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Evaluation of Well-Being of Maritime Students: An Application of Dokuz Eylül University

2024· article· en· W7132378049 sur OpenAlexaboutno aff
Elif Türkan Arslan, Ömer Emre Arslan

Notice bibliographique

RevueÇanakkale Onsekiz Mart University AVESIS · 2024
Typearticle
Langueen
DomaineEngineering
ThématiqueMaritime Navigation and Safety
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHappinessQuarter (Canadian coin)Work (physics)OfficerMeaning (existential)Value (mathematics)Affect (linguistics)Life style
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

<span style="color: rgb(119, 119, 119); font-family: &quot;Open Sans&quot;, Arial, sans-serif; font-size: 14px;">Seafarers, who are a crucial element of world trade, work under many challenging conditions. Many adverse conditions such as exposure to hazardous cargoes, intensive work under long working hours, being away from their families, and working in environments with noise and vibration affect the health of seafarers both physically and mentally. Well-being, which depends on the personal evaluations that people experience in their lives, can vary depending on many judgments, and emotions such as life satisfaction, responsibilities, health, work, entertainment, and relationships. The "Seafarers Happiness Index" for 2023 showed a decline from 7.12 in the first quarter to 6.36 in the last. In the last quarter data of 2023, it is seen that the catering department is the happiest rank with a value of 7.1 among 14 ranks, while the deck and engine cadets have the 3rd and 4th lowest values. Therefore, this study aims to assess the well-being of cadets, who represent the initial stage in officer formation. The students studying at the departments of Marine Transportation Engineering (MET) and Marine Engineering (ME) of Dokuz Eylul University Maritime Faculty were chosen as the sample. The PERMA-Profiler questionnaire, which consists of 23 questions and measures well-being with the dimensions of Positive Emotion (P), Engagement (E), Relationship (R), Meaning (M), and Accomplishment (A), was applied to the participants via Google Forms. After data cleaning, 164 students were included in the analysis. The Independent Samples T-test, ANOVA, and correlation tests were applied since all sub-dimensions of the well-being scale remained within the ±1.5 boundaries of normality. The statistics were formed based on gender (female/male), department (MET/ME), and internship duration (junior/senior). When the analyses are examined, it is seen that female students feel more loneliness than male students. According to the departments, there is a significant difference in all dimensions except the relationship dimension and overall well-being (OWB) score. ME students had higher mean scores in all dimensions. There is a strong, positive relationship between OWB and P, M, E, A, and R dimensions respectively. There is no significant relationship between students' grade point averages and their well-being. It was observed that senior group students had higher averages than junior group students in all dimensions except the engagement dimension and in the OWB score. Additionally in the questionnaire, students were asked an open-ended question about the situations that affect their well-being positively/negatively. When the responses were grouped within themselves, social environment/friendly relations, academic/professional success, engaging in hobbies, economic conditions, and family relations were the most recurring factors, respectively. In this study, the well-being of maritime students holds great importance in connection with the fact that a large portion of accidents at sea are attributed to human factors. It represents a critical step towards determining the psychological and social supports required for ship safety and efficiency.</span>

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,667
Score d'incertitude au seuil0,586

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,008
Tête enseignante GPT0,227
Écart entre enseignants0,219 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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