Elaborating the Context Calculator: A Design Experiment in Geothermy

Abstract : This paper presents a research project in science education that is positioned at the intersection of computer science and context in learning. The main objective is to improve learning process by creating a software tool that participates, from the inception to the achievement, in the design of leaning scenarios, based on context effects, and, to show that context effects' learning is an efficient method in the development of student's knowledge regarding a concept. The software will compute differences between two – or more – external contexts based on specific parameters, related to the phenomenon or object that students are expected to study. The elaboration of the calculator (" the MazCalc ") is conducted using the design based research theory, meaning that several iterations of learning field experiments are conducted in order to collect relevant data which are used for the tool creation. In this paper, the design of the scenario involves students from North America and from the French West Indies and the concept studied is about geothermal energy. The instantiation of the context calculator is made with the geothermal object of study, and the differences are computed in the calculator between the two contexts mentioned. This example makes possible to validate the link between context effects predicted and observed, and also to study the impact of external context on the learning process. This study has been conducted thanks to the GEOTREF project support.
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Springer; Patrick Brézillon, Roy Turner, Carlo Penco. Modeling and Using Context, 10257, pp.513-526, 2017, Lecture Notes in Artificial Intelligence 978-3-319-57837-8. 〈10.1007/978-3-319-57837-8_42〉
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Claire Anjou, Thomas Forissier, Jacqueline Bourdeau, Yves Mazabraud, Roger Nkambou, et al.. Elaborating the Context Calculator: A Design Experiment in Geothermy. Springer; Patrick Brézillon, Roy Turner, Carlo Penco. Modeling and Using Context, 10257, pp.513-526, 2017, Lecture Notes in Artificial Intelligence 978-3-319-57837-8. 〈10.1007/978-3-319-57837-8_42〉. 〈hal-01625781〉

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