Research Abstract No.52
             Variables predicting academic achievement of students
       in master of science program ( behavioral science ) field of study
                        : applied behavioral science research
                                               by
                       Assoc.Prof. Dr. Pachongchit Intasuwan
                             Instructor Mr. Prateep Jinnge
                        Researcher Mrs. Tasana Tongpukdee
                          Researcher Miss. Usa Srijindarat   


    The present study was designed to explore the variables which could predict academic achievement of
the students in Master of Science Program ( Behavioral Science ) whose field of study is Applied
Behavioral Science Research. The sample consisted of 61 graduates and students in the program during
1984 - 1990. Data were collected from graduate entrance examination records, grade records and personal
history records of the students. 
    Data were analyzed by using pearson product moment correlation, one-way analysis of varience and
chi-square. Stepwise multiple regression analysis was used to find predictors of academic achievement. 
    The academic achievement was categorized into grade point average at the end of the first term,
cumulative grade point average at the end of the third term, grade point average for research methodology
and statistic courses, grade point average for individual and environment course and grade point average
of individual and social development courses. 

    The results of the study were summarized as follows : 
    1. Entrance examination scores for the research methodology and statistics part, cumulative grade point
average at the bachelor's degree level and sex could significantly predict grade point average for the first
term at the .001 level. The predicting power variance explained ( r2) was 33 percent. 
    2. Cumulative grade point average at the bachelorís degree level, sex, entrance examination scores for
the research methodology and statistics part, and work records of students could significantly predict
cumulative grade point average at the end of the third term at the .001 level, with 37% predicting power. 
    3. Entrance examination scores for the research methodology and statistics part, studentsí work records
and sex could significantly predict grade point average for the research methodology and statistics part at
the .001 level. The predicting power was 38 percent. 
    4. Cumulative grade point average at the bachelorís degree level and the entrance examination scores
for the research methodology and statistics part could significantly predict grade point average for the
individual and environment part at the .01 level, with 18% predicting power. 
    5. Cumulative grade point average at the bachelorís degree level could significantly predict grade point
average for the individual and social development part at .05 level. The predicting power was 9 percent. 
    6. Studentsí cumulative grade point average at the end of the third term for both sexes significantly
differed at .05 level. Female students had higher cumulative grade point average at the end of the third
term than male. 
    7. Grade point average at the end of the first term, cumulative grade point average at the end of the
third term, grade point average for the individual and environment part for non-working and working
students differed significantly at .05 and .01 levels. 
    8. Grade point average for the research methodology and statistics part of students with bachelorís of
science degree graduates and those with social sciences or other degrees differed significantly at .01 level. 


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