Relationship between Student’s Self-Directed-Learning Readiness and Academic Self-Efficacy and Achievement Motivation in Students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Self-directed learning readiness to expand and enhance learning, This is an important goal of higher education, Besides his academic self-efficacy can be improved efficiency and Achievement Motivation, so understanding how to use these strategies by students is very important. Because the purpose this study is determination of relationship between students self-directed learning and academic self-efficacy and Achievement Motivation in Payamnoor students (2012-2013). In a correlation-descriptive study 322 bachelor students were selected from Payamnoor University of Rafsanjan (2014-2015) through a Simple random sampling. Data collection was SDL questionnaire, academic self-efficacy questionnaire and Achievement Motivation questionnaire. Data were analyzed by multiple regression, simple regression, variance analysis and T-test. The obtained findings from this research showed that there is a relation between student’s Self-directed learning readiness and academic self-efficacy and academic motivation in Students University of Payamnoor. Also Independence in learning and Study skills and problem solving has the most ability for academic self-efficacy and academic motivation prediction and there was the most correlation.According to results and that self-directed learning readiness to enhance self-efficacy and academic motivation, it is necessary to teach strategies to students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it