Computers are promising tools for providing educational experiences that meet individual learning needs. However, delivering this promise in practice is challenging, particularly when automated feedback is essential and the learning extends beyond using traditional methods such as writing and solving mathematics problems. We hypothesize that interactive knowledge representations can be deployed to address this challenge. Knowledge representations differ markedly from concept maps. Where the latter uses nodes (concepts) and arcs (links between concepts), a knowledge representation is based on an ontology that facilitates automated reasoning. By adjusting this reasoning towards interacting with learners for the benefit of learning, a new class of educational instruments emerges. In this contribution, we present three projects that use an interactive knowledge representation as their foundation. DynaLearn supports learners in acquiring system thinking skills. Minds-On helps learners to deepen their understanding of phenomena while performing experiments. Interactive Concept Cartoons engage learners in a science-based discussion about controversial topics. Each of these approaches has been developed iteratively in collaboration with teachers and tested in real classrooms, resulting in a suite of lessons available online. Evaluation studies involving pre-/post-tests and action-log data show that learners are easily capable of working with these educational instruments and that the instruments thus enable a semi-automated approach to constructive learning.
This paper presents three lesson activities for upper secondary education that focus on learning subject specific knowledge and general system thinking skills by creating a qualitative representation. The learning goals and the pedagogical approach are described.
We investigate a computer supported approach in which pairs co-con-struct a qualitative representation of the dynamics of the industrial revolution in a shared workspace. A key feature of this approach concerns the use of a meta-vocabulary for representing cause-and-effect relationships that facilitates the use of a predefined norm-representation to automatically steer the collaborative learning process. In particular, it provides focus on the set of ingredients that the learners should use. Additionally, the workspace offers each learner pair information about progress and content-related support. An evaluation study was executed in a real classroom. A workbook provided information for constructing the representation and gave advise on how to approach this task together. How-ever, most pairs took an alternative approach and divided their actions in the shared workspace in an unbalanced way. Three types of task division occurred that showed differences in the number of errors and the number of requests for support. From this result, we formulate future directions for the development of a pedagogical approach that stimulates collaborative learning with qualitative representations and the support offered by the software.
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