They play. So far, so good. But, what do they learn?

Retrieved from a post of Nicolas Balacheff on the SOA scientific portal on February the 26th, 2010
 
Martin Oliver and Caroline Pelletier contribution to the edited book "Digital Generations" is quite interesting and stimulating, taking up the challenge of contributing to our effort to understand "what, if anything, people are learning by playing games" (p.69) Their contribution is based on activity theory, referring primarily to Vygotsky, built on the system formed by the Tool as a mediator between the Subject and the Object (the latter meaning the intention of the subject) and its contemporary extension by Engeström and others which takes into account the social determination of both the Subject and (his/her) Object(ive). The authors make the relevant remark that taking a systemic perspective means that properties which may be identified cannot be ascribed to the Subject as an isolated part of that system. What raises a theoretical and methodological difficulty when the problématique is to understand learning (or Subject semantic/meaning attached to a behaviour). Meeting this difficulty with the cK¢ model [*], I solved it (if I may say so) by considering what could be seen as the projection of the system model onto one of its components, the learner (or onto the Tool). In the case of cK¢ it leads me to propose the (P, R, L, Σ) quadruplet to model the learner conception (what could be mirrored by a quadruplet of the same kind to model the Tool). So, it is clear that I am interested in the method of analysis which the authors propose in order to operationalize the theory.

Then, looking precisely at the proposed methodology, I see a few issues which may be interesting to discuss: contraction, action/operation and in the end the reference to learning and the related question "what is learned?"

Contradiction is a difficult concept to manipulate from a methodological point of view. As Piaget analysed it, contradiction exists if there is a witness of its existence and it can be noticed only if there is an explicit awareness of an objective or an expectation. So there may be a contradiction from the point of view of the observer and not from the point of view of the Subject. How to decide on that? Which observed behaviours can inform the observer? These are difficult questions but critical ones when learning is at stake (as pointed by the authors). So we cannot diagnose a contradiction if there is not an evidence that it is the case for the Subject and hence if we cannot state what is the Object from the Subject point of view. This points a new question: is the Object what the designers or the researchers or the observers claim to be? This question which is important to model the game-playing activity is indeed critical from a learning perspective (it is directly related to identifying learning outcomes). The authors identified in the discussion section, in relation to the interpretation and classification of observed behaviours, the "such claim are difficult to justify without assuming (rather than knowing) the intention of the player" (p.83). My own position is that this is a central issue for learning and that our research effort must start from that point : an explicit hypothesis on the learner intention.

The delicate distinction between action and operation could be better addressed if it was contextualised by such a claim about the intention of t he Subject or the Object of the activity. The authors express their expectations of a progress if a finer grained reading of the actions or the behaviours (eg eye tracking) was possible. My claim is that it may be of no help if the observer cannot relate it to an intention or an objective. Actually it is the identification of the Object in the system and/or the intended learning outcomes (at least as research hypotheses) which will determined the reasonable level of granularity we have to reach.

Eventually, in my opinion, the question "what is learned?" cannot be answered without responding to the question of the objective, intention, aim of the game and the situation which contextualises it. If we do not start from that point, we will progress as blind researchers and in the end respond "they learn how to play" (p.86), which may be a disappointing and quite unhelpful answer. We may agree that this applies also to the problem of understanding the Subject intention, then the nature of the Object and in the end the whole question of learning in a game environment. This issue may be peripheral from a strict game-play perspective, where whatever is learned the motivation and the interest in the game is the thing which counts, but it is critical from an educational point of view.

Note: - Piaget et al. (1974) Recherches sur la contradiction Paris: Presses univ. de France, 2 volumes. - (P, R, L, Σ) stands for Problem, Operators (in French "règles"), Representation (semiotic system), Control structure

A note after the reading of: Oliver M., Pelletier C. (2006) Activity theory and learning from digital games: developing an analytical methodology. In: Burckingham D., Willett R. (eds)  Digital generations (pp. 67-92). Mahwah, NJ: Lawrence Erlbaum.

Retrieved from a post of Nicolas Balacheff on the SOA scientific portal on February the 27th, 2010

I recently read an article from Begoña Gros on the use digital games in education which offers a general overview of video-games and their contribution to learning, with an interesting discussion of their use in a school context. While focused on instructional design and not on computer science design, it still touches a few technological issues.

After a short history of the area from the research perspective, Begoña Gros reports on what we can learn from research on the contribution of games to learning. Several general cognitive competences are mentioned: improved spatial skills, iconic and spatial representations, ability to read images, divided visual attention, keeping track of events at multiple location on the screen, better developed attentional skills including metacognitive competence enhanced by the collective game play (sharing strategy, knowledge, sharing resources). "However, there is no research that actually documents a link between video games playing, attentional skills, and success in academic performance or specific occupations" (p.30). So it is not surprising that while most teachers acknowledge the contribution of games to the development of a variety of skills thay witness a resistance in adopting them in their everyday practice. One reason is the time needed to become familiar enough with a game so that a significant activity can be engaged. Another reason is that "it is difficult for teachers to identify how a particular game is relevant to some component of the curriculum, as well as the appropriateness of the content within the game" (p.35). This resonate with the remark that "game designers are not concerned with the accuracy of contents of the games and, on occasions, they are capable of producing contradictions or erroneous concepts with respect to the function of particular games used in learning activities" (p.36) This time, "design" means computer science design of game-based learning environments.

The main concern which is transversal to this paper is that of the challenge of adapting computer games to school and curricula. I would suggest an other challenge which is that of a closer collaboration between researchers in computer-science and education to design learning games not only adapted to the use in schools but also coherent with the game of knowledge.

Blog post after the reading of: Begoña Gros (2007) Digital Games in Education: The Design of Games-Based Learning Environments. Journal of Research on Technology in Education 40 (1) 23-38

A conversation on "debriefing", a key stage in the use of learning games

Based on a post on the SOA Science corner blog , originally published on Tuesday 23rd, February 2010 (18:58)

What may be the differences between games and simulations? A paper by Sara de Freitas and Martin Oliver [*] suggests that there is not much, and hence that it is quite natural that many of the learning issues that are relevant for simulations are also relevant for games. If there is one difference to mention, it comes mainly from the entertainment characteristic which is attached to games, and it is exactly this dimension which makes both of them appealing to education and difficult to use. This difficulty rests in the fact that "in educational contexts, there is a need not only to enter the 'other world' of the game or simulation, but also to be critical about that process in order to support reflective processes of learning as distinct from mere immersion in a virtual space" (p.255). The authors notice that the apparent mismatch between the game and the curriculum may be due to “the omission of a clear debriefing session” (p.260). Then, the key question of evaluation: what should be the characteristics of a game (more generally a simulation), so that the debriefing is made possible? This implies that we can tell what the game-simulation is vis-à-vis the knowledge at stake (i.e. the expected learning outcome). This dimension of the analysis which is, in my opinion a prerequisite, is not considered in the paper. Should we add it as a fifth dimension to the four already proposed (context, learner, internal representational world, processes of learning)? Or is it subsumed in a way that I didn’t catch in my reading?

Martin Oliver responded (February the 26th 2010) that...

Sara de Freitas is certainly interested in the kinds of games that resemble simulations - she likes to use the portmanteau "gamesim" to denote this category.

Personally, I think that attempting to draw clear definitions that distinguish games from simulations would be problematic - my opinion is that what makes them useful or not is how they get used. A game can be treated as a simulation, and a simulation can be played with; it's a matter of convention which side of the definitional line they are placed on.

The discussion in relation to the "other world" experience of the game reflects that Higher Education (rather than, say, training) values the ability to reflect upon and critique experience, not just improve it. (Obviously that's a value statement, and not universal, but I'd refer people to Ron Barnett's work for a more general discussion of this kind of issue.)

The debriefing session is an example of a pedagogic technique intended to help bridge differences between play and curriculum performance - in some ways, this could be understood as just one more example of the classic problem of learning transfer. What is learnt from play is unlikely, in itself, to map neatly onto the goals of the curriculum; the debriefing simply recognises that a process of reinterpretation or renegotiation may be necessary. I don't think that "debriefing" describes a well-defined pedagogic interaction - more a class of conventions about asking people to make sense of the experience they have just had. To this extent, all that's required of a game (or simulation) is that people have an experience to reflect upon. We haven't tried to engage with what makes some debriefings better than others; this is, I'm sure, a fruitful area to consider but it's not one we looked at. Matching the game design to that debriefing is then an obvious and sensible approach - but again, it was outside the scope of this particular paper (which focused on evaluation rather than design).

And the conversation continued (Nicolas Balacheff, March the 1st, 2010)

"Debriefing" is a concept worth to be discussed a bit further. In order to explain why I think this way, I will start from the idea that inviting students or trainees to play a game is always (I use this word on purpose), a teaching/training-learning context, with an agenda in mind. This agenda may be hidden to the learners, but it is a key reason why to choose a game and invite them to play it. This agenda can be described in terms of learning outcomes (from a piece of knowledge to a specific behaviour -- possibly at a meta level like in problem solving or socialisation). Even if the game is successful it is unlikely, because of the richness of the game-play and the short time given for the genesis of whatever mental construct, that the learners will realize what was important, new, worth to be made explicit, put in a certain form and kept for further use. It is even more difficult to imagine that they will be able to relate any interesting outcome to knowledge socially or culturally shared by the community they will join after this teaching/training-learning period. So, from an educational perspective, debriefing is critical. Within the frame of the theory of didactical situations this phase is called "institutionalization". Indeed, this is even stronger than "debriefing", it means that the teacher-trainer has a special voice and responsibility in acknowledging the learning outcome and the value of a learning game.

A note after the redeading of: de Freitas, Sara and Oliver, Martin (2006). How can exploratory learning with games and simulations within the curriculum be most effectively evaluated? Computers and Education 46 (3) 249-264. 

Why do learners (not) blog?

Retrieved from Nicolas Balacheff  (2010) comments on papers available on the SOA scientific portal

We have heard here and there claims and expectations about the so-called Learning 2.0 revolution. The rational is that learners will be able to share, collaborate, exchange in a more open and dynamic way, blowing the barriers that formal education and training may have raised on the way towards knowledge. Among learning 2.0 tools, there are blogs. All of us, I mean the blogers, know that bloging is not such an easy thing and having the tools is not enough. So a paper like the one of Behringer and colleagues is especially interesting in that it explores in a pragmatic and rigorous way the students motivation or lack of motivation to use blogs; among the latter there is a preference for direct communication and fear of a loss of privacy. May be not a surprise… a question one may have is that of knowing how far this is intrinsic or witnesses the weight of a culture and a lack of experience of these tools.

A note after the reading of: Andergassen, M, Behringer, R, Finlay, J, Gorra, A, and Moore, D. “Weblogs in Higher Education – why do Students (not) Blog?” Electronic Journal of e-Learning Volume 7 Issue 3 2009, (pp203 -215)

Could designed-based research become the TEL research standard?

Retrieved from Nicolas Balacheff  (2010) comments on papers available on the SOA scientific portal

Design-based research is a rather interesting framework for TEL research project,which although not new (the seminal papers go back to the early 90s) does not seem to have deserved all the attention it should in the European research area. Taking as an indicator the references of the EduTech wiki from TECFA (*), one may conjecture that it reached us in the early 2000, but since then I have not the feeling that it has spread very much within our research community. I don't see clear reasons for that. In my opinion we must spend some efforts, especially in a network like Stellar to consider this approach. From the presentation of Wang and Hannafin (ETR&D 53/4 2005), design-based research seems to be especially adapted to multidisciplinary research as well as to research which must be carried out in close connection to the field it explores. It may be the case that some researchers think that they are working in this paradigm while actually they do not, since there are at least two occasions of misunderstanding. The first source of misunderstanding is the emphasis of design-based research on iteration, an emphasis which is reminiscent of the life cycle of technology design. But here iteration is not only aiming at the improvement of the design, but also at critically revisiting theories to develop or refine them. What is valued is the practical use of theories (p.13), and the fact that theoretical and practical issues are tightly related. The second source of misunderstanding is that because of its close relationship to the field, design-based research may be confounded with action-research. This is missing the priority of design-based research, while acknowledging its situatedness, to transcend the particularities of the context in which the experiment is been carried out. This difficulty is very well identified in this paper, and addresses directly the main concern of our field which is of understanding what results we produce which could be of a general value beyond the specific project in which it has been obtained: "Generalizability […] must be verified according to the theory goals of the design and discipline requirements of the research. Researchers need to optimize a local design without decreasing its generalizability […]" (p.19). So design-based research is not a sophisticated conceptualisation of the life cycle of a technology, it is of a different nature and objective than action-research. To some extend it can be seen as a proposal for a new discipline with original problems of methods and rigour.

There is one point on which this paper passes a bit too fast. It is the meaning of "real", what could count as "real-word context". Any experiment or observation carried out in a classroom changes what it is as opposed to its normal functioning. This is well-known but  as a common sense fact and scientifically not enough documented. The authors acknowledge the complexity of reality, but do not catch the need to model it in an explicit way (with all the constraints of something which is out of reach of an exhaustive description, indeed). Any experimental science is faced to this need including natural science. The place where an experiment is carried out is an experimental apparatus, it has to be described as such even if it is embedded in a so called real context. (it means a context which is largely out of control but if which many features have no impact). This is a condition to be later on able to discriminate between generalizable results and "idiosyncratic" (p.19) adaptations or observations, and to sort out which of the data are relevant for further analysis. This dimension of design-research may well be the missing element to succeed in becoming the scientific standard it is ambitions.

Blog post based on the reading of: Wang F., Hannafin M.J. (2005) Design-based research and technology-enhanced learning environments.  Educational Technology Research and Development 53 (4) 5-23, DOI: 10.1007/BF02504682

Moving research on learning games forward

Retrieved from Nicolas Balacheff (2010) comments on papers available on the SOA scientific portal

Among the text I have recently read about learning games, "Moving learning games forward. obstacles, opportunities and openess" (Klopfer E., Osterweil S., Salen K. 2009) is in my opinion the most comprehensive, insightful and likely to provide a good basis for beginners in this research area.

First it synthesizes efficiently the common views of learning games and of the relations between games and schools, without caricaturing the situation. Second it considers in a contrasted and balanced way digital games and learning games from an economical and a functional perspective (what they are for). Third the paper survey ideas and principles about the design and use of learning games, covering most of the aspects be they technological or cognitive, educational or institutional.

One the one hand, some claim that games are so efficient to favour and enhance creativity and learning that the value of school is questionable, they even may not hesitate to abandon schools. Others consider that games are not relevant or manageable in school context and hence tend to exclude their use. The authors, considering the arguments, argue that there is room for the use of games, and that this use can enhance learning, provided that certain conditions are fulfilled. A first condition is that the school context does not kill the basic characteristic of game-play which is "freedom", while drawing attention to the fact that a game is based on a structured set of rules with "win" states criteria (so "freedom" must not be read in a naive way). The game structure guarantees "fairness by being applied transparently and equitably to all players" (p.5); a point which is important because it allows ending a game not depending on an (apparently) arbitrary decisions of a teacher. In other words, if a game is ruled by some knowledge, then it is this knowledge which will serve to end the game. A principle which is at the core of the theory of didactical situations (*); later in the paper this takes the form of principle: find the game in the content.

After a discussion of commercial games, the authors conclude that "learning games can also be fun and have mass market appeal" (p.9) and suggest that they have not to mimic the high-tech look and feel of video games. One must leave common sense ideas about what a game should be (e.g. game=virtual world) and understand the fundamental characteristics which may make them relevant for learning: "feedback, structure, goals or path to progress" (p.14). Eventually, they propose criteria to characterise learning games: "they target the acquisition of knowledge as its own end and foster habits and understanding that are generally useful within an academic context." (p.21). A puzzling thing here, is that they make a difference between learning games and training games, and seems to associate tightly school and academia. A position which can be understood if "training" is viewed in a very limited way, and vocational studies is marginalized -- what would be a mistake.

Eventually: "what is the magical recipe for a good educational game?" (p.27). Luckily, the authors dare to ask such a question but do not respond by a recipe, but rather by a set of principles and tips (some) borrowed from Castranova (quoted by Baker 2008): "making a game out of learning will most certainly not be the way to approach the development of learning games. However, "finding the fun in that learning" and devising ways to focus on and enhance that fun as a core game dynamic is a good strategy", and "go to the right tech". Then 14 principles of design are listed. A list not homogeneous, addressing different levels and layers. I would retain only a few of these:

"4. Put learning and game play first" (p.31) adding this warning: "There may be some fixed set of constraints on both the technology and learning goals that are unchangeable--and of course, sometimes the combination just won't work";

"5. Find the game in the content", including the quite strong claim that "in any academic discipline, there are elements that are fundamentally game-like", moreover adding that "an educational game should put players in touch with what is fundamentally engaging about the subject matter" (p.28). Such statement converge in a very interesting way with the Brousseau's claims about the game of knowledge when in the 70's he coined the theory of didactical situations (**). Including the refutation of the idea that "games single-handly teach the subject matter". I would add that learning games need a well designed didactical framework (including the teacher).

"11. Define the learning goals" (p.36), this seems to be common sense but I agree with the authors that there is a common view that learning in a game context will happen naturally and be of value. But if we ask "what are kids supposed to be learning?", then the role and outcome of the game is anything but obvious.

To conclude this reading note, let me emphasise this call: "it is imperative that researchers and developers more clearly define their learning goals and corresponding assessment tools be developed and shared openly" (p.37). Definitely this paper is more than a survey, it is a research programme and could be now read as such. Many of the statements hide difficult questions, the game now could be to discover them, state them and propose a research strategy to address them.

Teachers adopt technology, learners should

As Rosamund Sutherland notices, educational technology has entered the classroom, but in many cases in support of the teacher activity (e.g. the interactive white board used as an enhanced black board) and not so much in support of learners activity. But let's hear her view:
But may be this is the result of the incapacity yet for technology to respond to the proper ecology of the classroom which is complex either from a spatial, social or intellectual perspective. The classroom as a technology enhanced learning space, still a challenge.

Exploratory learning versus Inquiry learning, where is the difference?

You may have recently received the call for the ITS 2012 workshop on "Intelligent support for exploratory environments: exploring, collaborating and learning together" which central object is the designed implementation and use of Exploratory Learning Environments (ELEs).

An occasion to ask whether there is a significant difference between Exploratory learning and Inquiry learning. Both terms are used, do they share meaning or is there a nuance I miss?

Learning aware environments

Retrieved from Nicolas Balacheff (2006) e-Agenda European Forum, Casteldefeld

Once upon a time (Eden research workshop, Casteldefeld 2006), I was asked the question: “Can we introduce learning in every human activity”? From a non-English speaking perspective this question may sound strange. Isn’t it the case that learning is present every where and at every moment in our life?  This is a matter of survival. Learning is a competence shared by all living organism. Learning is life long. It starts with our first breath and continues with it until the very last second. 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.).

Designing environments likely to stimulate and support learning outside formal education and training experience—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 technology 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. That is 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 technology 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).

How do you expect people to learn in the future?

"How do you expect people to learn in the future?" A question I heard recently, which will never be out of date... here is how I viewed it ten years ago.

I remember, fifty years ago, I thought that by the end of the century cars would have almost disappeared and we will all be equipped with personal helicopters… It is the way I expected people to travel in the future! I am afraid that the question is as risky today in the case of learning. What I expect, is more relevant environments because of the development of virtual reality and a better understanding of learning and teaching (training). Learning may not change a lot in the coming fifty years, but the learning opportunities and possibilities may improve a lot; in particular behavioural learning and training should dramatically develop (acquisition of tacit knowledge, learning of how to perform professional gestures). On the other hand, if reliable and secure on-line certification develops, then lifelong learning which always existed from an individual perspective, may become a reality from an institutional perspective. Failure in the initial formal schooling will appear far less critical, and eventually the institutional models of school and training systems could change at this point since evaluation and assessment is the real driving force of any (to-be-) institutionalised learning.

Some progress since then?

Teaching, an emergent property of learning environments (2)

Retrieved from Nicolas Balacheff (1999) notes for the EU/US conference, Stuttgart

One of the main characteristics of complex knowledge is on one hand that to master it requires to master several different pieces of knowledge organised in the form of a system, and on the other hand that its use depends on methods which are not mere algorithms. Such knowledge cannot be constructed spontaneously even when the learner is provided an adequate problem-situation, an in some cases such situations are 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 conceptions, i.e. 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 it. The development of technological tools to use these knowledge (formal computation, simulation, etc.) increases the difficulty by modifying within a kind of systemic loop the nature of the users conceptions.
One cannot expect one universal agent to be able to handle the complexity 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.

The development in Grenoble of the project TéléCabri, within the "Computational Environment and Human Learning Group" (EIAH) of the Leibniz Laboratory, allows us to get an insight of this complexity at different levels:

• At the epistemological and educational level, e.g. all the problems of learning in an environment which associates the best technology, like the microworld Cabri-geometry, and the classical means (books, notebook, etc.), as well as the teaching problems raised by the cooperation of teachers through the technology but also with the technology, with a full distribution of learners, teachers and resources within space and time.
• At the technological level, e.g. the problems of ensuring that the platform which associates different types of machines, visiocommunication, TCP/IP and H320 protocols, access from the TéléCabri site as well as from students or teachers places. At this level the institution has to realise that education may quickly need not only buildings, teachers and administration staff but also engineers.

A platform like that of TéléCabri is structured by several different axis 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 depending of the needs at the time when the interaction is looked for.

It is rather clear that the solution to the problems one meets on such a platform cannot be solved by one super-ITS being implemented on a learner super-machine. It is also clear that the availability of human teachers is crucial either because of the limits of the technology or because of the needs of students for a human presence. Then, the learning environment should be constituted by lot of resources, content specific as well as conception specific (taking into account the variety of learners possible conceptualisations); the teaching power of the whole system will not 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. May be it is just rediscovering that education has never been the result of the action of one isolated tutor but of the Society at large...

Cuban wrote in 1987: "[Teachers] will either resist or be indifferent to changes that they see irrelevant to their practice, that increase their burdens without adding benefit to their student learning, or that weaken their control of the classroom" (p.71). After more than a decade focussing on the learner, we could rephrase this quotation to emphasise the need for more investigations on what could be the conditions for the educational efficiency of learning environments from the point of view of general education or training as well.

Up to now, most of the basic or applied research, have been carried out in classical environments (schools or training centres). This has strong limits since it is not true that teachers and learners can involve in a radical way the new technology.The TéléCabri project is an attempt to do so, targeting students being not being able to join the classical schools (they are cured at home or in an hospital). By the way, this platform developed in the Grenoble Academic Hospital is an excellent example of a EU-USA collaboration (it is the product of a joint effort from the EIAH group, Hewlett-Packard and PictureTel).

A step further would be to set up an Educational Technology Centre (like those suggested by the "President's information technology advisory committee" to President Clinton—august 1998), this would be a very expensive and complex initiative which would surely benefit from an international synergy, putting together the best of education and technology from EU and USA.

Teaching, an emergent property of learning environments (1)

Retrieved from Nicolas Balacheff (1999) notes for the EU/US conference, Stuttgart

The trend of research in educational technology, during the last decade, has been to focus on learners and learning. The evolution of the ideas could be sketched in the following way : the initial paradigm was to design Intelligent Tutoring Systems (ITS) as autonomous machines with strong instructional functionalities and some sort of modelling of learners' needs and cognitive characteristics, a second paradigm has been the development of learning environments (eg microworlds) opening to the learner a real space for the exploration and the construction of knowledge. The former has not led to clear success, the later has evidenced serious difficulties (well documented by the Logo literature) and the need to complement the environment by teachers input and guidance. The lesson then, is that if teaching reduced to instruction is not the more successful avenue, the absence of teaching features in a learning environment does not guaranty either the quality of the learning output.

What are the lessons ? Clearly the need to search for a new paradigm which could ensure a better equilibrium between learning and teaching, between human and machines. The common interest of Europe and the US, either in general education or professional training (lifelong learning), to overcome educational difficulties especially in science, mathematics and language learning, together with their common recognition of the potentialities of educational technology, should lead to a fruitful synergy in this area.

The reasons why the learner, either a child or an adult, needs "teaching inputs" are very often hidden as a result of the strength of the emphasis on the constructivist principles of design of learning environments. These needs are especially important with modern environments which are largely distributed and provide a potential access to a huge range of knowledge and information. These reasons could be sketched by the following questions which acknowledge that the learner has in general a low level of control on the events which are on the edge of the learning process in which he or she is involved—unlike the expert problem-solver:

"How to look for something you don't know? "
"How to know that you have found what you looked for? "
"How to know that you have learned?"

A last question raises a crucial question related to the fact that in many cases learning is related to a willing to get the adequate qualification with respect to a given competence or activity. Indeed, the issue of certification must be considered together with the design of a learning environment, since…

"How will others know that you know?"

These issues, which call for the involvement of teaching (agents) in the learning environment, are even more essential in the case of complex knowledge (as opposed to basic skills).

Education, éducation and bildung... far out of reach

Retrieved from the TEL opinion blog, January the 4th, 2007  

"Science Education” or “Mathematics education” are not expressions easy to translate in French; we would prefer to speak of “apprentissage des sciences” ou “apprentissage des mathématiques”, or alternatively of “enseignement des sciences” or “enseignement des mathématiques” but we have the “éducation physique” which has recently been renamed “Activités physiques et sportives” (APS) after the emergence of the “Sciences et technologies des activités physiques et sportives” (STAPS) as an academic domain. Still we have the “éducation civique” which aims at educating the learner as a citizen, with as an alternative the “instruction civique” which seems more like teaching than educating. This quick sketch of the linguistic context in which we have to communicate, demonstrate that the word “education” is a difficult one, which seems not to translate well in English when we compare the French use of the word with the English use which seems to be a bit larger.

I suspect that the same happens with the German word “bildung”—a word even more complex than “éducation” if one considers the 10 pages it deserves in the “Vocabulaire Européen des philosophies”. I will not here try to summarize the “bildung” section of this dictionnary, but just notice that its connotation is much closer to culture and civilisation, although indeed it is far from being a synonymous of any of them. The distance between “bildung” and “das lernen” or “das unterrichten” appears to be larger than between “education”, “learning” and “teaching” .Indeed, this raises a serious question when translating “Artificial Intelligence and Education” and using AI-ED as a key word in our domain. Not to mention all the key words using the word “education” or one of its versions.

However, John Self acknowledges a difficulty of the same nature, when writing that:

“If a field is to call itself ‘AI in Education’, then it seems necessary for it to say what it considers ‘education’ to be. However, despite its name, AI-ED has never been concerned with education in its broad sense but only with the specific issue of learning. We may believe that the whole purpose of education is to promote learning but in reality the process of education includes many activities only indirectly related to learning, as any textbook or conference on ‘education’ will confirm. 

The term ‘education’ is generally taken to mean ‘formal education’, that is ‘paid-for education’, rather than the ‘informal education’ we receive for free from our culture’. There is a nostalgic preference for the latter, with the former being considered to stunt individual learning capabilities. These polemic views will not be our concern. We will be concerned only with the nature and effectiveness of the learning processes.” (Self 1995, p.6)

The best decision may well be to avoid “education” as a key word, or part of a key word in our metadata. Indeed with one exception: AIED… 

Self J. (1995) Computational mathetics: towards a science of learning system design . November 1995 draft version (available online at that time, sometimes refered to as Technical Report 96/23, Computer Based Learning Unit, University Leeds) Cassin B. (ed.) (2004) Vocabulaire Européen des philosophies . Paris: Seuil & Le Robert

Learning, not so far from teaching

Retrieved from the TEL opinion blog, November the 18th, 2006
 

We have all experienced difficulties in translating our papers and talks into English, and some of our English colleagues have taken up the same challenge when preparing their communication in an other language. The difficulty is classical: translation is not a mere transduction, words from two different languages rarely match: beyond the definition there is the connotations induced by the context or shaped by the history and the culture. This is not only a problem when translating our papers and talks, it is also a problem when establishing an ontology or metadata from an international perspective. This is especially a problem for research on TEL because most of our work does not develop in a formalised framework: the meaning of our words is not stable or fixed, even for recent neologism like e-learning (or elearning, or eLearning…).

I take here a first example from among all the problems we had to solve with Lucile Vadcard and few Kaleidoscope colleagues when building the metadata for the description of the documents to be uploaded on the TeLearn open archive that Kaleidoscope recently launched. This first example is “learning”. Indeed, “learning” is a word which is at the core of our discourse, and essential to any of our theoretical or practical activities. Here are a few of the expressions one could consider, they are taken from what is often proposed as keywords by conferences or journals: collaborative learning, ambient learning environment, learning environment, augmented learning environment, blended learning, distance learning, learning object, learning grid, situated learning, tangible learning, etc. When translating in French, it is clear that a “learning environment” is not “un environnement qui apprend” but “un environnement pour apprendre”, or to make it provocative: “un environnement qui enseigne”. This is more evident with the expression “blended learning” which is difficult to translate in a simple manner, it could mean “apprentissage mixte” (as suggested by Wikipedia) but this misses that eventually it refer to a teaching strategy which makes the best benefit of different possibilities, either digital or not, to stimulate and support learning. Again, we see that there is some “teaching” in the meaning of “learning”. It is very likely that the source of our difficulty is there. It is possibly why some of our colleagues decided not to define the expression “mobile learning ”!

Invited to participate in the workshop eAgenda, I had to consider the question: “can we introduce learning in every human activity?” One may understand now why, at first, this question embarrassed me. To elaborate a comment, I thought interesting to come back to the origin of “learning” and “teaching” in the English language. Both English words, “learning” and “teaching”,  has 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?” In other words: can we empower every environment with “teaching” capabilities.

Indeed, such a discussion goes beyond a problem of translation. It raises the problem of understanding what is our field about. In my opinion, it is about “technology for human learning.” In this expression “learning” point more specifically the human epistemological challenge, passing to the small word “for” the burden of the teaching connotation. Moreover, it translate well in French: “technologies pour l’apprentissage humain”!

If you are interested by continuing this discussion, and not only reacting to this blog,  just click here

A didactical view on authenticity

Retrieved from the TEL opinion blog, August the 27th, 2008

The search for authenticity of learning situations is a concern for most designers of TEL environments. Most of them realise soon that this is a desperate project since any environment is a representation of some kind of a reference, often called "reality", which keeps staying at a distance. To be as close as possible to reality does not mean much, unless we can qualify or quantify the closeness. Indeed, this is a challenge and we are not be well equipped today to take it up. A solution might be to find a theoretical framework within which we can formulate the problem, and then search for a solution within this framework. This first step will put limits on this solution, but it will make it much more tangible and so accessible to further progress. Currently we too much lack definitions and references to ensure that we can seriously discuss the issue. But, let's try something...

 First, we may agree that a learning environment becomes such if it is embedded in a situation which can contextualise the learner activity and hopefully stimulate, support and validate his or her successful learning. Be they formal or informal, these situations have an objective which can be made explicit in learning terms at least from the point of view of their designers; the fact that this objective is explicit for learners is another story. Following Brousseau(*), let's call "didactical" these situations. Didactical situations can be distinguished from other situations by their explicit intention to "teach". And here is the problem! As soon as the learner identifies this intention and bases on it his or her activity, it is very likely that the learning outcome will not have the expected "authenticity". All the search for authenticity of learning situations (and learning environments) is dedicated to the overcoming of this difficulty.

Second, let's consider the limit case of a didactical situation which didactical intention is completely transparent. If learning occurs in such a situation, we could ascertain that its outcome has the expected "authenticity": it does not owe the didactical intention (in other words the reasons for the activity of the learners are in the knowledge at stake not due to any guessing of the teacher or trainer expectations) These are "adidactical" situations, let's quote Brousseau:

"[The student must know that] this knowledge is entirely justified by the internal logic of the situation and that she can construct it without appealing to didactical reasoning. Not only can she do it, but she must do it because she will have truly acquired this knowledge only when she is able to put it to use by herself in situtations which she will come across outside any teaching context and in the absence of any intentional direction. Such situation is called an adidactical situation. Each item of knowledge can be characterized by a (or some) adidactical situation(s) which preserve(s) meaning; we shall call this a fundamental situation." (Brousseau p.30)

These three concepts: didactical situation, adidactical situation and fundamental situation will allow us to locate our problem of authenticity, and to formulate it.

So, designing an authentic learning situation depends on our capacity to characterize the related fundamental situation in relation to the piece of knowledge which learning is at stake. The problem is then not the closeness to reality, but the fact that the situation has the epistemic properties specific to this piece of knowledge. The specification of a so-called authentic environment requires first the expression of these epistemic properties and of the way they can be "translated" in the tangible world. However, once we have such a situation, there may be still a long way to designing an adidactical situation likely to be made available to learners. The design of this adidactical situation and the related environment is the challenge of designers of authentic TEL environments. After that, there is still one issue for the teacher: bring to life this adidactical situation in the classroom without damaging its "authenticity", what is the didactical challenge!

A quick example to conclude this post: the concept of "angle" in mathematics finds its full meaning when linear measurement is not possible or too "expensive" (for example when sailing on the Atlantic). Let say that the fundamental situation for "angle" is the problem of locating a point in the macro-space. We can realize that the classroom can hardly host a macro-space, we have then to find a situation which has the characteristics of the macrospace (linear measurement being impossible or too "expensive") and can be implemented in a classroom. If the problem were presented in the frame of a piece of paper (micro-space), the situation may appear quite artificial in the students eyes (a ruler is enough), then the corresponding didactical situation would be delicate to negotiate and in the end fragile. Technology can offer a solution, opening the window of the computer on the macro-space...

Brousseau G. (1997) Theory of Didactical Situations in Mathematics . Springer (Kluwer Acad. Pub.)

In search for the authenticity of learning situations

Retrieved from the TEL opinion blog, January the 4th, 2007
 

 "WallCology" is a neologism coined by Moher's team to designate "a ubiquitous computing application [...] which situates a virtual ecosystem within the unseen space of classroom walls" (p.163). Actually, this technology blows the boundaries of the screen, and even of the internet; it invade the "real" world, following the design principles of embedded phenomena project which I introduced in a post some times ago. From a content perspective:

"WallCology situates students within a complex virtual ecosystem, where they may conduct investigations focusing on topics such as the identification and classification of species, habitat selection, population estimation, food chains, predator-prey relationship, life cycle phases, adaptation and response to environmental change" (p.164)

Then learners are exposed to a field of experience which hybrids the "real" and the "artificial" worlds. It is not an augmented reality, nor a virtual reality, but a new world which holds key characteristics of the world we are familiar with: persistent, tangible, immersive. Phenomena are simulated, and the simulation is -- I may say -- seamlessly embedded in the learner physical environment. The underlying vision is of offering learners the experience of contemporary science inquiry (i.e. "collaboration of researchers from multiple distributed sites working around research questions associated with a common phenomenon" -- p.165). However, the project does not propose only a technology but a comprehensive environment in which learners have to cooperate, organise their work and also to learn how to behave in order to make experiments and observations possible: The WallCology "creatures" are designed to behave in such a way that "students must learn to approach the observation points quietly, and to consider the reaction to noise as a component of their behavioral description" (p.167).

Designed with "the desire to problematize inquiry", WallColgy includes a lot of the characteristics to facilitate a "move closer to authentic physicality" (p.166). However, Moher's team suspected limits in this choice. I don't mean only technical limits but what we may call epistemic limits. For example, they decided to use imaginary creatures instead of "authentic" ones in order not to frighten young children and to avoid stereotyping the living conditions of some learners.

This consideration points a question rarely addressed: what means "authenticity"? Once one has said that there will always be a distance between the real world and any of its representation, what can we add? Is authenticity an issue of the same nature for entertainment, expert planning (architecture, surgery, etc) or learning and training?

The environment has been implemented in two classrooms, respectively for seventh and third grade learners. The article report on these experiences is contrasted. On the one hand there are clear indications that learners played the game and their behaviors provided "tentative evidence of the effectiveness of the feature in promoting authentic inquiry practices" (p.169). Learners were genuinely committed to the problem induced by the situation and the WallCology context, they caught the complexity of the task and invented strategies, new research questions and structured their cooperation (distribution of roles). Many positive cognitive outcomes are then reported, but their progress was more at what I may call an instrumental level; at a more conceptual (so to say) level the progress is more limited. As Moher and his colleagues report it: learners (esp. Seventh grade) "did not show improvements on pre-post items related to the use of behavior as a cue to species identification" (p.170), or "none were able to give strong characterization of [the tag-recapture method] conceptual motivation" (p.170). Indeed, the authors have noticed that "the design of instruction and the design of technology proceed in parallel, mutually informed by curricular goals, classroom practice, and advances in technology" (p.171). But noticing this is not enough. So to say, the report of the project about students achievements resemble the reports of students about the bugs behaviors: there should be now a step towards a more substantial conceptualisation. If I dare a parallel, a psychological model of the bugs might not help the learners, but a model of the bugs interactions with their environment is surely the stake. Then:

what about a model of the [learners<->WallCology] system, or may be more generally what about a [subject<->milieu] system from a learning perspective?

Moher, T. (2008). WallCology: Designing interaction affordances for learner engagement in authentic science inquiry. CHI 2008 Proceedings - Learner support (April 5-10, 2008 - Florence Italy) - pp.163-172.

Ambient learning

Retrieved from the TEL opinion blog, January the 4th, 2007

"Ambient learning", in the TEL context, comes in general as part of expressions like "Ambient learning environment" (eg Gomez and al. 2004) or "Ambient learning technologies" (e.g. Lonsdale and Vavoula 2004). It refers to "devices and systems that enable active, responsive environments that play a part in the learning process". The expression is reminiscent of "ambient intelligence", an ICT conceptual construct referring to "devices [which] work in concert to support people in carrying out their everyday life activities, tasks and rituals in easy, natural way using information and intelligence that is hidden in the network connecting these devices" (Wikipedia ). Moreover, "As these devices grow smaller, more connected and more integrated into our environment, the technology disappears into our surroundings until only the user interface remains perceivable by users." (ibid.).  Richard Noss in the late 80s coined the expression "ambient learning culture", but the connotation seems to be different. The quotation and its textual context is:

It should be clear that the computer is being cast in a rather special relationship to the learning process, not simply as another concrete embodiment of an abstract mathematical concept. As Dörfler (1986) argues, the distinction between concrete and abstract is artificial in any case, since it presupposes that there exists an a priori union of actions and operations which is fractured in the course of learning. The key idea is that of focusing attention on the important relationships involved, a role in which [...] the computer is rather well cast; but not without the conscious intervention of educators, and the careful development of an ambient learning culture." (Noss 1988 p.263).

By "ambient learning culture" Noss means that one, in such a culture, would engage in learning in any occasion, everywhere, at any time; while in "ambient learning environment", it is the environment which is supposed to stimulate and support learning; an environment which might be naturally tutoring... Again, for the non-native English speaker, there may be some teaching in this meaning of learning. Then, how to translate that correctly in other languages than English? and, more important, what is the conceptual rational of this expression?

  Dorfler, W.: 1986, 'The cognitive distance between material actions and mathematical operations', in Proceedings of the Tenth International Conference for the Psychology of Mathematics Education (pp.141-146). London Gomes A., Mendes A.-J., Marcelino M.J. (2004)  Avaliação e evolução de um ambiente de suporte à aprendizagem de programação. Actas do VII Congresso Ibero-Americano de Informática Educativa, Monterrey, México, Outubro de 2004   Lonsdale P., Vavoula G. (2004) Research into current technology that could be applied to the design of learning spaces. Report prepared for JISC project eSpaces   Noss R. (1988) The computer has a cultural influence in mathematical learning (pp. 251-268) in Bishop A. (ed.) Mathematics education and culture. Dordrecht: Kluwer pub.

Retrieved from the TEL opinion blog, October the 15th, 2006 

GRID technology is a more and more important field of investigation in computer-science. It could be seen as the digital implementation of the old proverb “l’union fait la force” (unity makes strength), by its way of using distributed computing resources to make a kind of super computing device. Indeed, there are many problems to solve to ensure the reliable and efficient cooperation between machines having different pieces of a computing task, their solution requires the convergence of theoretical frameworks from parallel, distributed and high performance computing. Taking up the challenge of GRID technology is strategic. A proactive policy does now support the progress in this domain.

 As is often the case, the emergence of a new advance on the technology front stimulates a new exploration on the front of educational technology. This is the old technology push story, which in my opinion is not wrong as long as it is not driven by a digital mirage. The recently edited book “Towards the learning GRID ” is a good occasion to learn where we are with this domain and what is the vision of its potential for TEL. The authors, among which several key participants of the Kaleidoscope Learning GRID SIG , set the scene in a very relevant way: “previous projects that have set out to improve learning through novel technologies have often failed to leave any significant mark because they did not give priority to the social, economic and technical perspectives of the key human factors” (p.63). So the learning GRID venture for which the ultimate goal is to ensure “the possibility to personalise the learning processes according to the learners’ preference and style” (p.74), will not be replicating errors we made in the past.

 Following the leaders of the ELeGI European project our colleagues from CRMPA and DIIMA , the added value of the GRID approach is to give a framework to realise the effective sharing of heterogeneous resources based on the concepts of service, distributed collaboration, and virtual organisation (p.66). A characteristic of GRID technology, they remark, is that it is not based on a mere protocol communication among the resources, but on message communication among services; This remark suggests that the resources could engage conversational interactions about what is requested and what is responded. This means a kind of intelligence that, if it were to exist, must be based on an understanding of the learning/cognitive and pedagogical/didactical requirements. But at this point we may be disappointed by reading the authors suggestion that “an innovative aspect is that our general model is the presence of three models: Knowledge Model, Student Model and Didactic Model, which substantially interact among them to define the specific and personalised formative path” (p.73). Of course, I think that they are not coming back to the seminal ITS trilogy. So, where does that leave us?

In a fully distributed world (wide web) these models should be distributed as possible features of the resources. Moreover, they will be explicitly or implicitly tangled (e.g. a knowledge model for a learning environment de facto include an epistemic and a didactical model—the latter being at least that of a didactical transposition). Then, I would suggest that:

The didactical nature of a GRID for human learning is an emergent property of the resources it gives access to and the interaction it supports, and not the property of one of the components

This resonates well with the “learning ambient intelligent vision of the learning domain” on which these authors conclude their contribution (p.74). Then we may choose to consider teaching as an emergent property of a system instead of one of its dedicated functions. This view may invite us not to consider GRID technology as an end, but as “[the] technology for building the next generation of learning environments” (p.182):

“Through the adoption of [GRID technologies], we can have a wide-scale learning resource sharing in heterogeneous and geographically distributed environments, the implementation of learning organizations in which different actors (universities, teachers, learners), sharing a common target, are able to cooperate to achieve a result” (p.183)

Let’s add that the actors could be artificial as well as human, and we get the picture of a hybrid world driven by the learners’ needs. Eventually, this is a picture that we could have drawn with the modern multi-agents technology. So what is the specific added value of the GRID approach? It is claimed that it is a solution to fulfil educational specifications that we all share nowadays, but still this solution is presented in rather general terms. We are almost sent back to the initial question but from a slightly different perspective: what are the problems relevant for GRID research when raised from a learning perspective? What are they, not in general educational terms, but in computer-science terms?

These comments are based on the following chapters taken from Ritrovato P., Allison C., Cerri S.A., Dimitrakos T., Gaeta M.  and Salerno S. (eds. (2005) Towards the Learning Grid Advances in Human Learning Services (Frontiers in artificial intelligence and application series, volume 127). Amsterdam: IOS Press.

Gaeta M., Ritrovato P. , Salerno S. (2005) Making e-Learning a service oriented utility: The European learning GRID infrastructure Project. (pp.63-78) Capuano N. , Gaeta A., Laria G., Orciulli F., Ritrovato P. (2005) How to use GRID technology for building the next generation learning environments. (pp.182-191) Lemoisson P., Cerri S. , Sallantin J. (2005) Conversational interactions among rational agents. (pp.214-230)