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Knowledge Propagation and Resulting Knowledge Enhancement

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Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data

Part of the book series: Studies in Big Data ((SBD,volume 29))

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Abstract

Once we have transformed data into knowledge, we need to propagate this knowledge—so that other researchers can use and enhance this knowledge. For that, first, we need to motivate people to learn the new knowledge, we need to make sure that the idea is propagated to more and more people. To ensure that, we need to analyze the process of idea propagation; this is done in Sect. 4.1. Once a person is willing to learn the corresponding techniques and ideas, we can start the actual learning. For this learning to be successful, we need to get a good understanding of where the person stands now, what is his/her level of knowledge in the corresponding areas. This assessment problem is analyzed in Sect. 4.2. Once this information is known, we need to actually present this information to the interested folks—and use appropriate feedback to modify (if needed) the speed with which this knowledge is presented. Issues related to the material’s presentation are analyzed in Sects. 4.3 and 4.4. Specifically, in Sect. 4.3, we consider the problem from the global viewpoint: e.g., in what order we should present different parts of the material, and how much flexibility should we give to students. In Sect. 4.4, we consider this problem from the local viewpoint: what is the best way to present different items. Finally, in Sect. 4.5, we analyze the problems related to feedback.

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Authors and Affiliations

  1. Department of Computer Science, College of Engineering, The University of Texas at El Paso, El Paso, TX, USA

    L. Octavio Lerma & Vladik Kreinovich

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  1. L. Octavio Lerma
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  2. Vladik Kreinovich
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Correspondence to L. Octavio Lerma .

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Lerma, L.O., Kreinovich, V. (2018). Knowledge Propagation and Resulting Knowledge Enhancement. In: Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data. Studies in Big Data, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-61349-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-61349-9_4

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  • Online ISBN: 978-3-319-61349-9

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