Let’s take a step back and consider how well we are using learning technology in contrast with what is possible given advances over the last decade. Ideologies influence design, then design constrains future options. We don’t have to look very far to see examples of this simple rule: classrooms, design of organizational work activities, politics, and the operation of financial markets.
What we create to survive during one era serves as neurosis for another. In education – particularly in technology enhanced education – a similar trailing of ideologies from another era is observed.
For example, education consultants and speakers commonly declare “if a student from 100 years ago came to our classrooms, she would feel right at home”. Obviously, this is an absurd statement (even if we overlook the challenges of time travel). Education has undergone enormous changes to curriculum, instructional methods, and technologies used. Classrooms today have a more diverse student population, greater attention is paid to the needs of students with special needs, and (for good or bad) students are instructed in different ways of knowing and understanding – in contrast to the singular world views of only 50 years ago. While pundits are wrong in criticizing schools as unchanged in a century, they overlook the more obvious challenge: learning itself is unchanged. Content, student, teacher, interaction (maybe), and assessment; in various combinations, continues to form education’s core.
What are the ideologies reflected in this approach to learning? And do we still need them?
Without going through a painful attempt to deconstruct learning and its systemic origins, I think it’s safe to state the following as the key elements of a weltanschauung that define formal education:
1. We know what students need to know in advance of their arrival (the learning needed can be defined)
2. Through manipulation and sequencing of content and interactions, we can get students to learn what we’ve already decided they need to learn (control)
3. Students at a similar age/grade/program level have a similar knowledge base. Even if we don’t make this explicit, how we design and deliver learning in K-12, university, and corporate settings is evidence that we hold this view. (similarity)
4. Structure, goals, outcomes, and assessment are all good. For that matter, coherence is good. Learning needs a target. (coherence and structure)
Other ideologies exist, but these are particularly influential in education, impacting design to accreditation.
What is wrong with these views?
To return to the opening statement, these views reflect an ideology that is growing in obsolescence in relation to the world outside of classrooms and training labs. When does a student know the structure of a problem in advance of solving it when she’s trying to create a YouTube video? When do a group of children know their learning outcomes when they choose to create and play a game? When does a salesperson know in advance that their is a correct way to engage a foreign client and thereby when the business of their organization? Learning, occurring under contrived conditions in classrooms, bears only a faint resemblance to real world problems and challenges. This is hardly news. Educators have known this for decades. Case studies and problem-based learning were developed partly as a response to the fabricated classroom environment.
Pedagogical innovations, as expressed in constructivism (in its many, many shades), do not provide the full force required to pull away from irrelevant ideologies that seek to warp learning to reflect needs of a different age. This failure to overcome ideologies is due to an inability, to date, of educators to rethink the learning model. Reformers have largely worked within, rather than on, the system of education. Working within the system has resulted in status-quo preservation, even when reformists felt they were being radical. Illich failed to account for how educational institutions are integrated into society. Freire spoke with a humanity and hope that was largely overlooked by a comfortable developed world incapable of seeing the structure and impact of its system. To create and nurture change, a message must not only be true for an era, but it must also resonate with the needs, passions, interests, realities, and hopes of the audience to whom the message is directed. As a result, pedagogy has not influenced learning broadly. It has lifted the spirits and motivations of small camps of educators for brief periods. But it has not altered learning in a way that transforms the system of education.
The externalized generation…
The last decade has provided individuals with the tools to continually externalize their thoughts and ideas. History is generally revealed to us through significant artifacts. We have books (artifact) that capture certain time periods. But we don’t have the raw daily conversation. We have a sanitized view of history. Future generations will likely have access to far more historical information than we currently have. Through Youtube, Twitter, Facebook, SecondLife, podcasts, Flickr, and blogs our daily conversations can be captured. Conversations that occur on Facebook or Twitter do not vaporize the way conversations around a boardroom table do. As both Vygotsky and Wittgenstein argued, language gives birth to thoughts. Twitter gives birth to identity, to being. Technology has enabled our generation to externalize – through video, pictures, audio, text, and simulation – our ideas. Once externalized, a trail of identity and conceptual development is left for future consideration and analysis. (I wrote more on the role of externalization and technology in this paper from 2006 (.doc))
Finding a cure for stale ideologies
Instead of working within the system of teaching and learning, let’s turn our attention to changing the system itself by suggesting responses to the ideologies discussed previously:
1. The learning needed can be defined
2. Control is needed to achieve required learning
3. Students at similar stages need similar learning
4. Coherence and structure needed for learning
French philosophers (always blame the French…but the Germans contributed their share as well) have lead us to relativistic views that could be used as a method for challenging these four ideologies. This would provide hours of fun, but with little practical outcome. The development of chaos and complexity theory offer another approach, but models in the physical sciences are often only useful as metaphors in the social sciences.
Education has had enough theorizing (yes, I get the irony). Let’s throw in a dash of pragmatics and see where we end up. In fact, let’s start at the smallest element in the learning process: a connection. Instead of trying to squeeze curriculum into a myriad of epistemological views and adding a splash of psychology and sociology, I suggest we zero in on connections. Biologically, learning is as simple as the firing of neurons. At a conceptual level, learning involves the connecting/weighting/strengthening of links between concepts and ideas. At a social level, learning involves interacting with other individuals (and increasingly, technological agents). How are connections formed? What does a particular constellation of connections represent? How important is technology in enabling connections? What, if anything, is transferred during an interaction between two, three, or more learners? What would learning look like if we developed it from the world view of connections?
Introducing [something that I haven't named yet]
Here’s the basic concept: technological advances in how content is created and how individuals interact are at a sufficient stage to serve as a replacement to traditional classrooms. Enter Technologically Externalized Knowledge and Learning (TEKL). Or Connector. Or Learnometer. Or learnalyzer. Or Learnabler. Or future learning approach. I have no idea what to call it without evoking the cheesy Batman “pow” images and shark repellant from the 70’s. For know, I’ll stick with the acronym TEKL.
What is TEKL? TEKL is a physical, wearable device that captures our physical and virtual interactions and assist us in recognizing and forming knowledge connections based on our past interactions, our social network, and our current work or personal interest needs. The image below expresses the elements of TEKL and provides additional detail on the function of various agents.:
Components of TEKL:
Profile: Our profile is essentially our identity online. We can contribute to the formation of our identity by completing profile pages on Facebook, our organizational social network or directory (i.e. IBM’s Blue Pages), or Google Profile. However, our identity and profile will be shaped by what others say about us online and by the indirect messaging evident in the types of people we connect with (i.e. if 90% of your friends are of a certain political or religious view, the probability of your politics/religion being similar is high). The portion of our profile that we control (i.e. what we say about ourselves) could be used for TEKL to suggest social (geographic) connections at conferences or other venues. Google Latitude – and numerous other services that map profile/social network to geographical location – is an example of what an early prototype of this service might look like. The intent of the profile feature of TEKL is simply to make available certain aspects of ourselves for connecting with other people and with information. Over time, our profile is augmented with additional information extracted from our patterns of interaction. Eventually, the trails left in our interactions and in our word/language use will enable TEKL to know us well enough to provide general guidance and direction (counseling?)
Patterning Agent: The patterning agent provides metrics, feedback, and visualization. How many words have I spoken today? How did I develop conceptually today (concepts are address by a separate agent – more on that below)? If I’m seeking accreditation in a particular field, how much progress was made? How do the ideas I addressed today match against ideas I’ve expressed in the past (my profile). Essentially, this agent visualizes our social networks and our interactions with others, providing insight into our knowledge and learning habits.
Discovery Agent: The discovery agent actively solicits additional information based on our current context and our social network. For example, if I sent an email to a colleague three weeks ago addressing, say, the headaches I have with my investment banker, the discovery agent would continually “seek” opportunities to connect me with individuals who have related patterns of communication (say a colleague in my social network who has a great investment banker). My communication and information patterns are constantly matched with those in my social network. Connections are recommended that I may not have noticed on my own. The discovery agent also serves as “constant Google” role, providing new and updated information based on previous emails, texts, tweets, phones calls, web searches, courses, and conversations. This agent can provide a valuable role when activated at an organizational level – i.e. “George, a colleague in UK is displaying similar patterns of conversations, would you like to connect with her?”. Privacy, obviously, is a huge concern here. Does the organization own our words and interactions? (by offering suggestions for interactions, our work habits would be made explicit, analyzed, and then matched).
Matching Agent: The matching agent analyzes an individual’s conceptual development. This requires that all of our interactions and conversations are first recorded. If a field has been well defined, a matching agent can make recommendations to information and social connections that would provide value for our learning. If I decide I want to be a nurse or an accountant, I can load the attributes of this work-type into TEKL and it would provide continual information and social recommendations to help me “become” a nurse or accountant.
Monitoring Agent: The monitoring agent works closely with the matching agent. It essentially serves as an “overlay” agent, determining progress toward our goals. With the profile of a particular career fully loaded, I could see regular indications of progress toward the requirements accrediting bodies allocate to that field. And, when I’m done being an accountant, and decide I want to be a carpenter, this new work-type can be installed into TEKL and my existing competencies and conceptual understandings can be measured against my new career. Instead of duplicating my learning as I change careers, I’m only required to develop those skills and conceptual elements that I’m still missing.
Mentor/Guide: The mentor/guide aspect of TEKL is the human/social function. When we decide to explore a new field, we may wish to have the value of a human guide, sharing personal stories and recommending approaches to our own learning and knowledge growth. E-harmony and other online dating services have altered how people date and find partners. TEKL offers a similar learner/teacher connecting service. Our profile is matched with educators/instructors, suggesting ideal relationships for learning.
As we go through the day, TEKL merrily records, matches, monitors, and recommends our learning and knowledge needs. When we go to bed, TEKL process our conversations (verbal – after all, everything is recorded), our email, our work habits, and our information seeking activities. Then, when we wake up, we receive a learning and knowledge status report, providing us with intelligent and relevant information as well as recommendations for greater personal efficiency and critical sources of information. The is a daily personal knowledge and learning GPS that provides direction and progress.
How does this move the field of learning forward?
How does this overcome the ideologies that education has to date been unable to shed through pedagogical reform?
First, given nature of today’s complex problems – we have hit the limits of cognition in the head. We need to rely on the network as a cognitive agent. Solving the biggest problems of humanity will require a pedagogy built on networks and the distributed knowledge amplification opportunities they allow.
Second, it pushes learning into the background. Rather than saying “I am learning now” – a nonsensical statement as we are constantly learning – it makes what we’ve learned explicit only after learning, rather than before (i.e. “learning outcomes”). Where the learning is undesirable (a misconception, for example), feedback is provided through both social networks and through conceptual patterns analysis.
Third, it accounts for the complexity of learning by permitting learning needs to be formed and reformed based on current needs and context. The learner is, in the much abused term, “in control”. Learning as foraging.
Fourth, instead of squeezing all students into a curricular path that ignores individual distinctions, students are continually provided personalized (ugh) content and connection suggestions.
Fifth, the coherence and structure of learning is not solid and fixed as in a course. Instead, coherence is continually shaped and formed as new connections are suggested, existing conceptual networks are challenged (by social networks and patterning software). Structure is a by product of learning processes, used to evaluate quality of learning in relation to some other entity (say, the competence and knowledge to be a nurse or a business person or a plumber). Where no ulterior motives – such as accreditation – are sought, evaluation is not a significant concern.
The real issue
The real issue is not related to technology. It’s the conceptual jump that’s most difficult. For example, the functionality expressed in TEKL exists in various tools already. The key value produced by TEKL is to connect the pieces in a meaningful manner that allows for personalization, utilization of social networks, exploration of patterns, and layering of “knowledge and skills” over an existing profile to offer new learning opportunities.
Different areas of research and entertainment – such as language analysis, data visualization, social network analysis, matching services on Amazon, friend suggestions on LinkedIn – have made significant inroads analyzing and matching information based on context and need. TEKL is, in a sense, a connecting agent drawing together proved functionally various fields and directing this connected structure in the service of learning and knowledge growth.