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Articles by Sombat Tayraukham
Total Records ( 5 ) for Sombat Tayraukham
  Rachapoom Pangma , Sombat Tayraukham and Prasart Nuangchalerm
  Problem statement: The aim of this research was to study the causal factors influencing students’ adversity between twelfth grade and third-year vocational students in Sisaket province, Thailand. Six hundred and seventy two of twelfth grade and 376 third-year vocational students were selected by multi-stage random sampling techniques. Approach: The instruments used for collecting data were: A scale on self-esteem, a scale on dominance, a scale on self-confidence, a scale on sense of personal freedom, a scale on achievement motivation, a scale on ambition, a scale on enthusiasm, a scale on responsibility, a scale on future orientation, and an adversity quotient scale. The data were analyzed by validity test of the causal relationship model. Results: The results of the study were as follows: (1) variables influencing the adversity quotient of 12th grade and third-year vocational students were dominance, sense of personal freedom, self-esteem, enthusiasm, self-confidence, ambition and achievement motivation. (2) Variables are directly influencing the adversity quotient of twelfth grade students was self-confidence while the variables both directly and indirectly influencing the adversity quotient of students were dominance, sense of personal freedom, self-esteem, and enthusiasm. (3) Variable are directly influencing adversity quotient of third-year vocational students was achievement motivation, the variables are indirectly influencing the adversity quotient of these students was dominance while the variables both directly and indirectly influencing the adversity quotient of these students were sense of personal freedom, self-esteem, enthusiasm, self-confidence, and ambition. Conclusion: In conclusion, the results of this study could be used as beneficial information for parents, teachers and those involved in education for developing students to have adversity quotient as well as to be used as guidelines for providing education in the future.
  Rungrawee Siribunnam and Sombat Tayraukham
  Problem statement: The purposes of this research were to compare in analytical thinking, science learning achievement and attitudes toward chemistry learning of Matthayomsuksa 5 students who learned using the 7-E learning cycle, KWL learning method and conventional approach. Approach: The sample consisted of 154 Matthayomsuksa 5 students attending in the first semester of the academic year 2008, Phayakkhaphumwitthayakhan School, Phayakkhaphumphisai District, Mahasarakham Province, cluster random sampling technique was employed. The were divided into two experimental groups who learned using the 7-E learning cycle and KWL learning activities and one control group who learned using the conventional approach. Results: The research instruments were: (1) 12 lesson plans for organization of 7-E learning cycle, 12 lesson plans for organization of KWL learning method and 12 lesson plans for organization of the conventional approach; (2) A 30-item analytical thinking test; (3) A 40-item achievement test of science learning achievement and (4) A 20-item of attitudes toward chemistry learning. The statistics used for analyzing the collected data were mean, standard deviation, F-test (one-way MANOVA), Hotelling’s T2 and Univariate t-test. The results of the study revealed that the students who learned using the 7-E learning cycle, KWL learning method and the conventional approach were differently showed analytical thinking, science learning achievement and attitudes toward chemistry learning at the 0.05 level of significance. The students who learned using the 7-E learning cycle showed more science learning achievement than did the students who learned using KWL learning method. Also the result and indicated than analytical thinking, science learning achievement and attitudes toward chemistry learning higher than did the students who learned using the conventional approach. In addition, the students who learned using KWL learning method showed higher analytical thinking than did the students who learned using the conventional approach at the 0.05 level of significance. Conclusion: In conclusion, students who learned using the 7-E learning cycle showed analytical thinking, science learning achievement and attitudes toward chemistry learning higher than did the students who learned by KWL learning and the conventional approach. Therefore, teachers should be supported to implement the 7-E learning cycle in science teaching in the future.
  Sombat Tayraukham
  This research aims to study the causal factors influencing teachers’ anxiety on transferring the schools to the local government authorities. Three thousond and five hundred school teachers under the office of education commission region in 19 provinces of the Northeastern region, Thailand was sampled by multi- stage random sampling techniques. The model consisted of four external latent variables: self-confidence, social participatory, attitudes towards local government authority and Internal working relationship. The internal latent variable was the anxiety on transferring the schools to the local government authority. The instruments used for collecting data were: a test on self-confidence, a test on social participatory, a test on attitude towards local government authority and a test on the anxiety on transferring the schools to the local government authority. The data were analyzed by descriptive statistics and validity test of the causal relationship model, a test on internal working relationship. Results indicated that the model fit the empirical data. Goodness of fit measures included chi-square (χ2) value = 300.89 at degree of freedom = 263, probability = 0.053, Goodness of Fit Index (GFI) = 0.99, Adjusted Goodness of Fit Index = 0.98, Standardized Root Mean Square Residual (SRMR) = 0.01 and Root Mean Square Error of Approximation (RMSEA) = 0.00. The variables in the model were found to account for 72% of the dependent variable’ s cvariance. All variables were statistically significant, having a direct effect on transfer the schools to the local government organization.
  Sombat Tayraukham
  This research aimed to investigate academic ethics in research methodology of Mahasarakham University’s Graduate Students, to compare between academic ethics in research methodology of Masters students and that of doctoral students and to construct predictive equations of factors that were related to behavioral academic ethics in research methodology. The samples of the study were 66 doctoral students and 434 Master students, who were enrolled in the faculty of Education, Mahasarakham University. The research instrument included: a 30-items scale on the academic ethics in research methodology with discriminating powers ranging from 0.19-0.63 and a reliability of 0.8645. The collected data were analyzed by percentage, mean and standard deviation t-test. Pearson Product-Moment Correlation Coefficient and Multiple Regression Analysis were employed for hypothesis testing. The results of the study showed: that all students who involved as the sample of the study had average scores of 26.35 (SD = 3.00) on academic ethics knowledge and 26.41 (SD = 3.06) on academic ethics behavior, while their attitude score toward academic ethics was at a high level, that there was no difference among masters students and doctoral student in terms of academic ethics knowledge score, academic ethics attitude score and academic ethics behavior score and that academic ethics knowledge and attitude toward academic ethics could predict academic ethics behavior. The multiple correlation coefficient (R) was 0.908 with predicting powers at 82.40%. The equations in the raw-scores form and standard-score form could be written as: the predictive equations in the raw-score form: Y’ = 1.072 + 0.877 know + 0.560 Att and the predictive equations in the standard-score form: Zy’ = 0.860Zknow + 0.081ZAtt.
  Methee Klomduang and Sombat Tayraukham
  The purposes of this study were to examine the relationships between factors of quality of life of University students and their learning motivation, to find out predictive variables of the students’ learning motivation, to analyze factors of the students’ quality of life as well as to regroup these variables and then to construct predictive equations of learning motivation of the students. The sample used in this study consisted of 1,300 Rajabhat Mahasarakham University students, obtained using the stratified random sampling technique. Data were collected using questionnaires on the quality of life with discriminating powers ranging 2.55-8.59 and reliabilities ranging 0.91-0.94 and a scale on learning motivation with discriminating powers ranging 2.56-7.02 and a reliability of 0.95. The collected data were analyzed using an exploratory factor analysis and stepwise multiple regression analysis. The results of the study were as follows: the variables, which could predict learning motivation of University students at the 0.01 level of significance included quality of life in terms of relationship with other people (D), quality of life in learning (A), quality of life in the services received from the university (E) and quality of life in terms of society with multiple correlation coefficient (R) of 0.708, an adjusted predictive coefficient (R2adj) of 0.497 and a Standard Error (SEest) of 0.318. For the results of factors analysis of the quality of life and regrouping the variables, seven factors were obtained and the factors were named in this order: social welfare (X1), the learner development process (X2), convenience and safety of the residence (X3), promoting commitment with other people (X4), the university’s utilities and materials to support learning (X5), the university’s health welfare and guidance services (X6) and creating learners’ human relationship (X7). The variables after factor analysis, which could predict University students’ learning motivation at the 0.01 level of significance included: factors in terms of creating learner’s human relationship (X7), social welfare (X1), promoting commitment with other people (X4), learner development process (X2) and the university’s utilities and materials to support learning (X5) with a multiple correlation coefficient of 0.707, an adjusted predictive coefficient (R2adj) of 0.496, a predicting power at 49.6%, a standard error of 7.9723 and constance of the predictive equations in the raw-score form of 13.270. The predictive equations could be constructed in a raw score form an a standardized score form as: the predictive equation in the raw-score form Y’ = 13.270 + 0.680X7 + 0.183X1 + 0.375X4 + 0.218X2 + 0.259X5, the predictive equation in a standardized score form Zy’ = 0.311Zx7 + 0.133Zx1 + 0.164Zx4 + 0.164Zx2 + 0.131Zx5.
 
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