Generating Content-Compliant Training Data in Big Data Education

Robert Häusler, Daniel Staegemann, Matthias Volk, Sascha Bosse, Christian Bekel, Klaus Turowski

2020

Abstract

In order to ensure adequate education and training in a statistics-driven field, large sets of content-compliant training data (CCTD) are required. Within the context of practical orientation, such data sets should be as realistic as possible concerning the content in order to improve the learning experience. While there are different data generators for special use cases, the approaches mostly aim at evaluating the performance of database systems. Therefore, they focus on the structure but not on the content. Based on formulated requirements, this paper designs a possible approach for generating CCTD in the context of Big Data education. For this purpose, different Machine Learning algorithms could be utilized. In future work, specific models will be designed, implemented and evaluated.

Paper Citation

in Harvard Style

Häusler R., Staegemann D., Volk M., Bosse S., Bekel C. and Turowski K. (2020). Generating Content-Compliant Training Data in Big Data Education.In Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-417-6, pages 104-110. DOI: 10.5220/0009513801040110

in Bibtex Style

@conference{csedu20,
author={Robert Häusler and Daniel Staegemann and Matthias Volk and Sascha Bosse and Christian Bekel and Klaus Turowski},
title={Generating Content-Compliant Training Data in Big Data Education},
booktitle={Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2020},
pages={104-110},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009513801040110},
isbn={978-989-758-417-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Generating Content-Compliant Training Data in Big Data Education
SN - 978-989-758-417-6
AU - Häusler R.
AU - Staegemann D.
AU - Volk M.
AU - Bosse S.
AU - Bekel C.
AU - Turowski K.
PY - 2020
SP - 104
EP - 110
DO - 10.5220/0009513801040110