Learner-Centeredness vs. Teacher-Centeredness: How Are They Different?
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
This study describes the teaching style behaviors that differentiate between learner-centered and teacher-centered approaches to teaching. The Teaching Style Assessment Scale, which measures teaching style, was completed by 1,261 nursing faculty in Japan. Discriminant analysis and cluster analysis revealed that the distinctive characteristic distinguishing the learner-centered approach from the teacher-centered approach is Personalizing Instruction. Personalizing Instruction recognizes and utilizes the uniqueness of each student’s strengths. Personalizing Instruction can facilitate students’ interpersonal understanding and self-awareness. By implementing Personalizing Instruction, teachers can facilitate the metacognitive process in their students, which is healthy for the individual and productive for meaningful learning. Learner-centeredness embraces Personalizing Instruction, while teacher-centeredness rejects it. Teachers practice learner-centered and teacher-centered styles nearly equally. Personalizing Instruction is the most critical teaching style element and the indispensable definitive factor separating these styles.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 it