A Study on the Happiness At Work of MTI Inters from the Affection and Cognition Perspective: an Ordinal Multinomial Logistic Regression Analysis with R

LI Jin & XIAO Weiqing

Foreign Language Learning Theory and Practice ›› 2024, Vol. 190 ›› Issue (4) : 82.

Foreign Language Learning Theory and Practice ›› 2024, Vol. 190 ›› Issue (4) : 82.

A Study on the Happiness At Work of MTI Inters from the Affection and Cognition Perspective: an Ordinal Multinomial Logistic Regression Analysis with R

Author information +
History +

Abstract

In the past decade, a large number of students of MTI graduated and entered the working market, however, no research has been carried out on the MTI interns happiness at work and thus it is difficult to know their real working situation. In this study, a questionnaire, on the basis of four-quadrant affects model developed by Warr and the life quality framework developed by Veenhoven, was designed and sent through So jump to MTI interns from 17 universities in 9 cities in China. An Ordinal Multinomial Logistic Regression Analysis with R is carried out and the results demonstrates that the average score of the happiness at work is a little above the center point, and the variables with significant influence are HAPA (low activated positive affects), LANA (low activated negative affects), work environment, skill, value and instant satisfaction. Further analysis reveals that the 6 variables mentioned above are related to the MTI training and translation agencies, thus corresponding improvement should be conducted to raise MTI interns happiness at work, and make them more active and loyal to the career.

Key words

cognition / affection / MTI / happiness at work / translator

Cite this article

Download Citations
LI Jin & XIAO Weiqing. A Study on the Happiness At Work of MTI Inters from the Affection and Cognition Perspective: an Ordinal Multinomial Logistic Regression Analysis with R[J]. Foreign Language Learning Theory and Practice. 2024, 190(4): 82

Accesses

Citation

Detail

Sections
Recommended

/