Motivation of Employees that Affecting to Effectiveness of Colleges under Vocational Education, Singburi Province - Buachom, Natsanan; Kao-un, Sittiporn; Teekaporn, Tossapon (Journal for Developing the Social and Community, 2021)
This purpose of this research were; 1) to study the level of motivation for work performance of personnel and effectiveness of colleges under Vocational Education, Singburi Province, 2) to study the effectiveness of colleges under Vocational Education Singburi Province, 3) to study the relationship between and 4) to forecasting equation the effectiveness of the college from the motivation factors ‘performance in vocational college education Singburi Province. The questionnaires as a tool to collect data sample consisted of 220 peoples. The statistics used for data analysis were percentage, frequency, mean, standard deviation, Pearson’s Correlation Coefficient and Multiple Regression Analysis. The results of this study showed that; 1) the overall motivation of college personnel under Vocational Education in Singburi Province was at a moderate level, 2) the effectiveness of colleges under Vocational Education in Singburi Province. Overall, the overall level was at the moderate level, 3) the work motivation of college personnel in the vocational education department of Singburi Province as a whole had a positive relationship. The effectiveness of vocational colleges in Singburi Province were statistically significant at the .01 level with the correlation coefficient (r) at the moderate level (r = .594) and 4) the motivation of the college personnel. There are only four aspects of Vocational Education in Singburi Province, but there are only four areas that jointly predict the effectiveness of vocational colleges in Singburi Province, namely, Respect (X2), Responsibility (X4), Performance (X3), and Policy and The organization’s management (X10) with forecasting efficiency of 66.7% (R square = 0.667) was statistically significant at the .01 level and can be used to create forecasting equations as follows: Forecasting equations in raw score = .086 + .242 (X2) + .241 (X4) + .222 (X3) + .038 (X10) Forecasting equation in standard = .606 (Z2) + .501 (Z4) + .425 (Z3) + .089 (Z10)