Perspective: Historic Innovations in Educational Technology
The Concord Consortium has just celebrated its thirtieth anniversary. As I flip through the first issue of our @ Concord newsletter, I feel both nostalgic and proud. That original issue paints a picture of an idealistic and scrappy era. Across its articles, I see innovators grappling with technical hurdles—that perennial hallmark of cutting-edge work—as they struggle to ensure broad access to technology-based resources in an era when computers were still hard to come by. I also see remarkable examples of ingenious ideas becoming reality, in the form of theories that would come to enter the common vernacular and early-stage software concepts that would ultimately transform into entire industries. From online learning to sensors and simulations, the Concord Consortium has been pioneering educational innovations from its inception.
The historical artifacts of our founding provide the closest thing we can get to a crystal ball. If we take a similar snapshot of technology today, what might it portend for the teaching and learning landscape of tomorrow? Let’s take a look back as we try to envision the future.
An early newsletter article* provides a detailed account of the circuitous technology path involved in learning how to support teacher and student interactions in online courses. A series of vivid descriptions of software packages tried and discarded make evident the vital role of a custom, integrated software environment in supporting asynchronous online learning. The article outlines a set of discoveries: the need for threaded discussions, the importance of sharing resources that include images, and the ability for participants with little technical background to easily create new discussions. In hindsight, it is clear that those experiments to make virtual education possible across time and space marked some of the earliest concepts of a full-featured K-12 learning management system.
Another article outlines the emergence of a broadly accessible computer for classroom use. Descriptions of the Apple eMate frame it as ideal for the K-12 learning setting and “far more valuable educationally” than the more powerful—and more expensive—office computers of the time. Affordability and usability were the criteria used to nominate that early portable device, calling to mind the introduction and meteoric rise of Chromebooks as they later came to dominate the K-12 educational market.
Other prophetic examples abound. One article makes the case for “collaborative creation of graphics,” predicting that “maps [of environmental study sites] with overlays showing…features and collection sites” could change the way students think about science. Students were able to interpret and analyze data from far-off places. Other articles outline how “inexpensive, portable computers…could transform education,” predicting that “life-long learning…can be made universally available.”
Indeed, these visions of online learning from three decades ago have become reality. Today’s ubiquitous devices and networks enable access in any setting imaginable. And YouTube’s endless catalog of tutorials on practically every aspect of the human experience supports all manner of informal learning as well. It’s now possible to learn about anything, anywhere and anytime. It’s also clear that thanks to the firm establishment of virtual learning across the nation, schools were able to go remote during the pandemic. While we are still unpacking the effects of that grand experiment, technology was central in connecting people across an incredible diversity of settings.
Looking forward
So what does this historical viewpoint offer us today? For one, it reminds us that our work in technology innovation leads to meaningful future developments. While some innovations will surely prove to be first of their kind, others will provide stepping stones or incremental improvements. But which elements of today’s initiatives presage new domains or essential future affordances?
Our models enable students to investigate these systems via inquiry-based experiences, allowing them to change parameters, predict outcomes, and reason about events and processes.
What seemingly small innovations are waiting to evolve into whole new industries ten or twenty years from now? While the only thing certain about all predictions is that some will be wrong, speculation is instructive, nonetheless.
It is already clear that our work promoting quality Earth science learning is groundbreaking. Over the past decade, researchers at the Concord Consortium have developed a suite of dynamic models for understanding geology and Earth systems. Because of the long-term nature of geological time, Earth science largely involves the study of static situations and disconnected ideas. The Earth, however, is a highly dynamic, connected system, and its rocks exist in different forms for key reasons—reasons that connect to the Earth’s system-focused nature. Our models enable students to investigate these systems via inquiry-based experiences, allowing them to change parameters, predict outcomes, and reason about events and processes.
These authentic, complex Earth and environmental system models empower students to be “hands on,” exposing them to simulation as a tool that can open doors for investigating physical systems and drawing important conclusions. The same goes, of course, for other subjects—models and simulations play a key role
in examining science both inside and outside K-12 schooling.
In other areas of STEM education, we are integrating software programming and hardware devices to enable easy programming and deployment of microprocessors and Internet of Things-like devices. This infrastructure may well evolve into an essential paradigm for guiding and launching hardware. Indeed, as robotics emerges in ways difficult to predict, this future seems more plausible every day.
We also are enabling students to envision mathematical modeling in a flexible environment that links elements from text to drawings and equations. While mathematical modeling has long been important, it has seen a resurgence in recent years within mathematics education circles and even at the level of statewide programs and standards. Combining this increased awareness with the rising relevance of modeling in the context of machine learning and AI-based approaches, it’s not difficult to imagine this work as a template for indispensable learning tools in future classrooms.
Finally, the rapidly developing world of AI is sure to create persistent traces for future generations of educational technology. At the Concord Consortium we are incorporating AI technology into our collaborative learning platforms to help teachers quickly and easily interpret, categorize, and react to students’ sensemaking. We are also working to help students themselves learn about the technologies underlying AI systems, preparing them to understand the tools that are rapidly shaping their future so they can approach these tools from an informed perspective. There is little doubt that this critical work is destined to evolve in essential ways for teachers and students alike.
These are only a few examples of how the present can become the future. Ultimately, we hope all our work will prove consequential in both its direct effects as well as the distant consequences our projects have for innovations and inspiration for equitable, large-scale improvements in STEM teaching and learning through technology. We remain as hopeful about this ambitious goal as we were back in that first issue of @Concord. Were those early glimmers of technology to succeed, our inaugural newsletter predicted, “far more people can share their knowledge with many more interested learners.” That goal is as relevant today as it was then, and we aim to continue this important work for many
more decades.
* Read our first newsletter at https://concord.org/newsletter/1997-spring/
Chad Dorsey (cdorsey@concord.org) is President and CEO of the Concord Consortium.