The Contribution of Learner Self-Assessment for Improvement of Learning and Teaching Process: A Review
Bibliographic record
Abstract
The present study is a literature review of 37 empirical studies from Greece and internationally of the last decade and aims at investigating the contribution of learner self-assessment to: a. enhancement of learning motivation, b. improvement of academic performance/learning, c. development of self-regulating learning and d. raise of self-esteem. According to the findings, enhancement of learning motivation as an outcome of learner self-assessment process has been identified in Greek Higher education, in Secondary education in Physics and in Primary education in English, whereas internationally has been identified in Secondary education in English and Physical education. In Greece, improvement of academic performance/learning as an outcome of learner self-assessment has been found in Higher education, in Secondary education in Physics and in Primary education in English, whereas internationally at all levels of education, in almost all subjects of Secondary education and in Primary education in Language Arts, English and Mathematics. Development of self-regulating learning has been identified in Higher education in Greece and internationally, whereas in Secondary education in Geography and Geometry only internationally. Furthermore, raise of student’s self-esteem as an outcome of self-assessment has been found internationally, in Secondary education in Religious education and in Greek Primary education in English language learning. Moreover, self-assessment process has also been examined internationally in non-formal education where English is taught as a second language with positive outcomes in performance/learning. Finally, self-assessment is implemented through various practices and tools such as rubrics, checklist, scripts, think boards, reflective journals, mind maps and in combination with learning or teaching models.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".