Self-Efficacy as Predictor of Motivational Goals in University Students
Bibliographic record
Abstract
Self-efficacy is an important factor in the accomplishment of goals because people with confidence in their capabilities are likely to approach difficult tasks as challenges and are motivated to master them rather than avoid them. The present study has investigated the potential role of self-efficacy in various approaches towards goal attainment. Self-efficacy refers to belief in oneself and one's personal skills; a person who perceives herself/himself in a positive way will be more motivated than a person who anticipates herself/himself as a failure (Was, 2006). Austin and Vancouver (1996) proposed that self-efficacy plays a very important role in the goal choice and task preference. When a person has confidence in his skills, with no self-doubt, he will possess a sense of being and be sufficiently prepared for a challenge. Thus, he becomes more motivated towards achievement. Self-efficacy levels can enhance or obstruct motivation. People with high self-efficacy choose to perform more challenging tasks; they set higher goals for themselves and stick to them. Actions are reshaped in thoughts, and people anticipate either optimistic or pessimistic scenarios in line with their level of self-efficacy (Kumar & Lai, 2006).Goals are defined as the end towards which one's effort is directed (Was, 2006). Goals serve as a course to the destination. When a person wants to do anything, he or she sets some behavioural intentions for the success. These intentions are referred to goals. Goal-oriented theorists define achievement goals as concrete cognitive representations that focus on a particular type of performance and these behavioural intentions are very much affected by the level of self-efficacy, which is belief in one's own self (Elliot C Lent, Lopez, & Bieschke, 1991; Elliot &Church, 2003).These gender differences in self-efficacy are attributable to different environmental, sociocultural, and inherited factors. …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| 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".