Personality Traits as Predictors of Self-Regulated Learning and Academic Engagement among College Students in Ghana: A Dimensional Multivariate Approach
Bibliographic record
Abstract
The study explored personality traits as they predicted self-regulated learning and academic engagement among college students in Ghana. A sample of 652 (return rate was 87.0%) was drawn from an accessible population of 17,396. Adapted versions of Taiwanese Short Self-Regulation Questionnaire (22 items; α = 0.84), University Student Engagement Inventory (15 items; α = 0.81), and Big-Five Personality Inventory (30 items; α = 0.70) were used for the data collection. The data collected were analysed using multivariate multiple regression. The study revealed that student-teachers exhibited lower levels of self-regulated learning and academic engagement. Again, openness, conscientiousness, extraversion, and agreeableness aspects of the personality traits predicted self-regulated learning and academic engagements of students. Findings from this study serve as a beacon for teacher education programs in Ghana to scale up their efforts in ensuring that preservice teachers are able to self-regulate their learning. As preservice teachers who will soon be practicing, they cannot help their students self-regulate their learning if they themselves have low levels of self-regulation and engagement. Students’ success can only be realized when learners are able to manage their own learning and engage in academic activities.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".