Adult Learners’ Learning Environment Perceptions and Satisfaction in Formal Education—Case Study of Four East-European Countries
Bibliographic record
Abstract
The purpose of this paper is to explore attitudes towards learning and perceptions of the learning environment. Our theoretical examination is based on the social-cognitive theory of motivation and research that emphasizes the connections between an individual’s perceptions of the learning environment and his/her motivation, interest, attitudes and confidence. Recent theories that deal with ‘powerful learning environments’ (Fraser, 2002) stress that the teacher should not look only at the physical aspects of the environment in which learning takes place, but also at the learner’s perceptions and beliefs. The importance of multiple aspects of learning environments will be stressed and some recommendations for improving the effectiveness of these environments will be given. Additionally, some theoretical concepts of learning environments will be reviewed. We will examine empirically the differences and correlations that occur in adult learners’ motivation and attitudes due to their psycho-social and physical learning environment. An international comparison between various post-socialist countries has also been carried out.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".