Author: haymest (Page 3 of 8)

Over the latter half of his career, Douglas Engelbart struggled to help organizations adopt augmented approaches to the technology that he had helped midwife in the 1960s. His Augmentation Research Center at the Stanford Research Institute focused on creating technology that would make us better, more creative, and more connected as human beings, but to the outside world he was merely “the inventor of the mouse.”

While innovations such as the mouse, the graphical user interface, and synchronous online work certainly humanized how we interacted with these new machines in profound ways, they did not change the social structures of work and innovation outlined in “Augmenting Human Intellect.” For a more detailed understanding of where he saw this effort go off the rails, see this video from 1998 (marking the 30th anniversary of the Mother of All Demos).

As I was attending the Smart Region Summit last week hosted by Arizona State University’s University Technology Office, I realized that this vision was taking shape more than half a century after Engelbart’s original work. The topics of discussion there ranged from broadband access to transportation to education in the Greater Phoenix region. The issues being addressed were not unique to Arizona. However, how they were being tackled was.

What the team at UTO has facilitated is conversations among communities that rarely interact during their normal course of business. New technologies of collaboration and discussion brought to maturity and widespread acceptance in part by the pandemic facilitated this melding of conversations that normally occur within silos. The fusion of ideas and projects that I saw last week was precisely what Engelbart had in mind as he wrote this in the 1990s.

An improvement community that puts special attention on how it can be dramatically more effective at solving important problems, boosting its collective IQ by employing better and better tools and practices in innovative ways, is a networked improvement community (NIC).

If you consider how quickly and dramatically the world is changing, and the increasing complexity and urgency of the problems we face in our communities, organizations, institutions, and planet, you can see that our most urgent task is to turn ICs into NICs.

The Smart Region group already laid the groundwork for this effort prior to the pandemic. From this foundation, the group successfully built upward, leveraging communities associated through geography. They could facilitate conversations about local, concrete challenges. It was the diversity of these conversations that technology fostered. Distributed collaboration technologies suddenly connected businesses, governments, and community groups that had never collaborated on this level before.

Over the past four years, another group within the UTO has also been attempting to create diverse, distributed communities. From the beginning, we conceived ShapingEDU as a different kind of educational community. However, ShapingEDU differs from the Smart Regions group in one key aspect: It lacks the geographic moorings of the latter group.

ShapingEDU’s strategic asset has always been its global, distributed design. The pandemic may have changed the substance of our efforts, but it did not alter our methods much. While we lost our annual in-person touchstones, most of our work and collaboration continued much as it had via technology platforms such as Zoom, Slack, and Google apps.

However, what is ShapingEDU’s greatest strength is also its greatest weakness. Localized concerns confronting community members often overwhelm the distributed efforts of the connected community. With any kind of distributed community, there is always the danger of it becoming disconnected from the immediate concerns and needs of its members. For communities concerned primarily with information distribution, this is manageable. However, for a community of doers, this presents a significant stumbling block.

There is another analogy. As teachers, we encounter similar challenges if we attempt to turn remote classrooms into anything more than information distribution mechanisms. Keeping the students actively connected to the conversations in the class has proven to be a primary challenge, as we have experimented with remote teaching. As a teacher, I’m always trying to boost the “collective IQ” of my students.

As an organization, ShapingEDU has always tried to boost the “collective IQ” of its participants and the larger education community. One approach to this challenge of distributed connection would be to adapt the model of the Smart Region project to create nodes of connected network improvement communities. These nodes would be localized and connect diverse teams. This same approach could scale the Smart Region approach to other regions.

A connected series of nodes was the vision of the short-lived FOEcast group that many members of the ShapingEDU community were a part of in early 2018. We envisioned a “distributed university” connecting and assembling insights from groups working around the globe. The global organization would facilitate conversations, collect work, and act as a distribution platform for these geographically dispersed groups.

Practically, what this means is that the doing of the working groups must be profoundly local and that the efforts of the distributed group would to facilitate global dreaming into localized doing. This is something ShapingEDU’s Universal Broadband Project Team has excelled at. Groundbreaker Lisa Gustinelli has connected national resources to profoundly local needs in Belle Glade, FL, by bringing FCC resources to a local community desperately in need of better connectivity to thrive.

ShapingEDU has always mapped out a vision where the distributed imagination of the collective group generates impactful local action. This is only possible because of the tools that technology has developed for distributed and persistent engagement. However, as Engelbart understood, our human organizations need to be optimized to take maximum advantage of the opportunities that technology creates. ShapingEDU creates fora that stimulate creative play, offers practical guidance, and provides opportunities for congregation and the sharing of insights.

The vision that Doug Engelbart consistently articulated was that we should use technology to augment our capacity to be human. In this, he echoed Vannevar Bush’s vision of using technological affordances to connect communities of thinkers. It is only through these networks of ideas that we can hope to tackle the enormous problems that were the detritus of Industrial Age thinking.

Many of the challenges that the Smart Region team are trying to address have to do with community responses to Industrial Age challenges of sprawl, pollution, and equity. Education faces similar challenges that are a legacy of systems of Industrial Age thinking. We are struggling to adapt institutions and practices designed for elite education to foster diversity and equity.

Overcoming these barriers will require a diverse community of thinkers to support a vast network of doers tackling the shifting landscape of education unique to their circumstances. As William Gibson said, “The future is here. It’s just not evenly distributed.” Supporting unevenly distributed “presents” will require creating networked improvement communities committed to building their best “futures” through deep learning and reflection. A fusion of models might just get us there.

Life is complicated. At any given moment, a thousand things are happening which impact my life. An exponential number more will impact my life in the future. Most of these things are things you only have a vague awareness of, at best. Additionally, I manage systems in my body, from the infinite complexity of my mind, to the autonomic beating of my heart, to complex interactions between the three as my fingers dance across the keyboard to type these words.

As we teach, we are also constantly abstracting. I explain the complex workings of the US government using models and simulations. A biology professor does the same as she explains the complex interactions of cells in a biological system. Neither one of us would claim that we are doing anything more than abstracting reality to make it understandable to our students. One of my favorite jokes is the one about the student who studies Intermediate French to prepare for a trip to France. When she gets there, she discovers they don’t speak intermediate French in France. The joke is that “Intermediate French” can only ever hope to be an abstraction of the richness of the living language as they practice it in France.

Games also abstract reality. Games have always fascinated and frustrated me, because they try to abstract complex actions into repeatable activities. It’s always a balancing act between accuracy and gameplay. Some games are very abstract, such as Go or Chess. Much like mathematics, they lean into gameplay and abstract mental interactions. At the other end of the spectrum, war games often attempt to model complex historical and technical interactions while acknowledging the role of chance in historical outcomes.

In his excellent book, Of Dice and Men David Ewalt argues that one attraction of more open-ended roleplaying games such as Dungeons and Dragons is that most of the activity involves storytelling rather than arguments about bounding the universe. While there are core rules, the logic of the experience is constantly evolving in the minds of the participants. Ewalt says that the frustration of war gaming is that, “only 10 percent of the match is really spent playing. Half the remaining time is spent arguing about history and the other half arguing about the game’s rules.” (Ewalt, p. 52) I find this to be a rather accurate breakdown of the experience.

However, I think that attempts to align history with rule making are of immense value. I have been playing wargames with a group of friends (all of who work at the college with me) since the early 2000s. For most of that period, we engaged in an ongoing iteration of the classic Axis & Allies wargame. Now, if you knew the printed rules of the game, you’d hardly recognize the version we were playing.

One of those friends once reflected to me that he wondered whether we were engaged in an immense time-wasting activity. I pointed out that as administrators and teachers, the construction of systems of rules, whether we’re talking about course structures reflected in a syllabus or the design of spaces and programs in which those courses lived, was the same mental exercise we engaged in as we attempted to construct systems of rules for the game. The learning was in the invention.

We engage in a constant modeling of reality as part of our daily exercises in sense making. Rules connect our perceptions of one another. What are the rules for sharing my ideas? What rules can I construct that will connect my realities with those of my students? The projects in ShapingEDU are also trying to construct their own models of effective engagement with the world. Some do so directly, such as with Ruben Puentedura’s Black Swan and Serious Play initiatives. Others seek to model a sense of the world, such as the Pandemic Teaching Reflection project. My Teaching Toolset Project is seeking to codify a set of rules that will model interactions between actual teaching behavior and the tools we use to carry it out. The Broadband and Student Voice projects are trying to construct maps through systems of governance and education to achieve their goals.

We are dealing with seriously complex systems in these projects. Explicitly or implicitly, we are trying to create or understand sets of rules that abstract reality. This brings me back to my original conundrum: How do you model complexity while maintaining gameplay? There’s a reason that most people don’t like to play complex games such as wargames. New players must confront a steep learning curve before they even get to the part where they’re engaging in strategy. The level of detail can be overwhelming.

Technology doesn’t help us here. Modeling reality in most video games results in mental (or physical) overload as you try to mimic body movements through a keyboard that you would otherwise engage in reflexively. Extending that to a team, as many sports games do, only multiplies that effort. In contrast, competition in Dungeons & Dragons takes place almost entirely in the imagination (with a little help from the dice).

Some may argue that I’m conflating modeling with gaming, the latter being subject to the whims of chance. I would counter that by saying modeling works in a Newtonian World but that a relativistic world operating under the principles of emergent design we cannot escape probability and uncertainty. Uncertainty inevitably introduces elements of chance and randomness. Frameworks such as simulations and games help us make sense of random outcomes and to adjust the rules going forward.

We need to pay attention to the “rules” we are following and recognize that they are themselves part of the game and subject to modification. Explicitly designing sets of rules helps us better understand the compromises we are forced to make in the service of insight. We can create new and novel ways of playing games of understanding, such as the clever modeling of university leadership through matrix gaming that Bryan Alexander ran with his graduate students at Georgetown University. I am always looking for new and better ways to simulate and game systems and to systematize games. We have a tremendous opportunity to do the same with ShapingEDU.

We have too many closed games in our world that are the equivalent of Intermediate French. Understanding the mechanics of how we construct games can help us construct richer systems of understanding. To do this, we first must recognize these limitations and never stop questioning and refining the rules. Wherever possible, we should create open-ended games, such as Bryan’s matrix approach. However, sometimes the act of creating the rules/constraints provides new insights into the challenges we face. Creativity requires constraints. However, rules should be explicit and subject to iteration. We should never forget that our ability to model a complex world depends on the lenses we use to see it. The rules of the games we construct form the design parameters of those lenses. Let’s make sure we use them to see the world in new ways.

Electrifying Education Part 1: Being There

Electrifying Education Part 2: If Tesla Engineers Designed Education

A common design strategy is to imagine solutions free of systemic constraints. This has several advantages. First, it focuses imaginations on the goals of the effort and may clarify them. Second, it highlights those parts of the system that may need to be adjusted to maximize outcomes. Successful electric car designs don’t simply replace the engine with an electric motor, they reimagine everything from weight distribution to safety to ideal ranges vs. battery size and cost. Under this exercise, a car has wheels and seats, but everything else is subject to radical redesign. In a digital world, it is possible to reimagine education in the same way.

To do this, we need to strip down what a “course” actually means. The word implies a journey, not a destination. Yet our courses were all about the destination (aka “getting it over with”). Classrooms are a destination. We “go to school.” We don’t “go to learn.” The first step in imagining what a learning journey in a digital world could look like is to explode the notion of school as a destination and instead imagine it as a waypoint in a much wider journey.

Classrooms are a finite resource. Resource distribution always devolves to resource rationing. Rationing drives the pace of learning and implies an end to accessing it. If we cannot get past our fixation on physical classrooms, we’re just replacing a physical classroom with a digital classroom. This is about as insightful as replacing a gas engine with an electric one and not engaging in any further design effort.

Remote teaching brought on by the pandemic stripped down instruction into its components by removing a lot of systemic constraints. I was well-placed to take advantage of this situation, because I had already begun a systematic redesign effort years before the pandemic. However, even under remote instruction, there was still one linear constraint that was very difficult for me to get past: my time. With smaller classes, the increased investment of time necessary to reach each student individually and to understand and address their specific learning needs was still manageable through creative use of technology. However, with larger classes, the systems I put in place were severely stressed.

Addressing these challenges required a greater modularization of my time. That meant that my instructional strategies must bring in additional specialist help. I talk about the potential of strategically deploying specialized support in the STAC Model. Creating a constellation of on-demand instruction and support, as well as explicitly deploying that as part of an instructional strategy, makes it possible to scale individualized instruction much more effectively.

While the STAC Model focuses on informal learning through librarians, tutors, counselors, and designers, we should also consider this model for creating teams that span disciplines within courses of study. I could spend a lot more time teaching students the nuts and bolts of government if I didn’t have to spend most of my time teaching them how to construct logical arguments. Those students who need additional help in particular areas could receive detailed help in those areas if I didn’t have to homogenize my instruction for the needs of the larger class. This is one characteristic of individualized instruction that makes it such a powerful tool, but it is very difficult to do with larger classes while working alone.

I have already done some limited experiments augmenting my class with an embedded librarian. These have yielded promising results. For certain issues, I can send students to a familiar face who also has a slightly different perspective and problem-solving approach than me. However, this is an ad hoc solution. My colleague, who is extraordinarily helpful, is often called to other duties serving the larger student body of the college.

The five areas of instruction identified by ShapingEDU’s Teaching Toolset project provide one way of envisioning a learning “space” for a much more robust modularised learning team. Different team members could occupy different spaces with groups of students tailored to the immediate learning needs of that segment of the cohort. Strategically employing different modes and talents in this system means that relatively large groups of students could move through the process in parallel. With clever design, we could maintain capacity while expanding individualized instruction.

The Teaching Toolset Matrix

Imagine this diverse learning “space” occupied by a team with a central project. Perhaps the space is, like my class, about a student’s role as a citizen in a democracy. A political scientist leads the team. It also includes an English professor, a librarian, a designer, and a statistics professor. This team designs a course/journey for groups of students that culminates in a project, which asks students to identify a wicked societal problem, analyze some approaches to dealing with that challenge, and lay out a roadmap for dealing with that challenge in the American political system. The waypoints are a series of blogs (public writing) that deal with each one of those pieces sequentially. The final product is a website that communicates a change strategy to the public.

Breaking down that process into a set of learning waypoints creates opportunities for teaching by each of the team members:

• • The English professor would teach argumentation and logic
  • The librarian would teach digital literacy and research methods
  • The designer would assist students in figuring out how to tell their stories through a range of technological tools that maximize the impact of the storyteller on the audience
  • The statistician would teach data analysis
  • The political scientist would frame it all into the structures of the political system

Expanding the learning network to embrace a wide range of tools creates nodes between these constituent parts. It allows students to move seamlessly from one area to the next fluidly and on demand. Strategically employing toolsets, each person in the team could connect individually with students. Even working within the constraints of traditional academic terms this would significantly increase the richness of a student’s learning experience. If we explode that constraint beyond an individual course, we could link projects to meta-projects that could provide context to an entire collegiate journey.

These ideas are not novel. However, they have always come up against a range of systemic constraints, from disciplinary to economic ones. My modest suggestion to distribute the engines of learning more efficiently will surely be met with logistical objections related to scheduling and workload. These concerns inevitably lead back to systemic paradigms connected to physical classrooms and butts in seats. It takes a team to create deep learning. Depending on a “hero” teacher to do that is asking a lot. Digital technology facilitates teams. We should take advantage of that.

Arguments against this kind of approach are very similar to those who argue that we can never make electric cars work in the same way as internal combustion engine vehicles do. This is not a very productive way of thinking about the fundamental problem. With vehicles, we need to maintain our transportation infrastructures, while eliminating the problem that they are currently killing our planet. With education, we need to maintain learning in the face of demographic and equity challenges (exacerbated by climate challenges) while maintaining rigorous instruction.

For either of those imperatives to be met, we need to be prepared to jettison anachronistic vestiges of the prior system. Creative rethinking of our systemic constraints coupled with optimizing our toolset opportunities provide a pathway to realizing what education was always meant to be and could become again.

Electrifying Education Part I: Being There

There are many parallels in how electric vehicles are disrupting the transportation industry and in how digital has the potential to disrupt the education industry. To realize the potential of electric vehicles, we must grasp changed opportunities for reaching our destinations. To realize the potential of digital, we must grasp changed opportunities to reach our students.

Electric cars change everything from the design of the car to how they’re used. With an internal combustion engine, the nature of the engine dictated the design of the car itself. Form followed function. Its impact stretches far beyond the design of the car itself. The impact of this one innovation of the 19th century still reaches into every corner of our society. So many of our systems, from fueling networks to urban planning, are explicitly or implicitly designed to support the internal combustion engine. The electric car disrupts these patterns. We just haven’t noticed it yet.

Digital education is a similarly disruptive force. It changes everything from the design of instruction to the systems where it takes place. Like the internal combustion engine, the classroom drives the design of instruction. Systems are, explicitly or implicitly, designed to support the concept of putting as many students as practical into the same physical space as their teachers. This is also an innovation of the 19th century telegraphed into today. We build campuses around classrooms and their enrollment capacity. Headcount based on contact hours dictates funding. This thinking stretches into classrooms that don’t exist in any physical sense. Everything revolves around the basic assumption that the classroom drives instruction.

Both systems are facing a reckoning. It is clearer every day that we must wean ourselves from the internal combustion engine. The pandemic has similarly shown us what happens when classrooms are wiped from the table. Much like an electric car, digital education liberates us from the constraints of form. It shifts our notions of space and time.

Moving students around from class to class and all the infrastructure built around that is dictated by the constraints of physical spaces. It’s logistically difficult to split off groups of students based on learning needs. The form of the classroom drives the shape of instruction.

Design shapes behavior. The fluidity made possible by both electric engines and digital education opens huge possibilities for design. Electric cars, liberated from the centrality of the internal combustion engine, are essentially modular. Digital education tools are also modular. Because learning can take place anywhere and at any time, teachers can plug and play instruction, employing a wide range of tools unconstrained by time and space.

Supporting electric cars is also more modular. Since any electrical outlet can charge them overnight, every house can become a gas station. If there’s anything the pandemic taught us, it’s that presence in a classroom is not a precondition for learning. Every study can become a classroom. Over the last couple of years, we discovered a vast array of modular, digital technologies that we can plug in anywhere in the learning process.

There are weaknesses to both the supporting infrastructure underlying digital learning and that supporting electric vehicles. With electric vehicles, it’s long-distance travel and charging times. Digital educational systems also face constraints. For one, the reach of broadband in the United States has shown itself to be a serious problem for a lot of communities, particularly those more economically vulnerable. Instead of constructing buildings to bring more students into educational networks, perhaps institutions should focus resources on constructing better networks of all kinds to connect learners where they are. This shift would require them to reimagine their paradigms about what constitutes a community of learning.

There is a general lack of recognition of how digital instruction is different and how this demands that we approach its delivery in novel ways. As we discussed in part 1, many institutions look at the lack of physical constraints in the digital environment as an opportunity to have a “classroom” that they can pack as many students into as they want. As a result, digital/online classes are often larger than their physical counterparts. The limited research in this area shows that digital sections should have fewer students to allow for greater personalized instruction and equity. Lower costs and greater flexibility should allow institutions to do that. However, most institutions continue to view the economics of digital instruction through an analog lens.

While we have a vast infrastructure devoted to traditional forms of education to fall back on, the last 18 months have shown us how brittle that infrastructure can be. In almost all instances, however, this brittleness comes down to a failure of imagination. To cite just one example, we continue to measure learning through various time-on-task indicators such as contact hours, which imply live, direct content delivery. This is a little like evaluating an electric car based on gas mileage.

We have so many more ways to engage our students than forcing them to sit patiently through our florid prose. There is increasing evidence that there are better ways to instill deep learning. When you are standing in front of 500 students in a lecture hall, it feels like you have little choice. But that’s because you’re looking at lecture like it’s a well-tuned (hopefully) internal combustion engine and not a compact electric motor you can plug in anywhere to the learning process. This is another example of form driving function.

Instead of being constrained by the mechanics of what you perceive to be possible because of the technology and the system that put you in that space, break it down by purpose. In a car, that purpose is to get to your destination efficiently and safely. In a course of instruction those purposes vary more widely, but in my classes my purpose is clear: I want to teach my students the skills to engage with their learning, not just regurgitate information. The actual content is useless without giving them the ability to process it meaningfully.

We must learn to recognize the commonalities of our purposes and separate them from the mechanics of the technology. Figure out how to plug your lecture into the students’ minds rather than relying on the inefficient transmission possibilities of most physical spaces. This does not mean you do away with it, but it means you think strategically about where on the engine of learning that you put it. We do not measure learning in time or space. We measure it in reception and comprehension. Instruction should reflect this.

So much of our institutional energy is focused on the modes of transmitting information to our students. We should focus on the transmission of learning itself. From invasive assessment regimes to endless, mind-numbing remote lectures, remote teaching highlighted transmission as a point of failure. It’s past time to consider how we can go digital and modular to make the transmission of learning more antifragile. We will not do that by making it more complex and trying to emulate outdated patterns found in classroom-based instruction. Much like creating an environment for supporting electric vehicles, this transition will require a shift in how our systems treat learning. Let’s hope that the pandemic has created a spark for driving learning in unexpected directions.

In Part III, we will examine what applying lessons from electric design could look like.

The scarcest commodity in my class is me. I don’t try to make myself scarce. I make it clear to my students that they can always find me by email and that it’s no big deal to fire up a zoom session. But, despite my mastery of digital time and space, I’ve never managed to be in two places at the same time.

The focus of industrial learning has been to scale the learning experience to accommodate greater numbers of students, so that education was no longer the province of the elite who could afford personalized instruction. Unfortunately, this has been accomplished largely by putting more and more students under the gaze of a single teacher employing a large lecture hall and amplification. We scaled the voice but missed the point that talking is not synonymous with teaching.

I can still remember walking into my first 500 person class at the University of Texas at Austin as freshman there in the 1980s. I was lucky in that class for two reasons. The first was that the professor was a dynamic speaker who introduced interesting concepts about a subject I cared a lot about. The second reason was that I was used to teaching myself instead of relying on someone else to do it for me. At a young age, I developed a love of reading and the fact that my father was a university professor meant that I always had access to excellent university libraries. I gave myself a parallel education from the one I received in “normal“ school. I aced the class.

Fourteen years later, after nine years of higher education and a detour into the tech industry, I walked into my first community college classroom determined to emulate the experience of that very first government class I took at UT. It was a dismal failure. I discovered that almost none of my students shared my love and understanding of learning, no matter how dynamic my performance in front of them was. Most of the students at this urban campus did not know what it meant to educate themselves or why it mattered that they did.

That was almost exactly 20 years ago. I have spent many of the intervening years trying to figure out how to reach those students. This journey has involved treks into pedagogical design, learning space design, and the application of every technological trick in my tool bag.

The gains have been incremental. I have realized considerable efficiencies in the application of creative approaches to teaching and learning. However, my students continue to struggle. There always seem to be a percentage of them that refuse to be reached no matter what I do.

When the pandemic hit, I was teaching one of the more challenging groups of students that I had ever encountered. Now, besides daunting college course material, I had to navigate them through a technological burden that they had not signed up for. My solution was not to continue business as usual, but to lean even more heavily into individualized instruction than before.

Zoom allowed me to meet individually with students in a way that was difficult, if not impossible, in a physical classroom where the best that I could hope for was group interaction. Most community college students do not linger on campus. I can count on one hand the number of times students spontaneously walked into my office hours in any given year.

Most of my students have significant external responsibilities, such as families and jobs, that take up almost all of their non-class time. College is seen as a luxury, a bet on an ephemeral future self that must always take a back seat to present concerns. The pandemic exacerbated the concerns of their present selves as they or their relatives sickened and jobs evaporated or became extremely stressful affairs. To add to the misery, flawed technological systems, which were their only lifeline to the world of learning, often collapsed under the strain.

I was very proud of my success rate in that first semester of remote teaching. After careful analysis, I only found one student that I lost for reasons purely related to remote teaching. I accomplished this feat by meeting individually with every student. I prioritized these meetings over every other synchronous activity. The first question out of my mouth was always, “How are you doing?” It was through this emergency stopgap that I discovered the power in these interactions. Instead of insisting the students come to me, I could meet them where they were and to connect the work that they were doing in the class with what they were going through.

Since then, I have not taught a single course in person. I have made these individual meetings a fixture in my instructional method. I can do this through the power of the technology in my toolbox. These insights have altered even the group meetings where some or all of the class is in Zoom. I started using concept-mapping software like Miro to actively and explicitly connect individual projects and interests to the material of the course. In this way, I can meet the students where they are instead of trying to feed them where I am. (I am feeling some trepidation about next semester when I may be forced to give up these tools and go back to slumming in a classroom.)

Until this point, I have been lucky that all of my classes have been under 18 students. This semester, however, I have two classes with 32 students each. I knew going in that this was going to present a challenge to the teaching models I had developed for remote students. I have a pretty clear idea of how much time and attention I need to give each student. Early on, the class sizes were already impacting group activities within the class. There simply aren’t enough minutes in our scheduled meeting times to reach every student.

This has already led to attrition. Out of over 60 students, only 41 students turned in the second major assignment. Ironically, the class has right-sized itself, but there have been casualties along the way. It should not be surprising that under these circumstances that the most accomplished students will push themselves to the front of the line. Those who never make themselves heard will sit quietly and watch the class slip by.

The only way to manage large groups of students is to talk at them instead of with them. This works with the more accomplished students. A practiced learner can get through my class without ever attending an interactive session. Most of my students don’t fit into that category.

In recent years, several studies of students in distance education have shown a linkage between overall performance and the way the class is taught. They show it is almost impossible to teach the class constructively and reach at-risk students effectively with over 24 students per teacher. As Sandy Baum and Spiros Protopsaltis found in a 2019 study, “Even when overall outcomes are similar for classroom and online courses, students with weak academic preparation and those from low-income and under-represented backgrounds consistently underperform in fully-online environments.”

I can feel those numbers this semester as I struggle to find the time to reach those students that need my help the most. The economics of teacher-student ratio vary wildly from institution to institution. Administrations will argue that trimming class sizes is simply not possible from an economic standpoint. However, the problem may not lie in “class” sizes. Instead, it may lie in a failure to imagine how we might group students in ways that are not based on “butts in seats.” There is no reason that classes still need to meet that outdated industrial standard. If we ever want to get past merely educating the favored few and reach talent that is less favored by circumstance, recognizing the power of individualized instruction is the only realistic pathway. The logistics of instruction are not an excuse.

The digital world offers us new opportunities that bend time and space. Bending time and space provides many opportunities to scale individualized learning. Scaling individualized learning is the only way to create equity for those students being failed by the systems we have created. We can only scale individualized learning by reimagining how we deploy our resources in the service of all of our students, not just those most capable. To do that, we need to look far beyond the classroom itself to the infrastructure that supports its continued primacy in educational philosophy, planning, and execution. Electrifying our analog systems provides opportunities for us to re-examine this paradigm.

Next Up: Electrifying Education (Part II): If Tesla Engineers Designed Instruction

As technologists, we often have our minds set firmly on the future. We have made it a hallmark of our profession to find the latest and greatest to share with our communities. Sometimes this results in innovative outcomes but all too often these efforts result in intriguing “projects” that never seem to take root in the fabric of our institutions.

We are so trained in this approach to reshaping pedagogy that, when we are asked to develop innovative approaches to teaching and learning, we instinctively grasp for our toolboxes instead of considering the pedagogical approach or other purposes of the technology first. All too often, technology guides the purpose and not the other way around.

The weaknesses of this tendency became apparent last year as most institutions were suddenly forced to lean heavily on their technology infrastructures to maintain continuity of instruction during the pandemic. Those institutions with a diverse set of tools that complemented each other and provided faculty and students with low barriers to entry had relatively smooth transitions to remote teaching.

However, those institutions that had not devoted much attention to their technology infrastructures ran into repeated problems as faculty and students bent technology to meet their learning needs. More often, however, we were driven to compromise instruction in order to do anything at all with the tools at hand. Even institutions that had relatively sophisticated technology infrastructures struggled if those tools were hard to use or did not incorporate antifragile design principles.

Challenges always look for weak points in any system. This is true of COVID, which looks for weak points in our biological systems. It is also true of Black Swan events, which will seek out weak points in our social systems. Education is a social system with many weak points. It is based on rigid systems of time (contact hours) and space (“online courses are to be kept separate from ‘real’ courses”). The pandemic disrupted both time and space. As a consequence, it compromised many different systems in unexpected ways. The design of our technological toolsets reflected many of these systemic weaknesses.

This did not have to be the case. Digital technology has the capacity to make our systems less rigid. Online courses can be decoupled from time and space with little regard for logistics like room scheduling. As long as you have power and the internet, you are good to go.

One mistake that many institutions made last year was to move courses online without considering those two essential preconditions. For instance, instead of trying to reduce class sizes, the focus should have been to reduce the need to physically be in class. Instead of expending scarce resources trying to get students into classrooms, technological resources should have been distributed throughout our campuses to allow those students with connection or device issues to come in and use institutional resources such as computers and wi-fi.

Ultimately, the purpose of a classroom is community. We seem to have lost sight of that. Instead, we sought to replace the tool without considering how we could build communities in the absence of physical proximity. The system drove this train of thinking, not the tools. It’s no surprise we saw so many failures under those circumstances.

Our systems measure instruction through imperfect metrics such as “contact hours” that are based on old technological systems such as classrooms. The technology of the classroom drove the system in this direction but then the system assumed its own logic based on that technology. This rigidity created a structural weak point that was attacked by the pandemic. Trying to mimic a singular set of tools centered on the concept of the classroom online resulted in a great deal of dissatisfaction, as well as declines in outcomes, when it came to the quality of our educational product.

For my own classes, I made a conscious decision to ignore these systemic constraints and focus entirely on what my students needed to learn. I carefully analyzed all of the different tasks required to successfully complete my course, designed a set of tools matched to specific tasks, and went on teaching as normal with few compromises in my instructional approach. As a matter of fact, as I wrote in my book, Learn At Your Own Risk, there were many aspects of my instruction that were better than before remote instruction took hold.

My approach isn’t a perfect system (no system of individualized learning can be “perfect”). However, it does illustrate an antifragile approach to integrating the appropriate technological tools available to me. I let the needs of the learner drive my decisions, not the available technology. There were some things that were suboptimal. For instance, in-person contact, particularly for those still struggling to learn how to learn, is almost impossible to replace. Videoconferencing is not a panacea.

So how are we going to be ready for the next set of challenges that come down the road? Everything from climate change to demography are going to buffet our institutions. Climate change makes a repeat of COVID more likely as humans and viruses interact in new and unexpected ways as both struggle to adapt to changes in their ecosystems.

We are going to have to change how we think about technology to make education a much more antifragile system. That means we need to understand how our technologies work holistically with one another to shape our learning environments. But we must also consider, as happened last year, what happens when a particular set of tools is taken away from us by unexpected events. How quickly will our learning ecosystems adapt and heal under similar circumstances?

This is not just about preparing for disaster. We must also grasp the opportunities afforded to us by creating more flexible systems. Climate change is one example of a challenge that cannot be solved by any one discipline or specialty. Like Covid, science must be complemented with social science. If the last year has taught us anything, it’s that sociology and politics have often created illogical outcomes that have killed more people than would have been the case had we simply followed the science. It has taken both science and our social systems to develop and, more importantly, distribute vaccines to slow or stop the disease.

Our systems of learning need to facilitate the construction of bridges between disciplines. The challenges that we will likely face will require a range of interlocking skills and technologies to overcome. Creating an information ecosystem is critical to any large scale effort. Digital technology excels at information exchange. As a social scientist, there is little stopping me from bringing a physicist or biologist into my class. This is true even if the scientist in question happens to be thousands of miles away. The act of sharing research is simple as well.

However, none of this will have an impact if our systems don’t adapt as well. Silos are human constructions. Sometimes we build them into our digital solutions as well where they undermine the potential of the tools. We have to decide to use our tools in such a way as to make our systems antifragile. Our technology will not do this for us.

Blogs on the Hackathons can be found here:

• Out of the Information Thicket – The XR Connection

• Through the Digital Looking Glass: Reflections on Toolset Hackathon So Far

• Ozymandias – The Power of Creating Meaningful Artifacts

• The Power of the Moment: Building Communities of Thought

• Humans are More Complex Than Light: Iterating a Tool for Understanding Tools

We find ourselves in a thicket, trying to make sense of the vast amounts of information that the Digital Age has unlocked. Our tools seem somehow inadequate to the task as all they seem to do is speed up the flows while doing little to cut through the tangles. Extended Reality (XR) is about to unlock a new suite of tools with the potential to help us link humans and their ideas in entirely new ways.

In 1945, Vannevar Bush, who headed science programs for the United States during World War II, wrote an article for the Atlantic Monthly called “As We May Think.” His concern in the article was our ability to process and meaningfully link information in an age of large, distributed research efforts, such as the one he had just led to develop the atomic bomb. To address this, he imagined a device to connect, recall, and remix pieces of information, which he called the Memex. The key aspect of Bush’s design of the Memex was that it focused on the linkages between chunks of information, which he called “breadcrumbs,” instead of the information itself.

Bush realized that the flood of information was useless unless you could connect it in meaningful and replicable ways. Knowing it is raining is only useful if you connect it to the need to take an umbrella with you on your walk. Bush, and the pioneers that followed him, recognized the power of computing technology lay in its ability to connect humans and their ideas. The thinking behind the Memex influenced the evolution of computing technology from Doug Englebart’s Human-Computer Interaction to Tim Berners-Lee’s World Wide Web and beyond.

What separated Bush’s piece from most other early computing documents was that he only spoke of technology toward the end. He started with a problem. The challenge that he perceived was not a technology problem. It was challenging of linking and understanding human knowledge. Meaning lives in the linkages, not the information. Technology could facilitate human these linkages. It could not replace them.

Almost 80 years on, we have not emerged from Bush’s thicket of information overload. Instead, the problem he identified is magnified to the Nth degree by our computing and communication technologies. Navigating today’s information environments as a teacher is every bit as complex as the problems that Bush faced. We often struggle to see the connections ourselves, much less make them clear to our students. Our problem is that we’ve been thinking with blinders that focus our attention on the nodes and not the linkages.

Almost all computing technology since the 1970s has been constructed on the metaphor of paper. We think of web “pages” and “documents.” It logically follows that we build tools around the creation, storage, and presentation of artifacts based on those metaphors. We “see” information in this context and miss precisely the kinds of insights that Bush was struggling toward with his conception of the Memex.

Networks are patterns. They are patterns of linkages between people, but they also represent patterns of ideas. Bush recognized that our fundamental problem was one of effectively seeing these patterns of ideas. As teachers, we should recognize that problem. We seek to have our students see the world in a different light by showing them new paradigms. As researchers and learners, we struggle to imagine new patterns of knowledge.

The paper metaphor limits our ability to see patterns differently. We become creatures of habit and context. We see challenges as linear, with a clear beginning and end. Because prose appears fixed, we miss opportunities to bend time and space. Networks are also creatures of time. They bend and morph dynamically. We may miss something critical by assuming it is frozen. (As I’m implicitly doing with this very blog/column.)

Not long after Bush wrote his article, Claude Shannon provided the other key piece to breaking the Gordian Knot of information tied to the medium of paper. His “Mathematical Theory of Communication” shattered the idea of communication being tied to analog streams of information. After Shannon, information did not exist in the tunnel of text but in a fractal universe of bits. This insight flipped the switch on the Digital Age. It was now possible to see information not simply as a network of interconnected narratives but as a network of interconnected ideas on the cellular level.

While Shannon’s reality forms the bedrock of general-purpose computing, it has yet to penetrate the human imagination fully. Even under the best of circumstances we build our tools to facilitate the limits of our imaginations. If we continue to imagine based on the limits of paper, our toolmaking ecosystems will continue to build tools to support that vision of the world. We are still networking with the creative metaphor of the postbox.

XR breaks the paper metaphor because it finally treats information as distinct bits, allowing us to remix it. We can bring digital spaces into the real world by augmenting our vision. We can fully enter digital spaces and share networks of ideas in constructed spaces we can manipulate and turn in any way that we want. Virtual spaces open up 3D concept mapping and allow us to practice scenarios in ways that were impossible in a two-dimensional world defined by flat digital spaces. We will be able to walk through ideas. By going into these imaginary spaces, we may finally emerge out of our informational thickets.

Our tools not only shape what we do, they also shape what we think we can do. They bind our realities and our perceptions of what is possible. Everything from product marketing to comparisons with older tools to habits formed through their initial use shape our perceptions of the tools we use. The goal of Summer 2021 Teaching Toolset Hackathons was to push past these kinds of preconceptions and use the collective experience of the ShapingEDU group to introduce the world to creative ways to use digital tools.

This project demanded its own set of tools to be successful. At the urging of Laura Gehringer and Karina Branson, I implemented Miro as a concept mapping tool and brainstorming area for the live sessions. I selected this tool in order to creatively and actively engage the hackathon participants, both during and between live sessions. I used this tool to implement what I like to call “digital constructivism.” In this role, the tool has served well.

As I explored and tried to make sense of the data collected in the concept map, however, it became increasingly clear to me that we were looking at the problem backwards. The tools we were analyzing were driving the conversation at the expense of the tasks we intended them to perform. The concept map, however, reframed how I looked at the challenges we were working through. I perceived a way to flip the conversation so that the teaching goals would frame how we perceived the tools. In this way my concept mapping tool actually served a meta purpose: the tool itself reshaped how we should analyze tools. Ironically, using the concept map tool itself led me to see how we should ultimately frame the project.

When we embarked on the latest iteration of the Teaching Toolset Project, I intended for the group to create a catalog of tools that could achieve specific teaching and learning goals as defined by Diana Laurillard in her book Teaching as a Design Science. These were Practice, Acquisition, Discussion, Inquiry, Collaboration, and Production. To her list I added the challenge of engagement, which I defined as Curiosity. The problem that the Toolset Project sought to tackle, as originally conceived, was that we were uncritically using far too many digital tools. All too often, these tools failed to connect to the tasks that they were intended to perform.

The two hackathons that we have done so far have given the participants a list of tools grouped by proximity and time, allowed them to add to the list, and then asked them to connect these tools to the aforementioned teaching goals. It was my thinking that the critical gap in knowledge was a deep understanding of the tools themselves. Because we so often uncritically adopt tools, we miss opportunities to apply them to the creative practice of teaching and learning. As a result, we miss opportunities or become frustrated with the tools when they undermine our pedagogical goals.

I slowly realized that in the project’s design that I was making exactly the same mistake that I wanted the project itself to overcome: I was missing an opportunity to use the concept tool creatively to better understand how it was itself reshaping the project. The concept map that emerged from the first two excellent sessions on Synchronous and Asynchronous tools was a complex snarl of connections. After the last session, I set to untangling this flying spaghetti monster of linkages. I eventually discovered that the only way I could make sense out of it was to put it up to a mirror.

My initial thinking on the project was to create a guide grouped into the five tool modes Traditional (synchronous/proximate), Informal (asynchronous/proximate), Conversational (synchronous/distant), Presentational (asynchronous/distant), and Combinatorial (XR) but I have since realized that this was a trap. This approach led us down a path where we’re letting the tools drive the instructional pathway rather than collecting and developing tools to support specific teaching goals as laid out by Laurillard. This is exactly the opposite of what I intended this project to do but it’s not surprising that it took this turn given how most of us are used to thinking about the role of tools in our teaching strategies.

It seems to be a fundamental human trait to become fascinated with the tools instead of the tasks which we have designed them to perform. Or, as Diana Laurillard says, “tools and technologies, in their broadest sense, are important drivers of education, though their development is rarely driven by education.” (Laurillard, Diana. Teaching as a Design Science, p. 2, Taylor and Francis. Kindle Edition). I would actually take this a step further and say that tools often eclipse our ability to imagine the tasks they were meant to perform. We think of the car, not the drive. This reality has become a central conceptual challenge in the Teaching Toolset Project.

As technologists we have a particular bias in this direction because mastery of our tools has been what has always set us apart from our colleagues. Therefore, to channel Foucault, we control the language around technology and use it as an instrument of power. Many of us are individually aware of this reality, but the systems we exist in have reinforced this part of our identity. Most institutions only recognize our value because of our technological distinction.

The alternative view of our role, reshaping systems of learning, disrupts established structures too much for many institutions’ comfort. This conceptual constraint has always been a matter of intense frustration to me. I always look at tools as a means to an end and never an end unto themselves. I judge tools based on how far and how fast they allow me to create my ends, whether we are talking about creating a photograph or a lifelong learner.

In an era of digital tool glut, keeping our ends firmly in sight becomes even more important. When everyone seems to advertise the latest and greatest at the expense of intuitiveness and capturing human creativity, we end up with a smorgasbord of increasingly complex tools that obscure our goals instead of augmenting us to greater possibilities.

As I attempted to clean up the sandbox that was created during the first two hackathons, the tool reshaped how I envisioned the final product of our efforts. Instead of creating a manual divided into the five tool modes, it compelled me to see a new structure based on the 6+1 instructional tasks laid out by Laurillard. Like an origami, the tool showed me I could take the work of the participants and reverse it to create the opposite: seven sets of tasks with tools to support them. In this way, the tool itself fulfilled the purpose of the project and created a meta understanding of how we think about tools.

Like art, our use of tools is a mirror for human ideas and identity. Digital Age tools amplify this effect through their innate bias towards transparency, they lay bare implicit human assumptions. As masters of our tools, we can grasp these opportunities to see new patterns that emerge from examining our challenges in a different light. Tools should always augment us as human beings by allowing us to create, see, and experience in ways that are unexpected. They are the gateway through the digital looking glass. The world will never look the same again.

We tend to undervalue the value of our students’ creations and, as a result, so do they. Digital tech gives us unprecedented power to create. It also gives us power to preserve, duplicate and share artifacts of our learning journeys in ways that paper cannot. But with that bounty also comes challenges. We are flooded by the products of creation. When creation was scarce, it was valuable. When thousands of TikTok videos compete for the world’s attention, the danger lies in undervaluing the gems among them.

We are also flooded by a plethora of options when it comes to tools for creation. Which media and media creation tools make the most sense to preserve the work of learning. Conservatives among us will argue that the discipline of writing is essential for developing the necessary mental skills to be considered learned. I won’t argue with the importance of writing but it can now be shared easily. It doesn’t have to go from the student’s printer to the teacher’s filing cabinet. It can be scrutinized much more broadly through the mechanism of blogging with comments, to cite just one possibility.

The importance of taking that writing and those ideas and using them as a foundation for other kinds of media should not be underestimated in a world dominated by videos, web pages and slide decks. The friction associated with creating visual artifacts has declined markedly in recent years. This kind of creation also constitutes a vital skill.

Applying rigorous methods to more creative production is a key to separating student work from the masses of ephemera that have emerged in today’s media environment, but rigor must be coupled with meaning to achieve true value. Are we asking our students to produce throwaway objects or are we asking them to invest in creating something that is meaningful to them and not just as a box checked off of our syllabi? How we ask them to employ digital tools is at least as important as selecting the tools themselves. All of our tools tell stories. We need to make them meaningful ones.

Our lives consist of a series of artifacts. Some are committed to memory. Some are tangible objects. The most powerful involve the mating of the two. That special book or picture touches off memories of what is fleeting. This is the core of what it means to be human. We all have history and are part of our families, communities, and cultures. All of these produce artifacts. Some are more persistent than others but any one of them can acquire deep, personal meaning to us. This is what we remember and becomes part of us. Time is fleeting. Our artifacts are what root us to experience. Shelley’s sonnet “Ozymandias” can serve as a powerful metaphor for the tenuous connection between the permanent and fleeting.

I met a traveller from an antique land

Who said: “Two vast and trunkless legs of stone

Stand in the desert. Near them, on the sand,

Half sunk, a shattered visage lies, whose frown,

And wrinkled lip, and sneer of cold command,

Tell that its sculptor well those passions read

Which yet survive, stamped on these lifeless things,

The hand that mocked them and the heart that fed:

And on the pedestal these words appear:

“My name is Ozymandias, king of kings:

Look on my works, ye Mighty, and despair!’

Nothing beside remains. Round the decay

Of that colossal wreck, boundless and bare

The lone and level sands stretch far away.”

— Percy Shelley’s “Ozymandias”

Like all other memories, our learning experiences can be simultaneously fleeting and permanent. The most powerful experiences combine the two and our tools must be used to connect them in a meaningful way to have a lasting effect on the minds of our students. However, all too often we handicap our imaginations as we consider how to structure learning experiences and the tools needed to facilitate them.

We have at our fingertips today an unprecedented set of tools for creation. Our challenge is unlike that of Shelley and his contemporaries. Pen and paper pretty much represented his range of options. Within decades, we added photography and then film to create, capture, and share our memories. In the last 40 years we have taken all of these media and given them to the masses. In the last 20 we have made it possible to share them widely.

We are faced with the challenges of opportunity. Even while it has opened the doors of creation to many, the democratization of creation has cheapened its value as a container of memory. What used to be a precious scrapbook of family memories is now a vast database of photos and videos of precious moments. The challenges now are ones of sorting and tool selection. For a precious few of those artifacts, the connection to memory remains as powerful. We assign meaning. It is not a given.

Our students must create objects to which they are prepared to assign meaning. It is this power of meaningful memory that we need to tap into as teachers. The problem is that all too often we cheapen the memories of learning by letting our tools limit the universe of possibilities open to us to create those memories. Our students learn that school is about the creation of nothing more than cheap, ephemeral artifacts and treat the experience accordingly.

Our challenge is to use our tools for creation and sharing to build powerful networks of meaning and memory from their learning journeys. We cannot do that if we treat their artifacts as disposable meaning, relevant only within the context of an assignment or assessment. To do this we must turn artifacts into experience.

This is not in any way to denigrate the experience of writing as Shelley experienced it. Creation is as much a product of constraint as it is of opportunity. Using our tools to reimagine those constraints is part of adding importance to our memories. Instead of the traditional paper, have your students create a photo essay. Teach them how to adapt their ideas from one medium to another. Have them work publicly and share with their peers and the world beyond the classroom. These are all ways that we can turn the confusing array of digital tools to create more precious artifacts of their work. It is networks of ideas mated with powerful tools that allow us to create scarcity and meaning out of excess and meaninglessness.

Meaning comes from scarcity. We must actively create scarcity as part of our quest for deep learning. “More of the same” will generate nothing more than the same from our students.

The purpose of asynchronous tools is to create statues that stand the test of time, maybe not as long as Ozymandias, but at least past the course or college experience. How can we use these tools to string together the times we are together with our students and complement their power to achieve meaning and not just the routine of assembly line learning? How can we use them to awaken the creative spirit within them and motivate them to do more than the minimum necessary to “get through” the class? These are all questions that we will explore.

Time is our only truly non-fungible asset. Deficits of money can be made up but deficits of time are impossible to recover. As teachers, we struggle with this every class. We understand that time spent with students is absolutely precious. It can never be made up once the clock at the end of a term runs out. It is difficult recoup even within the context of a single class session. Time is a truly scarce resource.

Scarcity doesn’t always breed perceived value, however. Students often struggle to find motivation. They sit through classes out of a sense of obligation or a belief that showing their faces will increase their grade. Their perception of time in an instructional session can often stretch toward the infinite (“When is this going to be over?”).

The reality is that we waste a lot of time in any class. The density of knowledge that we can ask our students to absorb within a given live session is even more constrained than that marked out by the clock hands. Lessons in a single class session can usually be counted on one hand, if that. One of my grad school professors (the only one who bothered to teach me anything about teaching) told me that you can’t expect students to absorb more than 3 points in a given lecture. Your challenge as a teacher is making sure that they absorb the right three points. I have found this to be a good yardstick of what I can realistically accomplish within a single session but even that is often an optimistic measure.

The pandemic and remote teaching showed many of us the limits of synchronous teaching. Students weren’t even engaging to the same level as they had during in-person sessions (and that was a low bar). The fact is that much of a given hour of synchronous instruction is repetitious. If it’s repetitious it doesn’t need to be synchronous. The first 5-10 minutes of my classes are usually spent checking roll, making announcements, and recapping highlights from the last session.

None of those things need to take up precious synchronous time and can be shifted into asynchronous tools. Taking roll can be automated by having students put their names in a saved chat or with numerous other tools. It is better to send announcements through an online course shell. Recapping lectures is unnecessary if you record a Zoom session and post it for later review.

Expository talking, aka lecturing, also took a hit during remote teaching. Many of us practice some form of the Socratic method. We quickly discovered that question-and-response really doesn’t work well with a bunch of anonymous black boxes in a Zoom session. Like announcements and recaps, moreover, the same level of interaction can be achieved through pre-recording lecture highlights and pushing that off into asynchronous time.

Using various methods, therefore, I liberated close to 80% of my synchronous time from the time vault during remote instruction. This drove me to think hard about what to do with the remaining time. Attention spans online are even shorter than they are in person. There was also an expectation that, since the session was being recorded, the student could go back and review the tape if there was something he or she missed.

The key to making synchronous time as productive as possible was doing something instead of just talking about it. I had always nibbled around the edges of this in my in-person classes but I never really trusted student-driven work to actually drive the class. I wanted to control the narrative in the classroom to make sure we “covered the material.” Giving control of the pace of the class to the students was a scary prospect and, after all, wasn’t I, as the “expert in the room,” abdicating my responsibility?

Faced with obvious indifference using online tools, it was clear that I needed to pivot decisively toward creating moments centered on the students, not the material. I would have to trust that the material would take care of itself. In in-person settings simulations often were a good way of creating immediacy and active learning. However, this was challenging in an online setting where interpersonal interactions are often more stilted. Instead, I asked myself where my students needed the most help. I started working back from my assessments and determined that analysis and argument were conspicuously absent from most of their work. The solution (HT Ruben Puentedura) was to introduce the Toulmin Argumentative Method directly into my live sessions.

This work consumed many class sessions as we dissected each students’ argument. My knowledge of the subject plus techniques of argumentation and research were brought to bear as I walked them through the steps of constructing an argument. The students were then tasked with finding sources that supported their arguments. In this way I sought to develop a community centered around intellectual inquiry. The tools used were very simple. I used Zoom and shared my screen with a concept-mapping tool. After the sessions I cleaned up the diagrams a bit and shared them on Canvas. This would have been more difficult to do using traditional, in-class tools. But it drew power from the collaborative synchronicity of the work online.

The central goal of this activity was to stimulate conversations and group practice to collectively unlock the riddle of their research projects. As Diana Laurillard points out, conversations are central to any learning experience. We can have most kinds of conversations asynchronously but they are reshaped, some might say limited, by their lack of immediacy. The key to generating effective conversations is creating opportunities for the unexpected and these are far easier to achieve synchronously. This is a more important distinction than whether that interaction happens in close proximity or at a distance.

We should not assume that returning to “traditional” classrooms will automatically return us to where we want to be, forgetting the lessons learned from remote instruction. As we discussed in a previous blog, most “traditional” classrooms did not take full advantage of the potential for the student-teacher relationship. Conversation was often one way. Over the last decades, learning space design has worked hard to overcome these initial biases. However, even the most innovative classroom will lose much of the benefit of immediacy if the teacher uses it to teach in a “traditional” way.

Digital Age tools can speed the flow of ideas but they have to be applied strategically in order to achieve the “decisive moment” where deep learning occurs. Information alone is not sufficient to stimulate ideas. Those ideas must resonate within the community of learning. Ideas are central to our humanity. Therefore, if we want to share our humanity, we must also share our ideas. If we want to teach in a learner-centric world, we must find ways to connect our humanity. This is where digital tools can help us. They give us tremendous power to amplify how we connect humans to each other. This reality forms the core of all synchronous learning experiences.

Good teachers shape realities and do so with intentionality. Synchronous experiences are the most visceral realities that students can experience in their learning process. These are the spaces where we can “perform” as teachers. However, they only work if they are also spaces where our students can perform as well. Teaching is all about achieving that “a-ha” moment in our students.