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Lessons Learned – 15 Years of Delivering Real-World Pedagogically Driven Courses Using Experimental Platforms

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User Modeling, Adaptation and Personalization (UMAP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9146))

Abstract

Advancing research and developing innovative personalization platform whilst at the same time striving to evolve and improve learning experiences for learners, is a challenging prospect. This may be achieved through a longitudinal commitment to developing real-world educational offerings that are used in the daily delivery of learning experiences. This gives the opportunity to continuously apply methods, develop platforms and perform evaluations to realize improvements in the field of user modeling and personalization as well as improving the user experiences they support. In addition, there are specific requirements and obstacles that need to be considered like the robustness and reliability of the experimental platform in order to make this process viable and integrated both with the daily tasks of users and the core business activities of the institution. In this paper, we record our experiences in delivering real-world online courses using experimental platforms that advance personalization and user modeling techniques for over 15 years. We also describe how our research and technology, which is driven by solid pedagogical requirements, has evolved during that time in order to deliver richer learning experiences.

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Correspondence to Athanasios Staikopoulos .

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Staikopoulos, A., O’Keeffe, I., Conlan, O. (2015). Lessons Learned – 15 Years of Delivering Real-World Pedagogically Driven Courses Using Experimental Platforms. In: Ricci, F., Bontcheva, K., Conlan, O., Lawless, S. (eds) User Modeling, Adaptation and Personalization. UMAP 2015. Lecture Notes in Computer Science(), vol 9146. Springer, Cham. https://doi.org/10.1007/978-3-319-20267-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-20267-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20266-2

  • Online ISBN: 978-3-319-20267-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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