22,021 research outputs found
Design and evaluation of a case-based system for modelling exploratory learning behaviour of math generalisation
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore
models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a
variety of learner approaches for constructing models and makes modelling of learner behaviour a challenging task. To address this
issue, we propose a learner modelling mechanism for monitoring learners’ actions when constructing/exploring models by modelling
sequences of actions reflecting different strategies in solving a task. This is based on a modified version of case-based reasoning for
problems with multiple solutions. In our formulation, approaches to explore the task are represented as sequences of simple cases
linked by temporal and dependency relations, which are mapped to the learners’ behaviour in the system by means of appropriate
similarity metrics. This paper presents the development and validation of the modelling mechanism. The model was validated in the
context of an ELE for mathematical generalisation using data from classroom sessions and pedagogically-driven learning scenarios
Genisa: A web-based interactive learning environment for teaching simulation modelling
Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction
Participatory learner modelling design: a methodology for iterative learner models development
Learner models are built to offer personalised solutions related to learning. They are often
developed in parallel to the development of adaptive learning systems and thus, linked to
the system’s development. The adaptive learning systems literature reports numerous
accounts of learner model development, but there are no reports on the methodological
aspects of developing learner models and the relation between the development of the
learner model component and the rest of the system. This paper presents the
Participatory Learner Modelling Design methodology, which outlines the steps for learner
model development and their relation to the development of the system. The methodology
is illustrated with a case study of an adaptive educational system
Exploring pathways for sustainable water management in river deltas in a changing environment
Exploring adaptation pathways into an uncertain future can support decisionmaking in achieving sustainable water management in a changing environment. Our objective is to develop and test a method to identify such pathways by including dynamics from natural variability and the interaction between the water system and society. Present planning studies on long-term water management often use a few plausible futures for one or two projection years, ignoring the dynamic aspect of adaptation through the interaction between the water system and society. Our approach is to explore pathways using multiple realisations of transient scenarios with an Integrated Assessment Meta Model (IAMM). This paper presents the first application of the method using a hypothetical case study. The case study shows how to explore and evaluate adaptation pathways. With the pathways it is possible to identify opportunities, threats, timing and sequence of policy options, which can be used by policymakers to develop water management roadmaps into the future. By including the dynamics between the water system and society, the influence of uncertainties in both systems becomes clearer. The results show, among others, that climate variability rather than climate change appears to be important for taking decisions in water management
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