IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
Ecological theories often explain the behaviour of communities in terms of the underlying interac... more Ecological theories often explain the behaviour of communities in terms of the underlying interactions that take place between the species that are part of the community. This closely relates to the idea of compositionality within Qualitative Reasoning, in which the model that simulates the behaviour of a larger system is automatically assembled from previously defined elementary units. A recurring question however concerns the viability of this approach, particularly the scalability of such small partial descriptions. In this article we present a fully implemented model and accompanying simulations of the Ants' Garden, a complex system consisting of multiple species with multiple interactions. The Qualitative Reasoning engine automatically assembles these models by reusing a previously created library with partial models of basic processes that govern population behaviour and interactions. The simulations show the typical behaviour of the Ants' Garden as currently known and described by experts, and support the idea that our previously developed library is adequate and scalable to simulate complex system behaviour.
Modelling is seen as a learning activity in itself and qualitative modelling environments start t... more Modelling is seen as a learning activity in itself and qualitative modelling environments start to play a role in this respect. However, building (qualitative) models is not an easy task. It is therefore necessary to develop support for teachers and students. This paper describes an experience in which Artificial Intelligence (AI) undergraduate students from the University of Amsterdam and graduate ecology students from the University of Brasilia were engaged in a collaborative model building activity. The objective was to build qualitative models about the carbon cycle and the greenhouse effect in GARP.
■ Traditional approaches to ecological modeling, based on mathematical equations, are hampered by... more ■ Traditional approaches to ecological modeling, based on mathematical equations, are hampered by the qualitative nature of ecological knowledge.
Ecological knowledge has been characterised as incomplete, fuzzy, uncertain, sparse, empirical, a... more Ecological knowledge has been characterised as incomplete, fuzzy, uncertain, sparse, empirical, and non-formalised. It is often expressed in qualitative terms, verbally or diagrammatically. There is a need for new and efficient computer-based tools for making this knowledge explicit, well organised, processable, and integrated with quantitative knowledge. Qualitative reasoning is an area of artificial intelligence that creates representations for continuous aspects of the world to support reasoning with little information. Particularly relevant for our work are qualitative representations of differential equations, (in-)equality reasoning and the explicit representation of causal relationships between quantities. We present qualitative models and simulations of population and community dynamics in the Brazilian Cerrado vegetation. The models are organised in clusters of predictive simulation models.
Information and Computation/information and Control, 2006
Creating qualitative models is often considered an art rather than a scientific undertaking, lack... more Creating qualitative models is often considered an art rather than a scientific undertaking, lacking a structured methodology that supports formalisation of ideas. This hampers the already difficult process of building qualitative models. This paper presents a methodology that structures and supports the capture of conceptual knowledge about system behaviour using a qualitative approach. The framework defines a protocol for representing content that supports the development of a conceptual understanding of systems and how they behave. The methodology supports modellers in two ways. It structures and explicates the work involved in building models. It also facilitates easier comparison and evaluation of intermediate and final results of modelling efforts.
Most of water ecosystems are endangered by human actions, in spite of their importance for all li... more Most of water ecosystems are endangered by human actions, in spite of their importance for all living systems. Qualitative models and simulations may be useful for stream ecosystem recovery in many ways: for understanding such systems, to predict values of variables and to combine such understanding with restoration and proactive actions of management. This study describes the development of qualitative simulation models about the effects of pollution by organic matter and its consequences on the amount of dissolved oxygen and mortality of fishes. We present simulations of good and bad management practices, that may result in increasing and reducing fish stocks. Problems we found and solutions we implemented during the modelling effort are discussed, including the explicit representation of assumptions and the role of ambiguities in the outcomes of the models. We argue that new ontologies and qualitative domain theories will be required in order to tackle processes are related to both energy flow and nutrient cycling and to represent complex interactions between physical, chemical and biological phenomena.
Representing the impact of external factors on the behaviour of a system is a challenge for model... more Representing the impact of external factors on the behaviour of a system is a challenge for modellers, particularly when these factors are dynamic and may change during the simulation. This article presents mechanisms implemented in the qualitative reasoning engine Garp3 for modelling quantities that exhibit exogenously defined behaviours. Exogenous quantities are those that influence the system but are not influenced by quantities represented in the system. Seven types of mechanisms for handling exogenous quantities are implemented: "constant", "generate all values", "increasing", "decreasing", "steady", "sinusoidal", and "random". Examples drawn from models of environmental sustainability (related to Millennium Development Goal 7) are used to illustrate the functioning of these primitives. Individually or combined, the mechanisms provide many options for modellers to represent cycles, oscillations, and regions of local stability.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
... Amsterdam, IOS Press, pp. 294-305. ... Translation of Basic Ecology, 1983. 6. Paulo Salles , ... more ... Amsterdam, IOS Press, pp. 294-305. ... Translation of Basic Ecology, 1983. 6. Paulo Salles , Bert Bredeweg , Symone Araujo , Walter Neto, Qualitative models of interactions between two populations, AI Communications, v.16 n.4, p.291-308, December 2003. ...
Successful transfer and uptake of qualitative reasoning technology for modelling and simulation i... more Successful transfer and uptake of qualitative reasoning technology for modelling and simulation in a variety of domains has been hampered by the lack of a structured methodology to support formalisation of ideas. We present a framework that structures and supports the capture of ...
This paper describes the DynaLearn project, which seeks to address contemporary problems in scien... more This paper describes the DynaLearn project, which seeks to address contemporary problems in science education by integrating well established, but currently independent technological developments, and utilize the added value that emerges. Specifically, diagrammatic representations are used for learners to articulate, analyse and communicate ideas, and thereby construct their conceptual knowledge. Ontology mapping is used to find and match co-learners working on similar ideas to provide individualised and mutually benefiting learning opportunities. Virtual characters are used to make the interaction engaging and motivating. The development of the workbench is tuned to fit key topics from environmental science curricula, and evaluated and further improved in the context of existing curricula using case studies. Through this approach, the DynaLearn project will deliver an individualised and engaging cognitive tool for acquiring conceptual knowledge that fits the true nature of this expertise.
Brazilian educational system is faced with the task of integrating deafs along with non-deafs in ... more Brazilian educational system is faced with the task of integrating deafs along with non-deafs in the classroom. A requirement of a bilingual education arises, with the Brazilian Sign Language as the native language and Portuguese as the second language. Qualitative Reasoning may provide tools to support Portuguese acquisition while developing scientific concepts. This study describes an experiment with eight deaf students being exposed to three qualitative models. Five students were successful in exploring causal relations and in writing up a composition about an ecological accident. The results encourage us to explore the potential of qualitative models in second language acquisition.
Negative and positive interactions between populations such as competition, predator-prey and sym... more Negative and positive interactions between populations such as competition, predator-prey and symbiosis, under the influence of environmental factors, have been pointed out as the main organising forces of communities. Due to explicit representation of knowledge and of causal relations, qualitative simulations can be useful for students to have insights on structure and behaviour of interacting populations. Our work is based on a library of model fragments representing basic population processes (such as natality and mortality), so that it is possible to derive complex community behaviour from ‘first principles’ [1]. Six types of interactions were modelled: neutralism (0,0), amensalism (0,−), commensalism (0,+), predator-prey (+,−), symbiosis (+,+) and competition (−,−). The symbols −, +, 0 represent, respectively, negative, positive or no effects from the other species. We define a ‘basic interaction model’, in which population1 produces some effect (effect1on2) that affects natality (born2) and mortality (dead2) of population2, while this one has an effect (effect2on1) which influences born1 and dead1. These influences may be positive or negative, according to the interaction type. For instance, in the predator-prey model effect1on2 has a positive influence on dead2 (increases mortality of prey) and effect2on1 has a negative influence on dead1 (decreases mortality of predator). Simulations with these models show typical behaviour of each interaction type, such as coexistence and competitive exclusion. The simulation models are organised according to educational learning routes, following the general scheme discussed in [2].
The dynamics of the dissolved oxygen in water bodies is the result of complex interactions involv... more The dynamics of the dissolved oxygen in water bodies is the result of complex interactions involving physical and biological processes. Understanding how the balance of these influences determines the amount of oxygen available for living organisms is a key factor to interpret the water body conditions, and eventually to use dissolved oxygen as an indicator of the water quality. In
Abstract: Building qualitative models is a difficult task. The construction of re-usablemodels, a... more Abstract: Building qualitative models is a difficult task. The construction of re-usablemodels, as well as the formalisation of the modelling process itself, are goalsboth to researchers in qualitative reasoning and ecology. This paper presentsa library of model fragments for reasoning about the behaviour of ecologicalcommunities. We have developed a kernel of partial models that representsgeneral knowledge about populations, which can
Most of water ecosystems are endangered by human actions, in spite of their importance for all li... more Most of water ecosystems are endangered by human actions, in spite of their importance for all living systems. Qualitative models and simulations may be useful for stream ecosystem recovery in many ways: for understanding such systems, to predict values of variables and to combine such understanding with restoration and proactive actions of management. This study describes the development of qualitative simulation models about the effects of pollution by organic matter and its consequences on the amount of dissolved oxygen and mortality of fishes. We present simulations of good and bad management practices, that may result in increasing and reducing fish stocks. Problems we found and solutions we implemented during the modelling effort are discussed, including the explicit representation of assumptions and the role of ambiguities in the outcomes of the models. We argue that new ontologies and qualitative domain theories will be required in order to tackle processes are related to both energy flow and nutrient cycling and to represent complex interactions between physical, chemical and biological phenomena.
Qualitative computer simulations have great potential for teaching people to understand and inter... more Qualitative computer simulations have great potential for teaching people to understand and interact with their physical environment. Prerequisite for using that potential, is that these simulations can be explained to humans in ways that they comprehend. Preferably, these explanations should be generated on the basis of the qualitative models that underly the simulations, to avoid having to handcraft the explanations for every new domain. The research that we describe in this paper deals with exactly that problem. It combines two lines of earlier research: representing qualitative models, GARP [2], and didactic discourse planning, DDP . All qualitative models represented in GARP can be questioned by students, using an as yet limited set of questions, that will be answered by a generic didactic discourse planner. The overall interaction between students and systems is guided by a 'mental tour' through the successive states of the simulation (the 'envisionment graph'). At each state several questions can be asked. These questions are linked to 'information needs', the topics of discourse. On the basis of these topics, the discourse planner will plan sequences of utterances, taking into account such things as the students beliefs, and the state of the discourse process.
Qualitative models support interactive simulations that are well suited to help learners in acqui... more Qualitative models support interactive simulations that are well suited to help learners in acquiring causal interpretations of physical systems and their behavior. Such simulation models can be large, particularly if they include many subsystems. When simulations are too big they hardly can be used effectively for teaching purposes. They have to be reorganized into smaller sets of simulation models and ordered in a sequence for the learner to progress through. Model-dimensions and techniques such as Causal Model Progression have been presented as means to address this problem. In this paper we investigate how to decompose a large qualitative simulation into a progressive sequence of smaller simulations, useful for teaching purposes, in the domain of ecology. Based on notions introduced by Causal Model Progression, the Genetic Graph, and the Didactic Goal Generator, we have constructed a set of dimensions that can be used in this respect. Following these dimensions we show how a large qualitative simulation model of the Brazilian Cerrado vegetation dynamics can be rearranged into a sequence of clusters, each representing and simulating distinct features of such ecological systems. These clusters are ordered in evolutionary model progression lines according to movements from static to dynamic models and, by incorporating structural changes, from less complex to more complex models. The approach presented in this paper thus provides means, in terms of knowledge characteristics, to effectively reorganize qualitative simulation models for teaching purposes. In the discussion we briefly argue that this approach may also be applicable to qualitative simulation in other domains.
This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects i... more This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects in the Danube Delta Biosphere Reserve (DDBR) in Romania. Qualitative Reasoning models represent processes and their cause–effect relationships in a flexible and conceptually rich manner and as such can be used as instruments for capturing and sharing explanations of how systems behave. The DDBR model
Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in ... more Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in a discovery-oriented learning environment. This paper discusses a set of knowledge representations referred to as Learning Spaces (LSs) that can be used to support learners in acquiring conceptual knowledge of system behaviour. The LSs are logically self-contained, meaning that models created at a specific LS can be simulated. Working with the LSs provides scaffolding for learners in two ways. First, each LS provides a restricted set of representational primitives to express knowledge, which focus the learner’s knowledge construction process. Second, the logical consequences of an expression derived upon simulating, provide learners a reflective instrument for evaluating the status of their understanding, to which they can react accordingly. The work presented here is part of the DynaLearn project, which builds an Interactive Learning Environment to study a constructive approach to having learners develop a qualitative understanding of how systems behave. The work presented here thus focuses on tools to support educational research. Consequently, user-oriented evaluation of these tools is not a part of this paper.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
Ecological theories often explain the behaviour of communities in terms of the underlying interac... more Ecological theories often explain the behaviour of communities in terms of the underlying interactions that take place between the species that are part of the community. This closely relates to the idea of compositionality within Qualitative Reasoning, in which the model that simulates the behaviour of a larger system is automatically assembled from previously defined elementary units. A recurring question however concerns the viability of this approach, particularly the scalability of such small partial descriptions. In this article we present a fully implemented model and accompanying simulations of the Ants' Garden, a complex system consisting of multiple species with multiple interactions. The Qualitative Reasoning engine automatically assembles these models by reusing a previously created library with partial models of basic processes that govern population behaviour and interactions. The simulations show the typical behaviour of the Ants' Garden as currently known and described by experts, and support the idea that our previously developed library is adequate and scalable to simulate complex system behaviour.
Modelling is seen as a learning activity in itself and qualitative modelling environments start t... more Modelling is seen as a learning activity in itself and qualitative modelling environments start to play a role in this respect. However, building (qualitative) models is not an easy task. It is therefore necessary to develop support for teachers and students. This paper describes an experience in which Artificial Intelligence (AI) undergraduate students from the University of Amsterdam and graduate ecology students from the University of Brasilia were engaged in a collaborative model building activity. The objective was to build qualitative models about the carbon cycle and the greenhouse effect in GARP.
■ Traditional approaches to ecological modeling, based on mathematical equations, are hampered by... more ■ Traditional approaches to ecological modeling, based on mathematical equations, are hampered by the qualitative nature of ecological knowledge.
Ecological knowledge has been characterised as incomplete, fuzzy, uncertain, sparse, empirical, a... more Ecological knowledge has been characterised as incomplete, fuzzy, uncertain, sparse, empirical, and non-formalised. It is often expressed in qualitative terms, verbally or diagrammatically. There is a need for new and efficient computer-based tools for making this knowledge explicit, well organised, processable, and integrated with quantitative knowledge. Qualitative reasoning is an area of artificial intelligence that creates representations for continuous aspects of the world to support reasoning with little information. Particularly relevant for our work are qualitative representations of differential equations, (in-)equality reasoning and the explicit representation of causal relationships between quantities. We present qualitative models and simulations of population and community dynamics in the Brazilian Cerrado vegetation. The models are organised in clusters of predictive simulation models.
Information and Computation/information and Control, 2006
Creating qualitative models is often considered an art rather than a scientific undertaking, lack... more Creating qualitative models is often considered an art rather than a scientific undertaking, lacking a structured methodology that supports formalisation of ideas. This hampers the already difficult process of building qualitative models. This paper presents a methodology that structures and supports the capture of conceptual knowledge about system behaviour using a qualitative approach. The framework defines a protocol for representing content that supports the development of a conceptual understanding of systems and how they behave. The methodology supports modellers in two ways. It structures and explicates the work involved in building models. It also facilitates easier comparison and evaluation of intermediate and final results of modelling efforts.
Most of water ecosystems are endangered by human actions, in spite of their importance for all li... more Most of water ecosystems are endangered by human actions, in spite of their importance for all living systems. Qualitative models and simulations may be useful for stream ecosystem recovery in many ways: for understanding such systems, to predict values of variables and to combine such understanding with restoration and proactive actions of management. This study describes the development of qualitative simulation models about the effects of pollution by organic matter and its consequences on the amount of dissolved oxygen and mortality of fishes. We present simulations of good and bad management practices, that may result in increasing and reducing fish stocks. Problems we found and solutions we implemented during the modelling effort are discussed, including the explicit representation of assumptions and the role of ambiguities in the outcomes of the models. We argue that new ontologies and qualitative domain theories will be required in order to tackle processes are related to both energy flow and nutrient cycling and to represent complex interactions between physical, chemical and biological phenomena.
Representing the impact of external factors on the behaviour of a system is a challenge for model... more Representing the impact of external factors on the behaviour of a system is a challenge for modellers, particularly when these factors are dynamic and may change during the simulation. This article presents mechanisms implemented in the qualitative reasoning engine Garp3 for modelling quantities that exhibit exogenously defined behaviours. Exogenous quantities are those that influence the system but are not influenced by quantities represented in the system. Seven types of mechanisms for handling exogenous quantities are implemented: "constant", "generate all values", "increasing", "decreasing", "steady", "sinusoidal", and "random". Examples drawn from models of environmental sustainability (related to Millennium Development Goal 7) are used to illustrate the functioning of these primitives. Individually or combined, the mechanisms provide many options for modellers to represent cycles, oscillations, and regions of local stability.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
... Amsterdam, IOS Press, pp. 294-305. ... Translation of Basic Ecology, 1983. 6. Paulo Salles , ... more ... Amsterdam, IOS Press, pp. 294-305. ... Translation of Basic Ecology, 1983. 6. Paulo Salles , Bert Bredeweg , Symone Araujo , Walter Neto, Qualitative models of interactions between two populations, AI Communications, v.16 n.4, p.291-308, December 2003. ...
Successful transfer and uptake of qualitative reasoning technology for modelling and simulation i... more Successful transfer and uptake of qualitative reasoning technology for modelling and simulation in a variety of domains has been hampered by the lack of a structured methodology to support formalisation of ideas. We present a framework that structures and supports the capture of ...
This paper describes the DynaLearn project, which seeks to address contemporary problems in scien... more This paper describes the DynaLearn project, which seeks to address contemporary problems in science education by integrating well established, but currently independent technological developments, and utilize the added value that emerges. Specifically, diagrammatic representations are used for learners to articulate, analyse and communicate ideas, and thereby construct their conceptual knowledge. Ontology mapping is used to find and match co-learners working on similar ideas to provide individualised and mutually benefiting learning opportunities. Virtual characters are used to make the interaction engaging and motivating. The development of the workbench is tuned to fit key topics from environmental science curricula, and evaluated and further improved in the context of existing curricula using case studies. Through this approach, the DynaLearn project will deliver an individualised and engaging cognitive tool for acquiring conceptual knowledge that fits the true nature of this expertise.
Brazilian educational system is faced with the task of integrating deafs along with non-deafs in ... more Brazilian educational system is faced with the task of integrating deafs along with non-deafs in the classroom. A requirement of a bilingual education arises, with the Brazilian Sign Language as the native language and Portuguese as the second language. Qualitative Reasoning may provide tools to support Portuguese acquisition while developing scientific concepts. This study describes an experiment with eight deaf students being exposed to three qualitative models. Five students were successful in exploring causal relations and in writing up a composition about an ecological accident. The results encourage us to explore the potential of qualitative models in second language acquisition.
Negative and positive interactions between populations such as competition, predator-prey and sym... more Negative and positive interactions between populations such as competition, predator-prey and symbiosis, under the influence of environmental factors, have been pointed out as the main organising forces of communities. Due to explicit representation of knowledge and of causal relations, qualitative simulations can be useful for students to have insights on structure and behaviour of interacting populations. Our work is based on a library of model fragments representing basic population processes (such as natality and mortality), so that it is possible to derive complex community behaviour from ‘first principles’ [1]. Six types of interactions were modelled: neutralism (0,0), amensalism (0,−), commensalism (0,+), predator-prey (+,−), symbiosis (+,+) and competition (−,−). The symbols −, +, 0 represent, respectively, negative, positive or no effects from the other species. We define a ‘basic interaction model’, in which population1 produces some effect (effect1on2) that affects natality (born2) and mortality (dead2) of population2, while this one has an effect (effect2on1) which influences born1 and dead1. These influences may be positive or negative, according to the interaction type. For instance, in the predator-prey model effect1on2 has a positive influence on dead2 (increases mortality of prey) and effect2on1 has a negative influence on dead1 (decreases mortality of predator). Simulations with these models show typical behaviour of each interaction type, such as coexistence and competitive exclusion. The simulation models are organised according to educational learning routes, following the general scheme discussed in [2].
The dynamics of the dissolved oxygen in water bodies is the result of complex interactions involv... more The dynamics of the dissolved oxygen in water bodies is the result of complex interactions involving physical and biological processes. Understanding how the balance of these influences determines the amount of oxygen available for living organisms is a key factor to interpret the water body conditions, and eventually to use dissolved oxygen as an indicator of the water quality. In
Abstract: Building qualitative models is a difficult task. The construction of re-usablemodels, a... more Abstract: Building qualitative models is a difficult task. The construction of re-usablemodels, as well as the formalisation of the modelling process itself, are goalsboth to researchers in qualitative reasoning and ecology. This paper presentsa library of model fragments for reasoning about the behaviour of ecologicalcommunities. We have developed a kernel of partial models that representsgeneral knowledge about populations, which can
Most of water ecosystems are endangered by human actions, in spite of their importance for all li... more Most of water ecosystems are endangered by human actions, in spite of their importance for all living systems. Qualitative models and simulations may be useful for stream ecosystem recovery in many ways: for understanding such systems, to predict values of variables and to combine such understanding with restoration and proactive actions of management. This study describes the development of qualitative simulation models about the effects of pollution by organic matter and its consequences on the amount of dissolved oxygen and mortality of fishes. We present simulations of good and bad management practices, that may result in increasing and reducing fish stocks. Problems we found and solutions we implemented during the modelling effort are discussed, including the explicit representation of assumptions and the role of ambiguities in the outcomes of the models. We argue that new ontologies and qualitative domain theories will be required in order to tackle processes are related to both energy flow and nutrient cycling and to represent complex interactions between physical, chemical and biological phenomena.
Qualitative computer simulations have great potential for teaching people to understand and inter... more Qualitative computer simulations have great potential for teaching people to understand and interact with their physical environment. Prerequisite for using that potential, is that these simulations can be explained to humans in ways that they comprehend. Preferably, these explanations should be generated on the basis of the qualitative models that underly the simulations, to avoid having to handcraft the explanations for every new domain. The research that we describe in this paper deals with exactly that problem. It combines two lines of earlier research: representing qualitative models, GARP [2], and didactic discourse planning, DDP . All qualitative models represented in GARP can be questioned by students, using an as yet limited set of questions, that will be answered by a generic didactic discourse planner. The overall interaction between students and systems is guided by a 'mental tour' through the successive states of the simulation (the 'envisionment graph'). At each state several questions can be asked. These questions are linked to 'information needs', the topics of discourse. On the basis of these topics, the discourse planner will plan sequences of utterances, taking into account such things as the students beliefs, and the state of the discourse process.
Qualitative models support interactive simulations that are well suited to help learners in acqui... more Qualitative models support interactive simulations that are well suited to help learners in acquiring causal interpretations of physical systems and their behavior. Such simulation models can be large, particularly if they include many subsystems. When simulations are too big they hardly can be used effectively for teaching purposes. They have to be reorganized into smaller sets of simulation models and ordered in a sequence for the learner to progress through. Model-dimensions and techniques such as Causal Model Progression have been presented as means to address this problem. In this paper we investigate how to decompose a large qualitative simulation into a progressive sequence of smaller simulations, useful for teaching purposes, in the domain of ecology. Based on notions introduced by Causal Model Progression, the Genetic Graph, and the Didactic Goal Generator, we have constructed a set of dimensions that can be used in this respect. Following these dimensions we show how a large qualitative simulation model of the Brazilian Cerrado vegetation dynamics can be rearranged into a sequence of clusters, each representing and simulating distinct features of such ecological systems. These clusters are ordered in evolutionary model progression lines according to movements from static to dynamic models and, by incorporating structural changes, from less complex to more complex models. The approach presented in this paper thus provides means, in terms of knowledge characteristics, to effectively reorganize qualitative simulation models for teaching purposes. In the discussion we briefly argue that this approach may also be applicable to qualitative simulation in other domains.
This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects i... more This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects in the Danube Delta Biosphere Reserve (DDBR) in Romania. Qualitative Reasoning models represent processes and their cause–effect relationships in a flexible and conceptually rich manner and as such can be used as instruments for capturing and sharing explanations of how systems behave. The DDBR model
Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in ... more Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in a discovery-oriented learning environment. This paper discusses a set of knowledge representations referred to as Learning Spaces (LSs) that can be used to support learners in acquiring conceptual knowledge of system behaviour. The LSs are logically self-contained, meaning that models created at a specific LS can be simulated. Working with the LSs provides scaffolding for learners in two ways. First, each LS provides a restricted set of representational primitives to express knowledge, which focus the learner’s knowledge construction process. Second, the logical consequences of an expression derived upon simulating, provide learners a reflective instrument for evaluating the status of their understanding, to which they can react accordingly. The work presented here is part of the DynaLearn project, which builds an Interactive Learning Environment to study a constructive approach to having learners develop a qualitative understanding of how systems behave. The work presented here thus focuses on tools to support educational research. Consequently, user-oriented evaluation of these tools is not a part of this paper.
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Papers by Paulo Salles