Academic Motivations of Pregrade Students in the Choice of International Business Career
Bibliographic record
Abstract
The main objective of this research is to determine which is the most recurrent motivation by university students choose international business careers at 8 universities in Peru. The study sample is composed by 1242 international business students from the main universities in Peru. For this study, the Academic Motivation Scale (AMC) was used, this scale considers intrinsic motivation factors (knowledge, achievement, stimulating experiences), extrinsic motivation (identified regulation, introjected regulation, external introjected) and amotivation.As a result, the research shows that the students wanted to achieve their goals (84%), because it is aligned to their dreams (83%), also that they want to show to other people that they are capable to generate business opportunities (81%). On the other hand, the main demotivations were the fact that they don’t care and just want to finish the career (10%), they didn’t know which career choose (13%) and they didn’t know the reason why they choose this career (15%).It is concludes that the factors of academic motivations (motivation, extrinsic motivations and intrinsic motivations) are positively related to the choice of the international business career. Where the most significant relationship is that between extrinsic motivation with external regulation and the choice of the international commercial career, to achieve its objectives such as giving a more positive image to family and friends. While the least significant relationship is that between the intrinsic motivation for stimulating experiences and the choice of an international business career.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".