Author: haymest (Page 2 of 8)

I do believe that we waste countless opportunities to make ourselves, our families, and our societies better because of the phobias we have about technology. We have done this to ourselves through poor design, breeding false mythologies, and the accretion of power to those who would perpetuate them. I continue to believe that technology, especially information technology, offers us unprecedented possibilities for liberation, both on a personal and societal level. There will be dislocations and political challenges, but we can overcome them with a clear-eyed view of the limitations and opportunities that our technologies provide us. Technology is neither moral nor immoral. It is amoral. It is a canvas upon which we paint. The picture we create depends entirely on us. It’s time to pick up the brush. – Discovering Digital Humanity, pp. 15-16.

Source: xkcd 1289

The New York Times is the latest media outlet to see ChatGPT as “technology” undermining education as we understand it. The fear that familiar institutions are being undermined is entirely justified. It is the inevitable consequence of systems of power based on Industrial Age technology being eroded. In recent chats about the technology with colleagues on Bryan Alexander’s Future Trends Forum, I compared ChatGPT and AI to the general alarm that greeted writing in ancient Greece.

And in this instance, you who are the father of letters, from a paternal love of your own children have been led to attribute to them a quality which they cannot have; for this discovery of yours will create forgetfulness in the learners’ souls, because they will not use their memories; they will trust to the external written characters and not remember of themselves. The specific which you have discovered is an aid not to memory, but to reminiscence, and you give your disciples not truth, but only the semblance of truth; they will be hearers of many things and will have learned nothing; they will appear to be omniscient and will generally know nothing; they will be tiresome company, having the show of wisdom without the reality. – Plato, Phaedrus

Plato/Socrates are not wrong here. It is hard to argue with the impact that literacy has had on human augmentation, but there is a lot of nuance to unpack here. We have all met humans who are well read but unwise, because they cannot properly apply the technology of reading/writing to their practice of life. However, as I wrote about in Learn at Your Own Risk, education is mired in a mindset that favors precisely this kind of book-service over knowledge-service.

All too often, the educational establishment (and those who seek to regulate it) equates the “reminiscence” of words with an understanding of those words. What we have witnessed over the history of industrial education has been a gradual scaling of access to writing, first through the mass production of books and then through the mass production of readers.

The reading and repetition of these words has become the bedrock of what we understand as “education.” Even those who teach critical thinking believe that without forcing our students to address this foundation first, we cannot get them to the analysis level of understanding.

This connective tissue of analysis, however, has proven to be a far more elusive (and hard to measure) goal, especially at the lower levels of higher education. I have spent a career trying to teach (and to figure out how to teach) “critical thinking.” It almost always fails on the shoals of trained practice and a lack of meaning in the student experience. I have seen many faculty (myself included) who claim to be teaching critical thinking through writing but who have capitulated to lower expectations.

We have trained most of our students to play along with the education game without really understanding what it was for. This invites them to do things like “cheating” the game because there is no opportunity cost, especially if no one catches them. More pernicious is the tendency to do the “minimum necessary” to pass the class.

ChatGPT threatens this construct. It has the critical thinking skills of a toddler, but we find that hard to distinguish from the efforts of our own students because we have such low expectations from them (derived, in my case, from long, hard experience). It may finally force us to address the loss of meaning many students experience when asked to conform to the existing educational paradigm.

After experimenting with it, I was confident that ChatGPT couldn’t do what I was asking my students to do. However, what I wasn’t confident about was whether I could distinguish between what it did and what they actually produced. It met the “minimum necessary” standard in many aspects of prose (although lacking in the proper citations). ChatGPT’s results weren’t very far off from the kinds of submissions that I routinely get from my students.

This realization didn’t make me toss out my prompts or assessment strategy, however. Instead, I grasped at the opportunity to use ChatGPT to get my students to engage in the critical thinking skills I claim to be teaching them.

My plan for this semester is to have them submit their prompts to ChatGPT as a draft for the first blog and then ask them to critique and build upon the AI’s results. This forces them to augment their approach by using the technology critically.

On a larger scale, however, ChatGPT is yet another chink in the armor of what we’ve been doing in industrial education for over a century. The technological threats to this have been mounting since the early days of the public internet in the 90s. Google search, crowdsourced papers, paper mills, question banks, etc. are all technologies that distributed collective intelligence has enabled. The resources at students’ fingertips have advanced exponentially even as faculty practice has not.

ChatGPT is moving so fast that most of my colleagues don’t even know it exists yet. However, they have been aware of the last two decades of internet-enabled technologies that have threatened our legacy assessment techniques, such as multiple-choice exams and standardized regurgitation essays.

In most cases, this realization has not forced them to re-evaluate their practice. Instead, defense has been the preferred strategy. Efforts to police the use of technology through proctoring and anti-plagiarism software are doomed to failure. If anything, pandemic remote teaching should have taught us that.

As I write in both of my books, the problem here is not one of technology, but rather of adapting ourselves, our practices, and systems to new realities. And, to take this further, there are tremendous opportunities resulting from these adaptations. We need real thinkers at all levels to tackle the complex problems of today and tomorrow.

Technology can connect us and augment us if we design and use it to do so. Applied properly, ChatGPT can form part of a suite of tools to make us better and more critical thinkers.

A friend of mine asked me the other day what I thought the purpose of society should be. My response was: we have a responsibility to our children to make the world better than when we came into it and societies should strive toward that goal. I then referred him to the Platonic concept of the philosopher-king. Technology has the possibility of making us all kings. Education has a duty to make us all philosophers.

Originally Published on the ShapingEDU Blog on January 12. 2023

We must get lost before we can find ourselves. Maps should not concentrate on preventing us from getting lost. Instead, they should point us to new ways of finding our way. Expressions like “we navigate learning“ don’t come from nowhere.

When we learn, we explore the edges of what we understand, but we also explore our imaginations and what they’re capable of. I wrote about this extensively in Discovering Digital Humanity. However, my work on the Tool Augmentation Tool reinforced my perception of just how important a role mapmaking plays in the process of creativity, innovation, and learning.

I recently wrote about how tools map our brains. Those who use those maps are engaging their brains in exploration. The idea is to get the user lost in their imaginations and then have to find their way back again. I use maps extensively in my classroom instruction in much the same way, as I try to map out the semester to my students while giving them ample room for creative exploration.

Creative exploration, however, doesn’t always happen. Both students and the academic decision makers that I regularly work with start with the assumption that I’m going to provide them with a map that will navigate them to their destination.

My challenge as a teacher lies in guiding without prescribing. This creates tension as I struggle to show them how to grow their own insights instead of just adopting mine.

Cartographic scholar Alan M. MacEachern’s work offers some valuable insight into how to create maps (and, by extension, all other kinds of abstract visualization) as tools for the visual exploration of information. In 1990, MacEachern and John H. Ganter wrote that:

[T]here is an assumption not only that the message is known, but that there is an optimal map for each message, and that our objective as cartographers is to identify it. For cartographic visualization the message is unknown and, therefore, there is no optimal map. (p. 65 – emphasis in original)

All-too-often we perceive the “destination” as a known entity. One problem with our growing dependency on Google maps is that we have lost the ability to find our own way through a map creatively. Most of the time, it presents a series of turns that magically transport us to the end of your journeys.

However, Google is not perfect. It makes certain assumptions when it plots the “optimal” route for me. The problem is that Google doesn’t really know me. It doesn’t understand my preferences for the journey. Do I want the fastest route, or do I want to compromise that to make the journey more relaxing? Do I want to explore a road I’ve never traveled before? It can’t really answer these kinds of questions.

Our educational processes often mirror the shortcomings of Google Maps because they likewise ignore the sensemaking aspect of our journeys. Industrial education has produced increasing levels of specialization, coupled with processes that emphasize “learning” modules and tests. Like Google, it gives us a series of turns defined as “courses” and “degree plans” that navigate the student magically to a degree.

We extend prescriptive navigation into the microcosms of individual courses. The term “course” itself implies a singular pathway through the process. Our college journeys have become nothing more than sequences of turns, lacking in sensemaking or meaning. Both students and the systems that control their movement through their learning journeys resist efforts to create randomness in that process.

A map with a singular pathway toward a destination is not a map, it’s a course. Maps imply a level of exploration. They should help you understand the broader context of your journey. Otherwise, we will never see outside the tunnel of our path and will miss the larger picture of the world that maps abstract. MacEachern and Ganter imply this when they state,

Maps and other visual representations are valuable to science, not because of their realism, but because they are abstractions. The abstraction process, if successful, helps to distinguish pattern from noise. p. 66

It is hard to create maps that encourage exploration without creating prescriptive instructions. In my classes, I try to create maps that explicitly force the students to explore. Getting them to follow them into the unknown and unpredictable, however, is not so straightforward. Grades form an unwavering destination for all of them. All that matters is finding the shortest path there, not what you may discover along the way.

I have a similar problem when I try to create maps to help others integrate technology into their practice. Considering a problem is more difficult than simply “getting the answer.” When I was working for an architecture firm, they were intent on having me produce an “ideal” learning space. When I pointed out that learning spaces were environments that helped people self-actualize their learning, and, for that reason, there was no one-size-fits-all solution, they didn’t like that answer.

Learning spaces contain within them implicit maps. We can extend this to any technology or technology environment. The Tool Augmentation Tool is an attempt to construct a map to help us understand the landscapes we create as we design environments for learning and innovation. It shows a series of pathways through a maze, but at every juncture, the user must add external inputs that change the character of the pathways that are being traveled.

We must also create maps that preserve a role for the teacher. You can teach by careful map design, but you can also design maps where either the teacher or a group of peers teach while using the map as a tool. The collaborative aspect of mapmaking is central to my practice as a facilitator of learning. Using tools like Miro to create maps of ideas opens vast new possibilities for innovation.

The Tool Augmentation Tool sets up a system of systems that moves users from tool to task in a variety of ways. It forces them to view the map from the perspective of a synchronous activity, both in-person and distantly. This shift in perspective creates different mental maps of the impact a particular technology will have on practice. The exercise then asks the user to consider the same two modalities (in-person and distant) as a set of asynchronous experiences.

Finally, it requires that the user reconnect these distinct explorations to form either a tool recommendation or a deep understanding of how a tool will impact a task., “The system should permit, indeed perhaps demand, that the user experience data in a variety of nodes.” (MacEachern and Ganter, 1990, p. 78)

A good map should force the user to zoom in and out and change our perspective. It jostles our complacency with “accepted” data. There are no “best practices” in this world. There is no “dogma” other than a goal of human augmentation.

Technology has made mapmaking infinitely more accessible. Tools like Miro have made interactive explorations of connective spaces possible in ways that were impossible even a few years ago. Building collaborative maps helps us find our humanity and make sense of a complex world of interconnections.

Sensemaking is the core of learning at all levels. It represents an intensely personal journey. We have a duty to help each other navigate that path but should not dictate it for others. Synchronous collaborative mapmaking makes it possible to journey together without giving up our individuality along the way. We are all designing the map of the future. Without collaboration and exploration, this would be an impossible task.

Tools extend human capabilities. From levers to steam engines, tools have augmented human muscle power. Parallel to this, other tools, such as writing and mathematics, extended our brain power beyond the individual. For almost a century now, computers have exponentially extended the reach of our thoughts.

Our brains are messy, particularly mine. Computers extend logic, but they have trouble mapping randomness. Translating the chaos of our minds into a logical framework has bedeviled human communication, collaboration, and group cognition well into the computer age. We continue to struggle to connect the chaos of our brains logically to the chaos going on in other peoples’ heads.

This is not something new. Writers live in this chasm. One of my favorite writing quotes is from Andy Weir, the author of The Martian, “Give a man a book, you entertain him for a night. Teach a man to write, you give him crippling self-doubt for life.”

A writer never knows how his or her thoughts are going to be interpreted. Will they be obvious, impenetrable, or laughable to the reader? Translating thoughts into linear text is a painful process (and one that I’m going through right now).

Even reading can be a fraught exercise. I have read the same text as someone else and come away with entirely different thoughts and interpretations of its meaning, what’s important, and even things that the author himself is describing but doesn’t fully understand. If I read an account of Ukrainian soldiers advancing through Russian defenses, I may extract a tale of improvisation and adaptation to circumstances. Others would certainly focus on the human suffering in the story. If I share the story, which story am I sharing?

We live in our own heads. It is incredibly difficult to understand how someone else will interpret or understand our words and actions. Creating tools to overcome this gap is a complex exercise under the best of circumstances.

Great writing comes close to achieving it, but few of us can make words line up that effectively. As Charles Bukowski puts it, “An intellectual says a simple thing in a hard way. An artist says a hard thing in a simple way.” (Notes of a Dirty Old Man, p. 207) “Art” is ordering communication.

Digital technology excels at ordering. Can it we apply it to ordering our chaotic thoughts more easily than the pain of pen and paper, or do the barriers lie somewhere else? This question has bedeviled much of my life and career. I have always been naïve enough to believe that technological solutions can expand the circle of “artists,” as Bukowski describes it.

I am constantly seeking ways to enable the artist in others. Often, I have used this as a prompt to construct an array of tools that stretch from physical to digital environments. These tools share one core purpose: they attempt to smooth the chaos of our thoughts so that we can share them with other chaotic brains.

Physical environments, like the many learning spaces I’ve designed over the years, can provide technologies to facilitate a wide range of connections. We can apply similar approaches to virtual spaces like the concept mapping spaces I’ve developed for my classes or the virtual networks of conversation I maintain with colleagues.

Both examples create maps of interaction for those who use them to augment their own minds. Effective learning and innovation spaces create networks that facilitate the sharing of ideas, both online and in-person. They help those who use them navigate complex narrative pathways collectively.

Complex thought mapping can also take us to the meta level. For instance, with the latest tool in my arsenal, the Tool Augmentation Tool, I am building a system to map the thought processes that I use when making decisions about technologies or systems that support those technologies. The goal is to provide a map for ordering thoughts while still giving space for others to inject their creativity into the process.

This is a complex map. I have constructed a set of tutorial pages designed to provide help for those who want to use it as a self-service tool. However, it may require an expert hand to steer through it. This is because, even after more than a year of attempting to simplify tool analysis, I recognize that there is no substitute for experience, mistakes, and iteration. This defines the limits of my narrative map.

Mapping our thoughts on the various tools is an arduous exercise. Just like with reading and writing, once you give the tool to someone else, they create their own narratives. These may or may not align with the narrative you have intended for the tool.

This is particularly true if systemic forces have trained your audience to think in ways that are misaligned with the intent of your narrative. For example, in my classes, I want my students to play and fail. This is central to any learning process. However, they have been trained by the system that failure is bad. They expect tangible rewards for just about any activity. I call this transactional teaching. It subverts many of the narratives my tools are trying to establish.

With the Toolset Project and the Tool Augmentation Tool, the challenge is that most of us have learned over the last 30 years to accept technological tools and innovations first, and then to adapt our practice around them. When we were told to go online, we were given systems to graft our in-person practices on to. This approach didn’t work very well. The resulting experiences have been disappointing.

This systemic reality has conditioned most of the audience for the Tool Augmentation Tool to accept tools as they are and to extol the virtues of this tool over another. We can use the TAT in this manner, but where its actual power lies is when we use it backwards and map tasks first before developing appropriate tools.

With the TAT, I have at least opened the door to this kind of exploration, but I suspect that it will be employed to evaluate tools before it will be employed to augment tasks. We often take tasks for granted and rarely break them down like Diana Laurillard does for teaching. As we peel that onion, we see how complex the activities are that we are trying to model when we map interactions with each other and those we seek to teach.

Balancing complexity with clarity is another acute challenge. This is a problem with game design. Simple and fun are often at odds with accuracy and richness.

Games are tools. Tools are games. As we construct games, we hope participants will chart a path through their mechanisms to achieve certain outcomes.

Games can teach lessons. Likewise, complex tools are maps of potential tasks. Like a game, they must balance order and chaos. We like to think ideas are not random. However, some of the best outcomes incorporate unexpected ideas from outside the usual procedural flow.

Our tools must support that without becoming too chaotic themselves. The conceptual tools we construct must also consider a certain aspect of randomness in order to stimulate innovation (or learning).

Creating an oscillation between lateral/chaotic thinking and an ordered process is central to any successful brain simulation. This is how our brains work. Thoughts float in and out randomly and then, occasionally, they coalesce into a moment of clarity. Communicating these ideas so others can understand is often critical to this process.

Building tools that synthesize order and chaos is in itself a process of ordering chaos. We now have the technological tools to do this at scale. The hard part isn’t the technology. The hard part is our brains. Shall we play a game?

Innovation requires disruption. Learning requires the deconstruction of established pathways of thinking. Change requires anarchy. These situations imply a certain level of chaos. Yet we seem to have an innate bias toward order in our online spaces and communities.

Perhaps it’s because the wild-west nature of the internet makes most people strive for control over what they perceive as a constant struggle against chaos. The result is that many of our online interactions are over-controlled. We stunt meaningful human change by tacking too much towards order.

Learning and innovation come from the disruption of established routines., Santi Furnari describes places where these kinds of breaks can happen as “interstitial spaces,” which he defines as, “small-scale settings where individuals from different fields interact occasionally and informally around common activities to which they devote limited time (e.g., hobbyist clubs, hangouts, workshops, meet-ups).” (HT Glen McGhee)

It is tricky to get the balance between order and chaos right, however. Too little structure and you risk what Steven Johnson refers to as an aerial network. Too much structure and you risk alienating your audience and turning them into passive spectators, not participants.

Furnari’s interstitial spaces pull the participants out of familiar network interactions and create spaces for “collective experimentation,” such as those exemplified by the Homebrew Computer Club, that can spark changes in practice (aka, innovation and/or learning). 

The content of the new practices is shaped via the collective interactions by which individuals engage with collective experimentation in interstitial spaces. Depending on how these individuals collectively interact and experiment, different types of new activities and ideas can emerge in the first place—that is, from different recombinations of those individuals’ different preexisting practices. In turn, these new activities and ideas provide the “raw materials” from which different types of new hybrid practices can eventually originate. (Furnari, p. 455)

Collective experimentation is particularly difficult to achieve in online spaces. Many, if not most, participants are engaging from within the context of their habitual environments. It is hard to achieve the true immersion necessary for the kind of shared meanings necessary for interstitial spaces.

At ShapingEDU, we have always attempted to create interstitial-type experiences. Our teams routinely create highly interactive online sessions that stand in marked contrast to many other remote events. In the “Four Stages of Zoom Enlightenment,” I used this work to and my experience as a participant in many other remote events to identify four categories of events. These ranged from traditional lecture/presentation (the lowest level) to digital constructivism, a series of live sessions connected by a persistent, tangible work project. 

Truly interstitial online spaces, however, remain elusive. Once you leave an online space (if not before), “real life” quickly takes over. Motivation to repeat the experience is overwhelmed by other responsibilities and follow-on visits to the space do not occur. Furthermore, as sessions become more predictable (an especially difficult problem for classes that meet frequently), there is little sense of the unexpected or anticipation going into the next session. 

Effective in-between spaces generate energies lacking in most of our day-to-day interactions with students and colleagues. This is because they create pockets of interactions insulated from the pressures of our daily networks.

“[I]interstitial spaces are defined both spatially and temporally. Spatially, they are small, in-between spaces – that is, small-scale settings where individuals from different fields meet. Temporally, they are short, in-between temporal spaces – short time intervals between the activities that individuals carry out, on a continuous basis, in their respective fields.” (Furnari, p. 445, emphasis in original)

We struggle to create these kinds of spaces online. Disconnecting people from the world around them (like my son does when he’s gaming) has long been a criticism of the online experience. However, this rarely extends to “professional” interactions. I know that many of my students, left unattended, would run my class as background noise and get on with their lives.

A common reaction is to over-structure the online event. Injecting order is a natural reaction to a perceived lack of control. One leader of the Homebrew Computer Club, Gordon French, tried this. It was not terribly successful:

Lee Felsenstein would later recall. “[Gordon French] would try to push the discussion to where he wanted it to go. He wanted it to be an educational event, holding lectures, teaching people about certain things, especially stuff he was expert on. He was very upset if the discussion strayed from people literally teaching other people in a schoolish sense. He would jump into whatever people were saying and get involved in the content, injecting his opinions and telling them ‘There’s an important point that shouldn’t be missed, and I know more about this kind of stuff.’” After the first part of the meeting, in which people would introduce themselves and say what they were working on, Gordon would stand up in front of the room and give what amounted to a tutorial, explaining the way the machine uses the code you feed into it, and informing the restless members how learning good coding habits will save you headaches in the future… and sooner or later people would get so impatient they’d slip out of the meetings and start exchanging information in the hall. (Steven Levy, Hackers, p. 179, O’Reilly Media. Kindle Edition.)

There is a spectrum between order and chaos. From the facilitator standpoint, tending toward order is easier to execute because you can control all the variables. This is also why it is so easy to gravitate toward a lecture-based approach to teaching. It also represents the lowest level of community engagement. 

If we isolate and dehumanize our audiences, our efforts are unlikely to stimulate creative growth in distributed communities of practice. In the artificial environments that we create online, and all-too-often in-person as well, it is easy to overlook the humanity of our participants.

Feeling our way toward the right balance is difficult, however. Open-ended discussions suffer from a lack of time boundaries. There is no pressure to bring the conversation to a close and so resolutions are rare. Mission creep is common. Bounded events risk stifling ideas because of a lack of time.

Perhaps the problem is that we are trying to over-control even this aspect of our interactions with one another. Furnaripoints out that connections between events are essential for establishing shared practices.

“[T]o constitute new practices, the new activities emerging in interstitial spaces need to be repeated over time, allowing new ideas to ‘stick’ – to be shared among the people interacting in those spaces, thereby being conducive to the formation of shared meanings around these new activities and ideas.” (p. 450) 

Repetition is more important than structure. It is repeated practices that form the catalyst for turning interactions into collective experimentation. Without them, even the most fruitful sessions are going to be largely wasted. Alternating periods of chaotic energy and thoughtful reflection should become repeated practice. 

One strategy for creating interstitial moments might be to establish periodic meetings where people bring their pedagogical innovations to the table and try to apply their techniques to the rest of the group. Another might be an open-ended book/article club where participants can suggest their own reading for group discussion and reflection (stay tuned on that one). I took part in such a group with four friends/colleagues several years ago. It resulted in many fruitful conversations and a lot of creative growth on my part.

Learners of all types benefit from a little chaos in their lives. It’s scary, but if applied in a safe space, discomfort can be a catalyst for exploration. We may not invent the next personal computer, but perhaps we can cut through some of the rigid order that characterizes so many interactions, especially online, these days.

It’s the beginning of the semester and I’m once again trying to bridge two incompatible systems. My students are used to closed-loop systems of education. They have had years of training in the rhythm of cram and exam (or some variation thereof). The “best” of them have mastered this pattern and start the semester trying to figure out my version of it. All of them see everything I/we do through this lens. The disconnect occurs when my class design doesn’t conform to their expectations.

The natural human reaction is to navigate the “maze” – and it is a maze – that I have set up with the minimum amount of effort necessary to get through it. Our students struggle to find meaning in the systems of education that have acculturated their habits of schooling. It is a rare student capable of looking beyond these structures. We program them not to.

One of my favorite scenes from Monty Python’s Life of Brian is the one where he tells the crowd “You’re all different!” and one guy says, “I’m not.” I feel like this a lot as a teacher. I try to convince my students that they need to engage in open-ended exploration, but they only want to know what I want them to do.

When I try to make the class expectations about them instead of me, they find this profoundly disorienting. My “final” is a web portfolio which they own. It’s a website on a server that they control. They’re creating a tangible artifact based on their own interests that they can use to show their communication and analysis skills to future classes or employers. They can take this assignment as far as they want. It’s an open loop.

Despite this, they never push the boundaries of what’s possible. Their focus is squarely on what is necessary. Necessary is always a closed loop.

Professional life today is not a set of closed loops. It is a set of problems, both large and small, that we must navigate. There are few instruction manuals on how to close these loops. The best we can hope to give our students are sets of skills that will prepare them for the unexpected.

One of the key failures of our educational system is that we structured it around routinized patterns that prepare our students for a world that doesn’t exist. Some students check out from clearly pointless routines. Others accept them and adapt their own patterns to match. Neither approach can solve complex problems. Getting through the routine motivates most of my students, not seeing what they can individually or collectively accomplish.

Perhaps most perniciously, they look upon collective effort with deep suspicion because the routine of education drives people toward zero-sum thinking. Whether you get through the system has little to do with whether I do.

This semester, and not for the first time, I had a student react strongly to the merest suggestion of graded group work. That’s because, inevitably, some percentage of the group will focus on the lowest common denominator necessary to “survive” the experience. The more engaged/savvy students don’t want to harness their wagons to drag those students along. They view peer learning as a trap.

Isaac Asimov’s “Profession” essentially parodies how far this kind of system can go. In his story, most “students” (they are programmed with knowledge instead of working for it) are directed, based on brain scans, to their “ideal” professions. They simply download the knowledge to carry out that profession into their receptive brains.

George Platen’s brain scans don’t conform to any pattern. The system relegates him to a “House for the Feebleminded” and he finds himself overcome by the shame of not being “allowed” to conform to the system.

Rereading this story just as the semester began really brought home to me the extent to which we mirror Asimov’s dystopian vision of education. I designed my class, within the constraints of the larger system, for the George Platens of the world. The rest of the system creates programmed individuals.

Unlike Asimov, I don’t believe that Platen is an exceptional case. I think everyone has, to a greater or lesser extent, a nonconformist impulse that results in creativity across a broad spectrum of activity. It’s just been buried by our closed loop education systems that emphasize conformity to process over creative, individualized approaches to learning.

These systems are no longer sustainable. Unbridled capitalism based on scarce resources has led to resource depletion, climate change and a general disregard for the needs of individuals. Many of the systems we are used to are not sustainable in this environment. Most of them were never equitable and depended on the exploitation of those less fortunate for their success.

In theory, learning represents one of the few open loops that exists in this paradigm. Open loops represent our best hope for navigating the thicket of challenges confronting our world. Over 75 years ago, Vannevar Bush recognized that closed-loop systems could neither manage the knowledge of the world nor the challenges that science and technology were creating. Following in Bush’s footsteps, Douglas Engelbart spent decades trying to apply technology to systematize open loop thinking, which he called “Collective IQ.”

Engelbart recognized that the fusion of technology with human collaboration was a means to bring humans to the level where they might confront the increasingly complex issues unleashed by the technology itself.

Consider a group’s Collective IQ to represent its capability for dealing with complex, urgent problems – to perceive and understand them adequately, to engage the stakeholders, to unearth the best candidate solutions, to assess resources and operational capabilities and select appropriate solutions and commitments, to be effective in organizing and executing the selected approach, to monitor the progress, to be able to adjust rapidly and appropriately to unforeseen complications, and so on.

He argues that we grow Collective IQ by exploring the “anticipatable” horizon leveraging both technology and our human capacity for imagination. This is something I want my students to do, albeit on a much smaller scale.

Engelbart augmentation horizon

Adapted from Engelbart

However, like Engelbart, I encounter resistance on a wide range of fronts, from institutions that are based on getting students through closed-loop systems of instruction to students who find the opened-ended nature of exploration disorientating.

These are issues that are difficult to resolve at the instructional level. The larger systemic context needs to support this kind of learning. This is a real challenge, as these systems are driven by larger societal factors, such as the “accountability movement,” that create perverse impulses toward closed loops.

If we hope to engage our societies in the project of Collective IQ to solve our urgent and unraveling challenges, we need to start with a realization of these interconnections and create systems of open loop learning. Our students are all different, even if they don’t want to be.

We like to think that learning takes place in a physical location. We call those places schools or colleges or universities. Often, we call those places classrooms. This is an incomplete picture. Those words describe places that can facilitate learning, but ultimately, all learning takes place in the mind.

We externalize learning because we have been trained to do so by more than a century of industrialized education. Digital thinking should liberate us from these logistical shackles, but that hasn’t happened yet. This disconnect is not a new thing. As early as the 1970s, Ivan Illich recognized how we commonly confuse learning with the physical manifestation of school when he wrote:

The pupil is thereby “schooled” to confuse teaching with learning, grade advancement with education, a diploma with competence, and fluency with the ability to say something new. His imagination is “schooled” to accept service in place of value.

If we disconnect learning from schooling, we can apply a much more flexible mindset to our design processes. This could have profound implications for how we design our pedagogy, programs of instruction, and technologies. These technologies include all the virtual and physical spaces that we can use to facilitate learning, not just the “gadgets” that may populate them. The key is to blend spaces and technologies into a continuum of tools that we can apply to any course or any individual who needs help to learn.

Our conception of “campuses” comes from the industrial notion of the factory. Factories don’t empower humans. They make us widgets in a machine. If you want more widgets, you build bigger factories.

Technologies often go through a period where they get bigger to maximize inefficient sources of energy and our ability to turn that energy to their purpose. In early aircraft, it was common to put more and more engines on a plane to generate more lift. Then we improved the engines and the ratio of engines to lift shrunk. The same is true for our educational technologies. Consider the cost and complexity of early Polycom systems and compare them to what you need to have a conversation in Zoom or FaceTime.

But this is also true on a systemic level. As we have attempted to scale education to a wider and wider portion of the population, the schools have grown to accommodate physical bodies in physical classrooms. It is high time we applied more efficient engines to our goals of connecting learners with knowledge and skills.

Remote teaching during the pandemic showed efficiencies are possible. Teaching and learning can happen wherever the student is. There is no iron rule that says the students must congregate in a specific physical location in order to hear the voice of the teacher.

Forcing students to gather excludes large parts of the population who cannot commit to being in the same place at the same time because of work or family obligations. It aggregates learning away from the individual, leading to less diversity through a reduction in individualized learning. These realities alone should lead us to question the current strategies for scaling education.

My experience as a remote teacher during the pandemic showed me the importance of community and collective engagement with the material that we were trying to learn. My students missed being able to congregate in person. What was missing, however, was not the classroom. It was the “hallway time” of informal spaces. We could move the classroom online fairly easily. Community time, however, was much more difficult to replicate. This realization led me to revisit the work I had done on informal learning for a local community college.

Immediately before the pandemic struck, I consulted on a new campus for Houston Community College. The brief for this campus was to maximize enrollment on a minimal footprint. Using classic measures of X number of student seats into Y number of classrooms that can be scheduled for Z number of hours did not work. This calculation showed that the desired enrollment was 50% higher than the space would accommodate, at least according to traditional measures.

Our approach to the resulting design was not to cram in more classrooms. Instead, we tacked in the opposite direction in order to maximize informal and support areas. This created a hybrid/blended environment where students taking online classes would find a place for collaboration and support. We would then effectively move much of the enrollment online but still create a hub for learning where learners could come together to form communities of practice.

This work led to many offshoots, starting with the STAC model and culminating in the Hybrid+ concept that I outlined in my 2020 book, Learn at Your Own Risk. The root of these ideas is that students need to be motivated and supported to engage in effective learning. This should form the underlying goal of any campus. Campuses with this design philosophy also support teachers that are trying to create individualized pedagogy.

That means that we should teach those things that require persistence, repetition, and convenience online. The campus would support everything from study groups to teacher-led small work groups to events that host outside experts. It would form a critical interface between students and the knowledge that they are seeking.

The other implication of this approach is that we need to rethink the nature of our courses. We should start by removing artificial distinctions between online and in person instruction. There is every reason to expect most courses to blend all modalities. The key distinction should be whether learning is expected to be synchronous or asynchronous, not whether it’s done online or in a physical space. All courses encompass both already. However, we don’t make efficient use of online resources to maximize the impact of the limited amount of synchronous time students and teachers have together.

Courses are tools used to contain discrete bits of knowledge. We build walls around them. This is another legacy of the specialization of undergraduate learning stemming from the factory model. The logistics of classrooms mean they are a scarce resource and that drives enrollment calculations and scheduling considerations. If digital learning means anyone can seamlessly teach or contribute to learning in a course, what’s the point of segregation?

With a fluid course model, any specialist can come into the course seamlessly and enhance the experience of the students, deepening their learning. Creating this level of fluidity will require systemic rethinking of how we organize our spaces, time, and structures of learning. We can build to optimize resources in all three areas. We can already adapt existing technologies and spaces to experiment with how this might work. For example, I already have a librarian embedded in my classes using nothing more than the affordances of my Learning Management System shell.

The learning space of the future is the mind. The technology spaces we build around that should reflect the realities of how people learn more than the logistics of how we educate them. Physical spaces, like the new Katy campus, which opened in May 2022, should form part of a much larger suite of tools, technologies, and people that will support learning in all its forms. This will also give us new opportunities to humanize, individualize, and diversify the education journeys for all.

There are certain books that constantly influence how I design systems for those I teach, advise, and facilitate. As I looked at the universe of books on that make up this list, patterns emerged. The list itself told a story. It was not an unexpected story, but I must admit that it surprised me at how suddenly it came into logical focus. These books orbit around the pole of postmodernist constructivism.

I discussed how constructivism has influenced my thinking in another blog, but it bears mentioning here that I think all technologists need to approach technological change with a constructivist mentality. As technologists, we build new worlds. Postmodernism deconstructs many of the paradigms of the old industrial world that we take for granted. Stripping bare the assumptions of our industrial culture is essential if we want to design authentically digital systems.

When I was studying postmodernist theory in graduate school, it was often attacked as rejecting the rationalism upon which humans built the modern world. Like many absolutist critiques, this is only partially true. Constructivist postmodernism accepts the processes of rationalism. However, it explores the possibility that our supposedly neutral analysis of the natural or social worlds is not really neutral after all. It challenges us to examine the social and historical factors in these biases instead of accepting human-constructed systems as they are present to us.

We should question the logic of every system. The overwhelming majority of systems we take for granted today, from government to business to education, were constructed using rationalist models. These systems now find themselves challenged by the fluid and fast-moving nature of technological change. The first signs of this come as “traditional” media being overwhelmed by “social” media, but other systems are increasingly coming under scrutiny.

What is missing from this all-too-familiar conversation is the idea that we can intervene in these changes to push humans to the fore. If we refuse to criticize inhuman legacy systems, we will continue our servitude to the machines. But we also have a responsibility to go beyond criticism and build new and better alternatives that bring people together instead of driving them apart.

As we build technology systems, we inevitably bump up against systems that reject critical questioning (see the “Understanding Systems” books on the list and my own Discovering Digital Humanity). Perceiving these systemic realities is essential for designing technologies that will not be rejected as being too threatening, but still reform practice to be more inclusive, diverse, and human. Applying constructivist thinking is an essential tool in achieving these goals.

As I neared the end of this project, I recognized that a Venn Diagram would provide a useful tool for visualizing how these topic areas overlapped and that the one area where they all overlapped is in the constructivist literature. The book that emerged at the center of it all was The Foucault Reader. While this is not the only constructivist text out there, it is one of the more approachable ones and summarizes many of the key tenets of the philosophy.

Constructivist thinking can seem deeply threatening because it seeks to question everything. As humans, we instinctively grasp at patterns of familiarity. They give us the illusion of control over our environments.

We construct systems for efficiency but also to protect ourselves from the unexpected. As a result, we often construct these systems reactively. They always incorporate human fears and cultural biases.

We find ourselves in a period of immense technological flux. This reality gives technologists immense power because we are the people constructing new systems from scratch. The job of the technologist is to support digital humanity through mindful design. Building systems of technology requires that we design them to augment the human experience. I chose the books on the list because they give the reader a primer on how to design technology, navigate systems, and construct networks of humans.

I organized the seven areas on the book list in such a way as to take the technologist on a journey from the concrete to the abstract. In the inner orbit, we start with technology design, progress to systems design, and then look at how systems push back against change (and strategies for working through that resistance).

The outer orbit contains books that teach us where we can use technology to create environments for human augmentation. First, we look at how we construct networks of knowledge. Second, we look at different venues of storytelling that the digital world opens up for us (word processing, visual tools, and gaming). Finally, we look at how we can design and adapt systems to achieve specific human tasks, from operating carrier battle groups to teaching and learning.

The last section returns to the center to look at the wellspring of constructivist thinking. If you progress through these areas of human-centered technology design, you can see Foucault with fresh eyes. In the coming months, I am considering reversing this journey using articles instead of entire books to show how you can use the end as the beginning as easily as you can use it as the end.

All the sections revolve in an orbit of powerful attraction around this basic idea that we construct how we see – either physically, virtually, or in our imaginations. If we understand this, we can see pathways to navigate to a mindfully designed future where the human, not technology or organizational/cultural constructions, stands firmly in the center. The alternative is that we can all become slaves in various forms of technological and systemic dystopias.

Given a choice, I always choose the humanist approach, but it often takes a lot of reflection to find that. The collective lesson in these books is that, as constructors, we can build systems that revolve around ourselves and are profoundly human. Collectively, they point us down the pathway to discovering digital humanity.

Our lives are narratives. We tell stories to learn from ourselves, to learn from each other, and for others to learn about us. A common theme emerged from the discussions at last week’s Mini-Summit on Emerging Credentials and Future Employment: Our credentialing systems’ signaling limitations distort the stories of what we’ve learned, what we do with them, and how we portray ourselves to those who might want to work with us. Our stories about ourselves are not getting where they can help us the most.

The goal of credentialing of any sort is to communicate achievement in learning (and doing) to potential employers as richly as possible. A basic tenet of the IdeaSpaces approach to technology is that we must always start with our goals and then work backwards to add the tools (technology and structures) necessary to achieve those goals. This is an iterative process, constantly looking at the technology environment to grasp new opportunities to augmenting our progress toward achieving those goals. Our tools and systems for communicating achievement at scale have never been good at telling rich stories and are long overdue for a re-examination.

Industrial systems of credentialing depend on cumbersome systems because the technology that they are based on, mainly paper, is an inefficient way of communicating the richness of an individual. It can be done, but the skill necessary to be a great writer/autobiographer is beyond the capabilities of most of us. Therefore, we’ve had to rely on shorthand representations of achievement that start with grades and assessment and “end” with diplomas, degrees, certificates, and resumés.

On the other end of this process, employers need high-quality employees. Once they exceed their immediately known talent pool, they have had to rely on abstractions of people to assess whether they will make meaningful contributions to the team. There is a reason that the best way to get a job has always been to know someone where you want to be hired. These shortcomings matter less for simple jobs than for recruiting innovative and creative talent. The needs of most employers are trending more and more to the latter category of worker.

Current industrial, paper-based systems of signaling create systems of connecting learning with employment. Their narratives are distorted by the mechanics of processing figurative and literal paper through normative structures. Richer canvases are available to us in the digital age. The signaling tools we have should reflect the richer learning journeys we experience in the digital age.

Iterating how we represent the data of our personal achievements is essential for relating the rich universe of ways we learn today, most of which are through informal learning. To cite just a few examples, we learn from YouTube videos, making, massively open online courses, or just by engaging in conversation within a distributed network of thinkers like ShapingEDU. These are not just passive exercises. It is possible to tell our learning stories through practical artifacts across a wide range of platforms, including videos, websites, and blogs. Learning is more transparent than ever before in human history because of these tools. Most methods of achievement signaling don’t use them.

The defining characteristic of the digital age is information plasticity. Data can be shared, remixed, and combined because it is digital. The success of micro-credentialing will depend upon its utility for creating a tapestry of digital stories that connect learning, credentialing, and employment better than legacy systems. Phil Long gave us a compelling illustration of what was possible in a world of digital stories when he described the Learning and Employment Records (LERs) Project he has been working on.

Our systems of schooling are only gradually grappling with these emerging realities. All systems are conservative tools. We build them to organize behavior for efficiency’s sake. We developed most of our systems of education during the industrial age, when the model was to transfer the efficiencies of the factory floor to the emerging information industries. Learners became widgets. The lubricants were the streams of paper that accompanied them at every step.

Industrial logic is deeply engrained in education’s information structures. These systems may have been computerized, but this has simply digitized paper rather than replacing it. Paper-based data streams create barriers to the richer narratives made possible by truly digital systems. Smaller bits of learning are lost. “Achievement” is expressed in the shorthand of degrees, transcripts, grades, and exams.

The third part of the story involves yet another disconnected set of systems: employers. We like to think of the market and private enterprise as being flexible and subject to easy change. The conservative nature of structures doesn’t change just because they happen to be in the private sector. Whether you are talking about education, government, or private industry, structures find efficiencies through routinization—often based on paper. The gatekeepers of employment are the human resources department. Their primary concern, and what drives them in their tool selection, is dealing with a daily deluge of paper equivalents. It is a defensive battle and defense makes for particularly conservative structures.

These systems add another narrative disconnect between learning and the ability of employers to perceive what potential employees can bring to the table. What is a better reflection of my ability, a resumé and cover letter or the rich tapestry of artifacts that I have built and shared?

We find ourselves caught in the gears of multiple anachronistic systems based on industrial principles and predicated on the technology of paper. The thing that keeps these systems in place is their perceived legitimacy. As Cheryl Grant pointed out in her presentation, the strength of new forms of certification being proposed lie in their distributed nature. However, distributed systems rarely overwhelm entrenched systems, no matter how anachronistic they may be. Instead of challenging systems directly, we need to figure out novel ways to construct stories that bypass the normative structures of signaling that currently dominate the landscape.

Graduates, even those with specialized degrees such as architecture or engineering, often lack the practical skills required by the employer. When degrees fail to signal specific skills, the learner’s ability to grow and learn independently is critical. Diplomas don’t signal our ability, but authentic work products do. Digital narratives offer us the potential to bypass anachronistic systems through richer mechanisms of storytelling. Labeling becomes less important if it is possible to convey actual artifacts of work.

Alternative systems of credentialing could communicate to the employer the ability of a person to contribute meaningfully to their teams by providing waypoints directing them to authentic artifacts of work. The reason that the current system works so poorly is that systems of education and hiring inevitably reduce the richness of the story of the learner’s journey. Alternative credentialing should not repeat this mistake and try to emulate legacy systems of certification. As an employer, I’m interested in where you are now, how you got there, and whether you have the potential for further growth.

Instead of challenging established systems, alternative credentialing can be used to tell rich stories of growth. These stories can relate the new ways of learning and sharing that the legacy systems miss and can give employers a much clearer picture of the person they are thinking about hiring. Deepening our understanding of ourselves and each other should be the goal of all learning. There is no longer any technical reason we should limit ourselves in the telling of those stories to the world with scraps of paper.

Digital technology introduced me to the idea that the world is an inherently constructed artifact. When I was a freshman in high school, my father gave me a blank slate called an Apple ][+. Over the next few years, I kept discovering new things that I could construct with it. When I got to graduate school a decade later, I discovered the work of postmodernist thinkers who were advancing the theory that language, stories, and structures of power construct our realities. These ideas, particularly the constructivist ones, resonated with me, because I recognized in them the same possibilities that I saw with my first computer.

If you can construct a world, you can also deconstruct the one that exists. There are no immutable laws, only human constructions. We can build our worlds anew.

Digital technology augments our ability to understand and redefine reality. By starting with basic ideas of what we are trying to accomplish, we can construct new technologies and systems to achieve those goals. We can work backwards (sideways?) from Foucault to Woz. The needs of the user should always define the shape of the constructed technology. This is the uniting philosophy of my work from IdeaSpaces to the ShapingEDU team’s work with the Teaching Toolset Project.

In postmodernist analysis, language creates and enforces power. How we define something constructs how we use it. Websters defines technology as ”a manner of accomplishing a task especially using technical processes, methods, or knowledge.” Douglas Engelbart’s conception of technology expands on this definition:

The conceptual framework we seek must orient us toward the real possibilities and problems associated with using modern technology to give direct aid to an individual in comprehending complex situations, isolating the significant factors, and solving problems.

If we start with the concept that technology is supposed to “solve problems”, we need to look much further than what we would typically refer to as “gadgets.” On one level, everything was high tech once, including the mundane like clothes, pencils, paper, walls, etc. Therefore, we need to think backwards and forwards as we consider technological solutions. On another level, human organizations, from governments to educational systems to corporations, are also technologies.

Adding human organizations runs against Don Ihde’s definition, which rejects “technology equivalent to any calculative or rational technique.” (P. 47, emphasis in original). Distinguishing technique from technology has a rational purpose because it separates the physical manifestation of technology from the mental manifestation of the task. The problem occurs when we become fascinated with the physical manifestations of technologies and overlook the mental aspects of what we use technology for. As a result, we are often frustrated in our tasks by the very technologies we create to fulfill them.

This central conundrum is the starting point of my new book, Discovering Digital Humanity, where I argue that our fascination with creating more and more technologies has overwhelmed our capacity to focus on tasks and to “augment” ourselves. If you want to drive a nail, it’s probably better to employ a hammer than a screwdriver. With mundane technologies, this seems obvious.

However, consider all the technological options we suddenly have for the task of expressing our ideas: pencils, word processors, concept mapping tools, blogging software, and that’s just the tip of the iceberg. Now take this up a level of abstraction and consider the integration of idea expression into the task of teaching someone else how to incorporate, modify, create, express, and share their own ideas and the complexity of the task of teaching becomes clear.

We need systems of technologies to approach teaching. We should also consider these systems technologies whose purpose is rationalizing and scaling the other technologies. They are ineffective in isolation from one another but share the goals of the original technologies employed.

Let us consider yet another definition of the concept of technology, that of German philosopher Martin Heidegger “as an ordering of the world to make it available as a “standing reserve” poised for problem solving and, therefore, as the means to an end. This challenging of man to order the world and in so doing to reveal its essence is called enframing” (Bijker, Hughes, Pinch, 2012, pp. 47-48).

Heidegger’s definition encompasses both physical and mental constructions of technology. Otherwise it’s impossible to “order the world.” Gadgets don’t order the world. Human structures do. Those structures fail because limited conceptions of technology limit our ability to assess how our systems fail. We like to point our fingers at broken technologies without considering the broken contexts in which they exist. We blame the tool and refuse to look in the mirror at our own failings. Technology failures almost always begin and end with humans.

Systems define relationships. Church and state define marriage, a human relationship. The “rules” of a profession often frames our relationship with technology. Frameworks shape how we express ideas. Environments shape our capacities to use technologies and technologies shape the environment that contains them. These are all systemic relationships.

Too many of our systems, from marketing to “best practices,” drive us toward thinking about technology as a thing that must be treated in isolation. This is one of the mental barriers we have had to confront with the Toolset Project. Most work in this arena takes place within systems of humans whose primary interest is the technology itself. Most of the participants in the brainstorming sessions were technologists conditioned to seeing technology as an end, not a means.

The technologist mindset is not typical of the world at large. The vast majority of humans have been taught to accept technologies and systems that compromise their goals. This is not some vast plot, but flows from this separation between physically and mentally constructed worlds. At the college level, we no longer teach people how to write in the technical sense of the word. We teach people how to express ideas and how to think about ideas. Writing is closely associated with a range of technologies and thinking closely associated with writing, but there’s an element of separation between thinking and technologies that we constantly struggle with, both as teachers and thinkers.

If we are going to create human-centered technologies and systems, we must acknowledge the centrality of the human-constructed paradigms in all our decisions. Constructing good paradigms and understanding bad ones is critical to our ability to achieve any significant goal.

All three levels of the IdeaSpaces framework are constructed paradigms. Space encompasses what most people think of when they think of technology. However, it goes much further than technical objects and includes everything that we might build into a physical or virtual environment. Time, as we understand it, is a human construct. We define the workday, the class period, and even when the sun comes up and down through our constructs of time. Structures are human constructions that establish frameworks, but they are also paradigms themselves. Therefore, just like any other technology, we can alter and adapt them to suit the needs of those who work within them.

There are many who might find this constructed world disconcerting. Digital technology creates a postmodernist technology environment. We are no longer constrained by massive built environments in the same way as we were during the height of the industrial era. We are no longer part of the machine, no longer subject to the factory clock, and therefore should not structure human organizations around these increasingly anachronistic realities.

Now is the time to drill deeply into what we need to accomplish as human beings, societies, and organizations and build up from there. There is nothing stopping us from imagining the shape of new worlds with the vast array of technology suddenly available to us. Being a part of constructing new worlds is why I love working with all the teams of creative minds exploring this terrain at ShapingEDU.