There is all the difference in the world between creating and editing pictures and viewing them. It is not, however, that the one is good and the other bad. There are skills and sensibilities, dispositions and capacities which are involved in both activities. To read a picture effectively requires a thorough understanding of the genres and contexts in which the picture was taken. Producing a picture also requires skills and abilities, understandings and literacies. I would argue then that we cannot privilege authorship above criticism. Both have value and a place. We are all at some stage or another a producer or a consumer of both analogue and digital technologies and products.

Nevertheless, there are good habits and dispositions around production, and likewise for consumption. These dispositions are likely to be very similar in analogue and digital contexts. Having said this, however, we need to highlight one vital difference.

All technologies require knowledge and skills both around production and consumption. But some technologies are clearly more complex than others and require specialised skills and knowledge. While almost everybody learns to read and write, very few learn to write software code. While most people can use a screwdriver, relatively fewer can use a soldering iron. This complexity factor limits and constrains the use of all technology. But digital technology represents a level of complexity which makes this division between people who can and people who can’t more stark. It is relatively rare to hear someone say of any analogue technology that it is simply beyond them and they cannot use it in any way. And yet this attitude towards digital technology is frequently heard.

A person who is relatively handy can tinker with, and fix a range of analogue technologies without ever being an expert in any of them. And yet, increasingly this tinkering is not possible with digital technologies as the technology requires such specialised skills and knowledge that the ordinary “handyman” cannot fix a problem.

I am no motor mechanic, but even I have been able to get a Volkswagen Beetle motor running again with a little logic, a prayer, and a spanner. There is no way that I could do the same with modern cars with their electronic complexity and sealed units. The growing complexity of our machines threatens to turn us all into helpless consumers, and robs us of any ability to tweak and tinker which an essential part of being an effective producer.

Personal computers were first introduced very much within a tinkering culture; the first computers were shipped with no applications – users had to create their own programs. These days the reverse is true – computers and devices are loaded with a wealth of applications, and programming is both unnecessary and discouraged. Production within each application is further consumerized by a move towards authorship using templates and wizards. Computing has moved from a strong producer ethos to one which encourages consumption. The rapid growth in computer usage explains this shift, but I would argue that as the user base expands so does the need to actively encourage producer dispositions, which are being lost by the ease of consumption.

Growing social complexity and knowledge specialization means that increasingly we are reliant on others to produce and fix, what formerly we could tinker with ourselves. This leaves us often helpless. While knowledge and skills specialization accounts for some of this movement from producer to consumer cultures, much of it is driven by underlying habits and dispositions. We can see in the Maker Movement (“Maker culture – Wikipedia, the free encyclopedia,” 2016) and in the thinking behind Computational Thinking, a growing reaction to this trend. As analogue technologies become increasingly digitized, I would argue that the need to foster producer mentalities and dispositions should be seen as a core aspect of Digital Thinking.

Successful thinkers display dispositions towards producer mentalities. Thinking Digitally means that you are able to Hack Your Life.

Creativity vs Drudgery

We face a future in which Artificial Intelligence will transform all aspects of our economy and society (Cellan-Jones, 2014). While we do not know what the future holds in store, I would argue that we need to see the growing technologization of society as an opportunity, and need to emphasise a disposition towards creativity rather than drudgery. Technology may be used to free up our lives for leisure and creativity, or for drudgery and work. Andrew Feenberg (1991) described the central contradictions between the potentialities for control and democratization inherent in technology, and pivotal to speculation over the role of technology has been dystopian and utopian visions of the future linked largely to these polarities.

Do we face a future in which a few use technology to control and pacify the many, in which humanity at large is debased by a digital divide in which they are passed over, or will technology free the majority from lives of drudgery to unlock their full potential? This is very much a political choice, and depends upon our social organization. The sharp debates around the politics of Austerity reveal the contours of the choices we have to make within the new world order, whether to accept Neo-Liberal Taylorist arguments about the nature of Capital, or to seek Socialist alternatives and a more equal distribution of wealth. The stark choice is whether we valorize capital above labour, or see technology as an opportunity to unlock human potential in ways not previously imaginable.

We urgently need a disposition towards creativity over drudgery in the ways in which we approach our use of technology.

Jane McGonigal (2011) has written about what she calls the four superpowers of games, and how these powers may make a better world. These superpowers form perhaps the dispositions of successful gamers. McGonigal argues they are the crucial dispositions for life itself. They are:

  1. Urgent Optimism
  2. Blissful productivity
  3. Social Fabric
  4. Epic Meaning

Her characterization of gaming as empowering in gamers a hopeful expectation of success in conjunction with productive work within a social network to accomplish meaningful tasks expresses a disposition towards optimistic, humanistic outcomes which resonates with a view of human purpose which is vastly at odds with the Malthusian vision of humanity as mere cogs in a machine.

Successful thinkers display dispositions towards creativity and unlocking their human potential. This requires constantly finding new ways to express yourself through technology, rather than allowing it to be used to marginalise your humanity. Thinking Digitally means that you are alive to the human within the machine.

Conclusion

In this exploratory paper I have attempted to argue that the most crucial element of our emerging relationship with technology is the dispositions and habits of mind we bring to our use of machines to automate and extend our thinking. The digital divide is often conceptualised as a divide around access to devices, but in reality it is a mental divide between those whose dispositions empower human creativity and problem solving, and those whose habits of mind limit the realm of the possible.

Bibliography

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Campbell, J. (1991). The Masks of God: Creative Mythology. Penguin Group USA.

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Posted by on December 6, 2019 in Computational Thinking, Critical thinking, Habits Of Mind, Learning Theories, Pedagogy, Thinking Digitally, Thinking Skills

 

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