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Gutu-Robu, Gabriel; Mihai, Darius; Dascalu, Mihai; Carabas, Mihai; Trausan-Matu, Stefan; Choi, Sunhea; Godfrey, Keith M.; Brands, Brigitte Angela und Koletzko, Berthold (2020): Cohesion Network Analysis: Customized Curriculum Management in Moodle. In: 2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (Synasc 2020): S. 175-181

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Abstract

Learning Management Systems frequently act as platforms for online content which is usually structured hierarchically into modules and lessons to ease navigation. However, the volume of information may be overwhelming, or only part of the lessons may be relevant for an individual;thus, the need for customized curricula emerges. We introduce a Moodle plugin developed to help learners customize their curriculum to best fit their learning needs by relying on specific filtering criteria and semantic relatedness. For this experiment, a Moodle instance was created for doctors working in the field of nutrition in early life. The platform includes 78 lessons tackling a wide variety of topics, organized into five modules. Our plugin enables users to specify basic filtering criteria, including their field of expertise, topics of interest from a predefined taxonomy, or expected themes (e.g., Background: knowledge, practice & counselling, or guidelines) for a preliminary pre-screening of lessons. In addition, learners can also provide a description in natural language of their learning interests. This text is compared with each lesson's description using Cohesion Network Analysis, and lessons are selected above an experimentally set threshold. Our approach also takes into account prior knowledge requirements, and may suggest lessons for further reading. Overall, the plugin covers the management of the entire course lifecycle, namely: a) creating a customized curriculum;b) tracking the progress of completed lessons;c) generating completion certificates with corresponding CME points.

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