Motives of Students’ Joining Master Program at Princess Alia University College/Al Balqa Applied University
Bibliographic record
Abstract
This study aimed at knowing the motives of students’ joining master program at Princess Alia University College/Al Balqa Applied University by the graduate students and a degree of their importance and succession, and to know whether these motives differed according to the variables of gender, specialization, age, and marital status. To achieve this goal, a questionnaire of two parts was developed: the first part consisted of personal information of a subject for the independent variables (gender, specialization, age, and marital status). The second part consisted of 25 items distributed on the following five fields: scientific motive, professional motive, psychological motive, social motive and economical motive with five items for each field. The questionnaire was applied on a study sample of 100 male and female students after having acceptable values of validity and reliability. The date was statistically analyzed by using means, standard deviations, T-test, and one way ANOVA. The results of the study showed that: Motives behind students’ joining master program were in descending sequence: scientific, professional, psychological, economic and social. There were statistically significant differences at (a<=0.01) between the means of the motives, due to students’ gender, in the field of psychology for female and in the field of social motive (a<=0.05) for females. There were no statistically significant differences at (a<=0.05) between the means of the motives, due to age, specialization and marital status. The study recommended that Al Balqa Applied University should take in mind motives of students’ joining master program by choosing the appropriate programs to develop and improve current programs for master in order to evaluate their level of knowledge and behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".