A data science analysis of academic staff workload profiles in spanish universities: Gender gap laid bare
Publication type
journal article
Publication date
2021
Author(s)
Cabero, I.
Epifanio, I.
Publisher
MDPI AG
Language
English
Geographical area
Abstract
This paper presents a snapshot of the distribution of time that Spanish academic staff spend on different tasks. We carry out a statistical exploratory study by analyzing the responses provided in a survey of 703 Spanish academic staff in order to draw a clear picture of the current situation. This analysis considers many factors, including primarily gender, academic ranks, age, and academic disciplines. The tasks considered are divided into smaller activities, which allows us to discover hidden patterns. Tasks are not only restricted to the academic world, but also relate to domestic chores. We address this problem from a totally new perspective by using machine learning techniques, such as cluster analysis. In order to make important decisions, policymakers must know how academic staff spend their time, especially now that legal modifications are planned for the Spanish university environment. In terms of the time spent on quality of teaching and caring tasks, we expose huge gender gaps. Non-recognized overtime is very frequent. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Journal
Education Sciences
ISSN
2227-7102
Volume
11
Issue
7
Pagination
317