One of the main research line of TECFA are `intelligent learning environments' (ILE). An ILE refers to a category of educational software in which the learner is `put' into a problem solving situation. A learning environment is quite different from traditional courseware based on a sequence of questions, answers and feedback. The best known example of a learning environment is a flight simulator: the learner does not answer questions about how to pilot an aircraft, he learns how to behave like a "real" pilot in a rich flying context. Experience with learning environments (like LOGO) showed that those systems gain efficiency if the learner is not left on his own but receives some assistance. This assistance may be provided by a human tutor or by some system components. In our flight simulator example, the future pilot would gain from discussing his actions with an experienced pilot. The implementation of these agents is based on artificial intelligence techniques in advanced experimental learning environments. In summary, we use the word `intelligent learning environment' for learning environments which include (1) a problem solving situation and (2) one or more agents that assist the learner in his task and monitor his learning.
Designing an intelligent learning environment (ILE) involves implementing some theory of learning and teaching. However, most available theories do not have the level of operationality required for implementation work. Designing an ILE is real research work. We are developing an intermediate framework that builds a bridge between theories and implementations by translating psychological knowledge into terminology more relevant to computer scientists. It specifies the cognitive architecture of systems like MEMOLAB. Let's examine two key concepts: the pyramid metaphor and the language shift mechanism.
The "pyramid" metaphor represents the concepts and skills to be acquired by the learner, ranked bottom-up according to their level of "hierarchical integration". Learning consists in moving up in the pyramid. Each level of the pyramid is defined by two languages: the command language and the description language. The command language vocabulary is the set of elementary actions that the learner is allowed to do at some stage of interaction. The command language syntax defines how the learner composes sequences of elementary actions. The description language is the set of symbols (strings, graphics,...) used by the computer to show the learner some description of her behavior. This description reifies some abstract features of the learner's behavior in order to make them explicitly available for metacognitive activities (Collins and Brown, 1988).
The command and description languages are different at each level of the pyramid, but each level integrates its lower neighbor. This integration is encompassed in the relationship between the languages used at successive levels: if a description language at level L is used as a new command language at level L+1, then the learner is compelled to use explicitly the concepts that have been reified at level L.This is what we called the language shift mechanism (Dillenbourg, 1992): when she receives a new command language, the learner must explicitly use the concepts that were implicit in her behavior. The meaning of the new commands has been induced at the previous level by associating the learner's behavior with some representation. This representation is now the new command.
The process by which properties that are implicit at some level of knowledge can be abstracted and explicitly reached at the higher level has been studied under the label of reflected abstraction (Piaget, 1971). The language shift mechanism has two uses. Firstly, it translates this psychological concept in a terminology more relevant for ILE designers. Secondly, it describes a pedagogical strategy (mainly inductive) to trigger reflected abstraction. By applying the framework to ILE design, we not only ground the structure of learning environments in a model of cognitive development. But such models of development can be tested through the difficult process of implementation. We found that this intermediate framework can be used to "interface" several theoretical backgrounds. Most psychological theories address actually only a specific facet of learning while an ILE designer must consider learning in its globality and complexity. Therefore, an intermediate framework should integrate multiple theoretical bodies of knowledge, each relevant for some aspect of reality. An educational computing system must account for the importance of discovery, for the role of practice and for the effect of coaching, because all of them occur at some stage of learning in the real world. The framework we propose can be read from different theoretical perspectives.
From Campbell and Bickhard's (1986) viewpoint, the language shift mechanism can be viewed as a process of inducing interaction patterns. An elementary interaction associates some sequence of user's actions and the computer's description of this sequence. Inferring the meaning of the description language can indeed be described as the result of inducing the relationship between the actions performed and their representation (Dillenbourg, 1992). This corresponds to a view of knowledge as something that stands in the interaction between the subject and her environment. It creates a bridge between our model and current research on situated learning (Brown,1990), a "hot" issue in AI and Education.
Our intermediate framework also introduces the designer to the theories of Vygotsky. The apprenticeship idea is reified in the pyramid model by sharing control between the coach and the learner: when the learner is able to perform at some level L, the tutor must guide her activities at level L+1. This level L+1 corresponds to the concept of zone of proximal development (Vygotsky, 1978). At each language shift, the learner will assume a more important control of his solution process and the coach's guidance will be reduced. Moreover, Wertsch (1985) proposed a linguistic analysis of the internalization process that relates it to the language shift. He observed (in mother-child interactions) that the move from the inter-individual to the intra-individual plane was preceded by a language shift inside the inter-individual level: mothers replace a descriptive language by a strategy-oriented language (i.e. a language that refers to objects according to their role in the problem solving strategy).
The third but central theoretical background that fits with our framework is the neo-Piagetian theory of Robbie Case (1985). We focused on this theory because of its rather operational form. The key idea in Case's theory of intellectual activity and development is what he calls the "executive control structure". He believes that problem solving across domains can be viewed as the execution of a "mental plan" defined as a program of schemata. There are two types of schemata: "figurative schemata" represent states and "operative schemata" represent transformations. The mental plan is divided into three main sub-components.
Case formulates his general theory with reference to developmental stages in specific domains. One of the characteristics of his theory is that it relates quantitative changes within a stage to qualitative changes between stages: for example, an increase in the active unit capacity of working memory occurs within a stage, but helps to explain the transition to the next stage. Case distinguishes activity within a stage (i.e. a "sub-stage") by first defining what he calls "basic units of thought". He then notes that during development (and probably also during skill acquisition) we have the classical four stages:
The increase in "Short Term Storage Space" (STSS) permits the transition from one sub-stage to the next. This increase is achieved within the "Total Processing Space" (TPS) which also contains the "Operating Space" (OS) utilized to control the active schema. STSS increases with age during development as a result of the maturation of the nervous system. It also increases during the learning of schemata as the result of an increase in the efficiency of the control structure: as the learner masters a task, the compilation of her knowledge frees up short term memory to hold new objectives.
There is an obvious mapping between the structure defined by Case and our intermediate framework.The control structures at each level of the pyramid integrate the control structures located at the lower level. The sequence of microworlds within the pyramid is structured as Case's view of development: quantitative variations define the improvement possible within some level (or microworld or stage) while the qualitative variations define the transition between two levels. The concept of stage transition is translated into the language shift mechanism. This transition is necessary when the learner tries to solve problems that have too high memory load constraints. After the language shift, the learner has at her disposal new control structures that enable her to solve the problems with a reduced cognitive load.
The shift from one level to another, i.e. to shift from one language to another corresponds to some qualitative jump in learning. Within each level, we defined four sub-levels that are discriminated by quantitative differences. These differences result form an increase in the difficulty of the challenges proposed by the coach. More complex challenges compel the learner to handle a larger number of dimensions and hence increase the working memory load. At the end of the second sub-level, the learner receives challenges that already belong to the next level. This shows the learner the necessity to have more powerful control structures to solve the proposed challenge (As in Case theory sub-level i.4 is equivalent to sub-level i+1.0).The "reunitarisation" of the objects used at some level in a new more powerful object frees the memory resources necessary to solve the problem.
(to be continued, most of the Case stuff should be cut....)
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