The Use of Qualitative Case Studies as an Experiential Teaching Method in the Training of Pre-service Teachers
Bibliographic record
Abstract
This study presents the suitability of case studies, which is a qualitative research method and can be used as a teaching method in the training of pre-service teachers, for experiential learning theory. The basic view of experiential learning theory on learning and the qualitative case study paradigm are consistent with each other within the framework of such principles as subjectivity, environmental interaction, holism, contextuality, constructivism, and access to information (theorizing). The concrete experience mode of the experiential learning cycle corresponds to the data collection stage of qualitative case studies, the reflective observation mode corresponds to the data analysis stage, and the abstract conceptualization mode corresponds to the theorizing stage. Accordingly, this study notes that qualitative case studies can be used as a teaching method in the school experience course for the pre-service training of pre-service teachers. It also explains in detail the steps to be taken when this new method is used in the teaching process, the preparations that should be done prior to the employment of the method, and what should be considered in the application of the method.
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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 | 0.053 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".