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Heinrich, B., Hristova, B., Klier, M., Schiller, A. and Szubartowicz, M. (2018) Requirements for Data Quality Metrics. Journal of Data and Information Quality, 9, Article No. 12, 32 p.
https://doi.org/10.1145/3148238

has been cited by the following article:

• TITLE: A Quality Assurance Reference Framework for Assessing Educational Data

  AUTHORS: Antonia Stefani, Bill Vassiliadis

  KEYWORDS: Quality Assurance Framework, Data Model, Digital Educational Content, ISO25000 Series

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.9 No.4, November 30, 2021

  ABSTRACT: Digital educational content is gaining importance as an incubator of pedagogical methodologies in formal and informal online educational settings. Its educational efficiency is directly dependent on its quality, however educational content is more than information and data. This paper presents a new data quality framework for assessing digital educational content used for teaching in distance learning environments. The model relies on the ISO2500 series quality standard and beside providing the mechanisms for multi-facet quality assessment it also supports organizations that design, create, manage and use educational content with the quality tools (expressed as quality metrics and measurement methods) to provide a more efficient distance education experience. The model describes the quality characteristics of the educational material content using data and software quality characteristics.