Predictors of Graduate Students’ Research Performance in the Philippine State-Run Higher Education Institution
Bibliographic record
Abstract
This descriptive study determined the predictors of research performance of the graduate students in Occidental Mindoro State College, San Jose, Occidental Mindoro, Philippines. This research specifically looked into the graduate students’ level of research performance, attitude towards research, challenges encountered, and the strategies employed to cope with the research challenges. A total of 41 completely enumerated students enrolled in Methods of Research and Thesis Writing during the second semester of Academic Year 2018-2019 served as respondents of the study. The study found that the graduate students’ level of research performance is high, specifically in writing the statement of the problem, hypothesis, significance of the study, and definition of terms. They have a positive attitude towards research in terms of usefulness and predispositions. They have negative research anxiety. Challenges encountered include insufficient funds, developing interest, inability to select researchable topics, and limited related literature. Coping strategies employed were frequent consultations with the adviser, seeking help from other competent faculty and students, using technology, and giving material appreciation. Attitude and challenges encountered were found to be predictors of the graduate student’s research performance. A positive attitude towards research and the moderate challenges encountered could affect the graduate student’s research performance.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".