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  • 标题:iKeyCriteria: A Qualitative and Quantitative Analysis Method to Infer Key Criteria since a Systematic Literature Review for the Computing Domain
  • 本地全文:下载
  • 作者:Mayra Carrión-Toro ; Jose Aguilar ; Marco Santórum
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2022
  • 卷号:7
  • 期号:6
  • 页码:1-21
  • DOI:10.3390/data7060070
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:A systematic literature review is a synthesis of the available evidence, in which a reviewof quantitative and qualitative aspects of primary studies is carried out, to summarize the existinginformation regarding a particular topic. The researchers extract key criteria from papers collectedabout their study area, answering research questions and conducting document analysis. Nonetheless,in some cases, these criteria are improperly justified, unknowing their true level of importancein the study subject. Hence, an additional study is necessary to explain the criteria relevancein the papers studied using qualitative and quantitative premises. The correct identification of thesekey criteria is a critical factor in prioritizing and achieving appropriate results in any scientificresearch work. In our paper, a new method to determine key criteria from a literature reviewis proposed, composed of three components: input-process-output. First, the inputs are a setof criteria to evaluate and a set of documents to analyze. Next, the process component examinesthe document set to indicate whether the criteria to be analyzed are found. The process componentproduces a Boolean matrix, which is the input of the mathematical logic process that will get the keycriteria considered necessary and sufficient as the output component. The iKeyCriteria method hasbeen applied in different computing domains, particularly for serious games design and virtualorganizations, giving positive results in each context. Finally, we developed an online tool thatprovides global support to the execution of our method.
  • 关键词:data;information retrieval;systematic literature review;key criteria;meta-analysis
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