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Data Mining for Knowledge Management in Latin American Universities (2015-2019)

EasyChair Preprint 4502

16 pagesDate: November 4, 2020

Abstract

Data mining enables new information to be revealed from large amounts of data and knowledge management is a systematic process of searching, processing, filtering and teaching information to improve people's understanding of a specific area. The present work shows the main aspects addressed by research related to QA and supported by MD in Latin American Higher Education Institutions during the last five years. The studies reviewed highlight the need to develop strategies that allow educational organizations to respond to the continuous and changing demands of the environment. To this end, they all make use of knowledge management processes. Some implement knowledge management models in the organization: ACCELERA model, KMS-THU, Bordón model, while others make use of one or several knowledge management tools such as online teaching: Aguaded, podcasting, wikis or chat to improve the results of the institutions and their users. The innovation and improvement that, at an organizational and individual level, entails the implementation of knowledge management processes, provides schools with a fundamental instrument with which to promote greater organizational and school performance of each of its participants. If knowledge management processes have a positive impact on educational performance, it will ultimately favor academic success or the successful completion of the educational stages of each and every one of its students.

Keyphrases: Data Mining, Knowledge Management, University, information management

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:4502,
  author    = {Daysel Labañino Griñan and Lissette Soto Pelegrin},
  title     = {Data Mining for Knowledge Management in Latin American Universities (2015-2019)},
  howpublished = {EasyChair Preprint 4502},
  year      = {EasyChair, 2020}}
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