Predicting the Job Performance of Physical Education Faculty Members in Practical Courses Based on Psychological Well-Being Components

As valuable capitals of the society, the faculty members play a very sensitive and valuable role in the training of specialized individuals, and their job performance is one of the basic indicators of success and continuation of educational goals in higher education; therefore, the current research was carried out with the aim of predicting The Job Performance of Physical Education faculty members in teaching practical courses based on psychological well-being components, which was carried out by descriptive-correlation method. The statistical population of the research was formed by the members of the physical education faculty, which was estimated by considering the unlimited statistical population of 384 statistical samples. The statistical sample was selected using available sampling method. The measuring instrument of the research was a questionnaire, the validity of which was checked and confirmed through the opinion of experts and reliability through Cronbach's alpha coefficient. Stepwise regression was used to determine the power of predicting job performance based on psychological well-being components. The findings of the research showed that among the components of psychological well-being, the components of Environmental mastery, Positive relationships with others, personal growth and self-acceptance have the possibility of predicting the job performance of professors.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.22108/jhs.2023.137655.1026
Primary Topic
Head and Neck Surgical Oncology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting the Job Performance of Physical Education Faculty Members in Practical Courses Based on Psychological Well-Being Components

SHILAP Revista de lepidopterología
Head and Neck Surgical Oncology
article

Predicting the Job Performance of Physical Education Faculty Members in Practical Courses Based on Psychological Well-Being Components

article en

Abstract

As valuable capitals of the society, the faculty members play a very sensitive and valuable role in the training of specialized individuals, and their job performance is one of the basic indicators of success and continuation of educational goals in higher education; therefore, the current research was carried out with the aim of predicting The Job Performance of Physical Education faculty members in teaching practical courses based on psychological well-being components, which was carried out by descriptive-correlation method. The statistical population of the research was formed by the members of the physical education faculty, which was estimated by considering the unlimited statistical population of 384 statistical samples. The statistical sample was selected using available sampling method. The measuring instrument of the research was a questionnaire, the validity of which was checked and confirmed through the opinion of experts and reliability through Cronbach's alpha coefficient. Stepwise regression was used to determine the power of predicting job performance based on psychological well-being components. The findings of the research showed that among the components of psychological well-being, the components of Environmental mastery, Positive relationships with others, personal growth and self-acceptance have the possibility of predicting the job performance of professors.

SHILAP Revista de lepidopterología
Decent work and economic growth
Openalex Percentile: Top 40%
Head and Neck Surgical Oncology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.