Εφαρμογή τεχνικών εξόρυξης δεδομένων και μηχανικής μάθησης στην πρόβλεψη της επαγγελματικής εξουθένωσης (burn-out) των εκπαιδευτικών (Master thesis)
Μπάτσιου, Αθανασία
The purpose of this study was to investigate the phenomenon of professional exhaustion
which is nowadays underlined as a syndrome concerning the teachers' community. In this
survey, 315 teachers were asked to complete the Maslach questionnaire recording the level of
professional exhaustion , as well as to answer a demographic and personal information
questionnaire. The results of this survey showed that teachers who are working in the present
post economic crisis and post Covid-19 time period while also facing increased duties due to
newly added work and self evaluation methods, are experiencing profesional exhaustion at a
15% rate. Considerably high scores were noted in the emotional exhaustion section( Section
A of the Maslach questionnaire), medium and high rates were detected in the
depersonalisation section, while scores of the personal achievement section were low. There
was a differentiation between professional exhaustion levels depending on the demographic
characteristics such as educational level ,work experience length, age of teachers, gender,
family state or number of underaged children. There was also a high percentage of teachers
willing to change their profession. Finally, a model for the prevention of professional
exhaustion was proposed . The outcomes of the present study are being put under discussion
in accord with current bibliography.
Alternative title / Subtitle: | Data mining and machine learning techniques in the prediction of teachers' burnout and attrition |
Institution and School/Department of submitter: | Σχολή Μηχανικών - Τμήμα Παραγωγής και Διοίκησης |
Subject classification: | Εκπαιδευτικοί -- Εργασιακό άγχος -- Ελλάδα Εξόρυξη δεδομένων Μηχανική μάθηση Επαγγελματική εξουθένωση (Ψυχολογία) Teachers -- Job stress -- Greece Data mining Machine learning Burn out (Psychology) |
Keywords: | Επαγγελματική εξουθένωση;Εκπαιδευτικοί;Δημογραφικά;Επάγγελμα αλλαγή;Εξόρυξη δεδομένων;Μοντέλο πρόβλεψης;Burn-Out;Educators;Demographic;Profession change;Data mining;Prevention model |
Description: | Μεταπτυχιακή εργασία - Σχολή Μηχανικών - Τμήμα Μηχανικών Παραγωγής και Διοίκησης, 2023 (α/α 13953) |
URI: | http://195.251.240.227/jspui/handle/123456789/16699 |
Appears in Collections: | Μεταπτυχιακές Διατριβές |
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File | Description | Size | Format | |
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Mpatsiou.pdf | 10.05 MB | Adobe PDF | View/Open |
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