Abstract
The paper presents an application approach based on Big Data Value Chain concept to data collected for teachers’ demography and qualification. The proposed approach discovers and further enables to account for the teacher aging as a sensitive factor of the education process. The first step of the study ensures a reliable and holistic dataset by careful preprocessing of the raw data. Different types of data analysis have been applied in the analytical step. As the statistical analysis was not able to discover all existing relations a non-trivial approach was proposed to discover models and connections of the three main teachers’ age groups. The analysis of linked data enriches the retrieved information by getting more insight at the relation between the teachers’ groups and the municipality of the school they teach. By describing education tendencies and by modeling the significant dependencies of the teachers’ age groups the proposed approach enables to reveal information useful for policies making.
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Acknowledgement
This research work has been supported by GATE project, funded by the Horizon 2020 WIDESPREAD-2018–2020 TEAMING Phase 2 programme under grant agreement no. 857155, by the Bulgarian National Science fund under project ITDGate agreement no. DN 02/11 and by the Science Fund of Sofia University under project no. 80–10-61/13.04.2020.
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Petrova-Antonova, D., Georgieva, O. (2021). Data-Driven Insights on Secondary Education: A Case Study on Teachers’ Demography and Qualification. In: Simian, D., Stoica, L.F. (eds) Modelling and Development of Intelligent Systems. MDIS 2020. Communications in Computer and Information Science, vol 1341. Springer, Cham. https://doi.org/10.1007/978-3-030-68527-0_16
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DOI: https://doi.org/10.1007/978-3-030-68527-0_16
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