A Study on the Preferences of Dental Technology Students for Overseas Employment
Bibliographic record
Abstract
Purpose: This study aimed to find overseas workplace and improve global competence through the preference survey on overseas employment by dental technology students. Methods: The survey sample consisted of 250 randomly selected dental technology students. Survey was conducted from March 1 to May 1 in 2012. Total of 245(98.0%) replies and analyzed 236 questionnaires excluding 9 incomplete questionnaires. The questionnaires used in this study consisted of 7 items for general information, overseas employment characteristics of 10 items, 7 items for overseas employment activation plane and job competency development of 7 items. Collected data were analyzed using SPSS(Statistical Package for Social Sciences) Win 19.0 statistics program. Results: Regarding general characteristics of the subjects, there were 131 third graders(55.5%), 63 first graders(26.7%) and 42 second graders(17.8%) among 130 males(55.1%) and 106 females(44.9%). 221(93.6%) of the subjects had no experience in language training. Students who had clinical training for 1-5 months were 123(52.1%), and 24(10.2%) students had more than six months. 89(37.7%) of the subjects had no clinical training. 155(65.7%) of the subjects hope to work with korean owner, and 81(34.3%) chose foreign owner. Favored working countries were Australia(41.5%), the United States(29.2%), Canada(18.2%) and other(11.0%). The field of dental ceramic was indicated to be the highest proportion of 104(44.1%). Period of training were 3 hours(40.3%) and 6 hours(35.2%). The most important training were language-centered education(54.2%), Job-oriented education(24.2%), local culture education(16.1%), other(3.0%) and Leadership Training(2.5%). The subjects chose overseas worker(44.9%), working-level practitioner (28.8%), successfully employed dental technology graduate(19.5%a) and professor(3.4%) as an instructor. The subjects get education and training information from professor(40.3%), other(28.0%), senior(14.4%), job site(8.9%) and acquaintance(8.5%). A credit exchange(2.46 points), a joint degree program(2.46 points), and a foreign professor(2.33 points) were needed to activate the overseas employment. A kind of dental prosthesis(3.58 points), carving tooth morphology(3.38 points), and majors of dental technology(3.30 points) were indicated to develop job competency for overseas employment. Age, year, clinical training experience and company owner were statistically meaningful data among the general characteristics affecting job competency development. Conclusion: The college needs to offer variety programs such as foreign language-centered education and a local job competency development program to graduates to be connected with international workplace and employment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".