Teaching, an emergent property of learning environments

Teaching, an emergent property of learning environments - IST 2000

I first presented this view of teaching in the context of the design of learning environment in 1999 on the occasion of a EU-US conference in Stuttgart (see the notes here and there). This new version was prepared for a talk at IST 2000 held in Nice; it includes outlines of the project Baghera which was emerging:

The project Baghera, a leading project of the Leibniz Laboratory, has the objective of shaping and experimenting radically new perspectives on the design of eLearning environments. First, by eLearning environment we mean not only the technology but the whole complex constituted by the machinery, its users and its environment. Second, it is the project basic belief that the complexity of human learning can be faced only if the design of eLearning environments takes the collaboration between artificial and human agents as a foundational principle. This requires a strong pluridisciplinary approach at every stage of the design and of the implementation.

A platform like the one we look for, is structured by several different types of interaction and cooperation: between teachers and artificial agents, between human teachers with the mediation of the technology, but also between learners mediated by the technology. Indeed we must add the interactions between learners and teachers either in an asynchronous mode or in telepresence, and between learners and the learning environment. Learning does not occur because of one specific type of interaction, but because of the availability of all of them. One type of interaction, or one type of agent, being selected depending of the needs of the learner at the time when the interaction is looked for, as well as of the specific characteristics of the knowledge at stake.

Then, the learning environment, constituted by content specific resources and conception specific resources (taking into account the variety of learners possible conceptualisations) gets its teaching power not from the property of one of its components, but the emergent property of the interactions of all the agents involved—either artificial or human, learners or teachers. In this approach the crucial issue is not that of the genericity of the technological environment (which is always obtain to the detriment of its cognitive and epistemological specificity), but of its adaptability and openess to change.

May be this is just rediscovering that education has never been the result of the action of one isolated tutor, or single intitution, but of the Society at large...

By the way, why “Baghera”? Because at the core of the system we intend to develop a society of non-human agents whose interactions will aim at the education of a human learner. But unlike the famous story, this time some human agents will take part in the adventure…

Some thoughts about Learning aware environments

Reference: Nicolas Balacheff, Learning aware environments, eAgenda 2006 European Forum, Castelldefels, Spain, 24 October 2006
 

Could we “introduce learning in every human activity”? From a non-English speaking perspective this question may sound strangely. Isn’t it the case that learning is present everywhere and at every moment in our life?  This is a matter of survival. Learning is a competence shared by all living organisms. Learning is life-long; it starts with our first breath and continues until the very last one. However there is something specific to human-beings, which is that not only do they learn to survive in their biosphere, but also they have to learn to survive in a noosphere that humanity is continuously building, renewing, transforming. The noosphere is made tangible by human artefacts, but essentially by language. Learning in the noosphere is so complex that specific strategies have been developed to support it, namely teaching (or education, instruction, training, coaching, etc.).

At this point it is interesting to come back to the origin of “learning” and “teaching” in the English language. Both words have a German origin, tracing back respectively to “læran” and “tæcan” in Old English. While the latter meant “to show” or “to persuade”, the former was preferred to mean “to teach” or “to guide”. Then, could we suggest that the English word learning has a teaching connotation, and that as a result the meaning of  the question is: “can we introduce læran in every human activity?”, what introduces the idea of environments with “teaching” capabilities.
 

Designing environments likely to stimulate and support learning outside formal education and training —or situations mimicking these—was in most cases out of reach until the emergence of the digital technology which bridges the biosphere, where our bodies and activities are developing, and the noosphere where minds and intellectual constructs are developing. While language and the related symbolic technology (writing and reading) were the privileged tools to support learning, digital technologies go beyond by producing highly interactive simulations and virtual worlds. But more significant is the development of augmented reality, the systematic embedding of sensors and system on ship in all artefacts which open the possibility of a “merge” of both spheres. Here is the challenge of ambient computing.

Just as the rest of our environment, modern digital technologies cannot support learning if they have not been designed on purpose by incorporating teaching (coaching, instructing, scaffolding, or else) features. This is the challenge of designing, implementing and understanding learning aware environments. They are environments which have the capacity to recognize and capture relevant events from observing the human activity, the ability to understand the learning needs and then to provide the adequate feedback in whatever form. This is a scientific and technological challenge for ambient computing and research on cognitive systems. This is also a political challenge because the full development of learning aware environment will not be possible without addressing ethical (protecting the individuals and the communities) and economical problems (accepting that knowing is a universal right).

#ocTEL MOOC (week 3 A33) Learning forward, designing backward

The third activity for this week 3 on Designing active learning is to design an activity and to review a learning activity. I didn't design one specifically for this MOOC, but I am happy to share one which I designed for a Doctoral school a few years ago, it was about the design of learning game, starting by inviting students to play a game...

About learning games and the design of learning spaces

The idea is simple: invite students to play a game first alone against the teacher who manages to sometimes loose, sometime win. This the time to acquire the rules. Then the students play against each other, first alone, then in team with a spokesperson who will play the strategy of the team. There are two levels of debriefing, the first one specific to the game as such, the second to understand the structure and the function of the game as a learning situation. Eventually, students are invited to analyse a simulation game in epidemiology. The sequence closes with a more theoretical analysis of the role of games in learning.

The lesson learned from this exercise is that while learning goes forward from action to articulated knowledge, the design of a learning situation must go backward from the targeted learning outcome back to the optimal situation to engage learner in the process. This situation could be a game but not necessarily, it must essentially be a situation which allows learners to mobilise what they know, whatever it is, in order to make the first step towards the target. The sequence of situation is a journey allowing the construction of the required mental constructs, then language, then means to evaluate and give ground to the piece of knowledge which has emerged.  This is a quick summary, but the essential is there.

It is with this in mind that I reviewed two activities proposed by (@James Kerr), History of Educational Technology-A Collaborative Timeline Project, and (@ElizabethECharl), Webquest – a hunting we will go. In both cases, the difficulty is to figure out precisely what will be the learning outcome and how the situations are appropriate for this objective. Kerr activity is interesting as such, it could stimulate conversations on the history of educational technology and beyond on the role of technology in education. It is an open situation which could give ground to several different learning objective. Elizabeth activity is more focussed on information search on the net. It is a starter, and actually presented as such, which fruitfulness will depend on the follow up either by new situations or by the teacher -- here a librarian. As a learner, I am now in standby in both cases...

The iPhone shrinked to a point of the kinetic space

If creativity means the capacity to imagine a use or an object away from its natural niche, then this is an excellent creative example. There, the iPhone is no longer a phone nor a digital assistant, it is a multiple-sensors device and the tangible representation of a point in the kinetic space. The innovative proposition of Joël Chevrier and his team, have applications for the learning in physics and mechanic, but also one may imagine that it could become a  representation of oneself body in the space and be used with young learners. This innovative pedagogical proposition exploits just a few of the potential of the iPhone: the accelerometer and the magnetometer. Just a few, but already enough to foster creative learning with mobile technologies.

Teaching counts

  Retrieved from the TEL opinion blog, December the 22th, 2005

The reasons why the learner, either a child or an adult, needs "teaching inputs" are very often hidden as a corollary of the emphasis on—and possibly the misunderstanding of—the constructivist principles of design of learning environments. I would like to suggest here that these needs are especially important in the case of modern environments which are largely distributed and provide a potential access to a huge amount of knowledge and information. The following questions illustrate some of the issues that learners may have to face when left on their own in the wild web of digital resources: "How to look for something you don't know? ", "How to know that what you have found is what you were looking for? ", "How to know that you have learned?". Here are some of the issues that a teaching assistant should help to address. Another crucial question is: "How will others know that you know?"

It is not enough that learners have solved problems for them to understand that they have learned. Creative problem-solving which is at the core of the constructivist approach is so rich in new intellectual constructs that it is even a problem for the learner to realise what is worth remembering. Here again is a specific task for a teaching assistant. There is no general teaching model which could be implemented to equip a learning environment with the corresponding functionalities.

The nature of complex knowledge (as opposed to basic skills) is another reason to seriously refocus the design of learning environments on teaching issues. One of the main characteristics of such knowledge is, first that to master it requires to master several different pieces of knowledge organised in the form of a system, and second that its use depends on methods which are not mere algorithms. Such knowledge cannot be constructed spontaneously even when learners are provided with an adequate problem-situation, and actually in some cases such situations are even still unknown (e.g. linear algebra). As a result, complex knowledge requires specific learning environments and content specific teaching strategies. The complexity of such knowledge also comes from the fact that the corresponding learners' conceptions (i.e. learners' cognitive constructs), can be very different the one from the other and rather complex to understand and to model. The current research on students' understanding of the concept of "function" in mathematics or of the concept of "energy" in physics witnesses this complexity. The development of technological tools aiming at supporting the use of these knowledge (formal computation, simulation, etc.) even increases the difficulty by modifying within a kind of systemic loop the nature of the users' conceptions.

We cannot expect one single universal agent to be able to handle the complexity of supporting the learning process in the case of complex knowledge. On the contrary, there is a need for specialised agents, either artificial or human, able to cooperate and to coordinate their actions in order to provide the best support to the learner—indeed, one could remark at this point that the situation might not be so different for the so called "basic skills"…

My claim is that: the educating function of a system is an emerging property of the interactions organised between its components, and not a functionality of one of its parts.

When the space is the interface

  Retrieved from the TEL opinion blog, April the 12th, 2008
 

Making accessible phenomena by means of simulations is one of the added values of computer-based learning environments. To make it simple, let's say that the key feature of simulations is to have a good mathematical model plugged on an efficient visualisation of the  targeted phenomena. However, such simulations are processed within the limited space of the screen of the computer over a short period of time. The development of virtual reality and the so-called full scale simulations allow the access to spaces beyond the limits of the screen. However, one is still immerged in an artificial world with time and persistence  constraints (notably, this is not the case in MMOs). The idea of embedded phenomena coined by Tom Moher opens smart ways to overcome several of these limitations.  An embedded phenomenon  is the emergent property of  the behaviours of a set of "distributed media located around the classroom representing 'portals' into [the] phenomenon depicting local state information corresponding to [its mapping onto the physical space of the classroom]." The space of the class becomes the interface with the model which has been implemented; but it is more than that since a simulation can run  "continuously over weeks and months, creating information channels that are temporally and physically interleaved with, but asynchronous with respect to, the regular flow of instruction."  This approach opens new significant possibilities for the simulation of phenomena where space and time count. Migration of  bugs, movement of the planets or earthquake find with embedded phenomena a much more relevant framework to challenge learner modelling, requiring an effective conceptualisation of space and time.   

But  the essential contribution may be not  at the level of the acquisition of the concepts themselves but at the level of the acquisition of the methodology and the organisation of the scientific work. Students have to organise the space and the time to collect data, then gather and analyse what they have obtained individually to build a collective knowledge. Given the role of time, the experiment cannot be replicated at will. Close to what happen with on the field studies , observations have to be planed, showing may be more accurately the relation between observation and theory.    Moher emphasises the positive effect of his approach, its "affective impact" (more emotional interest in the phenomena) and its impact of productive social interactions. And indeed one must recognise that  this smart idea provides students with an unprecedented experience. However, there is not much conceptual analysis, and it is difficult to assess how far this will be manageable and robust enough under the classical practical constraints in school. It is said at the beginning of the paper that "the [embedded phenomena] framework does not prescribe an instructional design per se, not does it provide any direct scaffolding to support learning", but few lines later it is claimed that "phenomena are made accessible and responsive to the needs of learners through the novel uses of classroom time and space". How are needs of the students, specifications of the environment and orchestration required from the teacher taken into account in the design and the implementation of embedded phenomena? There is inherently a simplification in the design of this framework and, at the same time, a complexification of the teaching and learning context. How far does this count? How does it impact the learning outcome? And the teaching task? Embedded phenomena have a huge learning and teaching potential, but it also opens the way to quite difficult and stimulating research questions. No doubt that we will be eager to discuss these with Tom Moher when he comes to the Learning science conference next summer in Utrecht . Moher, T. (2006). Embedded Phenomena: Supporting Science Learning with Classroom-sized Distributed Simulations. Proceedings ACM Conference on Human Factors in Computing Systems (CHI 2006) (April 2006, Montreal, Canada), 691-700. (Best Paper award)