Case Study in Contemporary Educational Research: Conceptualization and Critique
Bibliographic record
Abstract
As one of important research methods, case study research has been used for many years across a variety of disciplines. This paper tries to review the principles and processes of case study. First, I would like to define case study according to its principles. Second, attentions will be put to the features and classification of the research of case study. Third, I intend to explain the process of case studies and case study methods. Fourth, I would review the strengths and weaknesses of case study research. Last, I shall summarize and critique a case study of language learning. Key words: Case Study; Research Methods; Educational Research Resume: Comme l'une des methodes de recherche importante, la recherche d’etudes de cas a ete utilisee pendant de nombreuses annees a travers une variete de disciplines. Le present article tente d'examiner les principes et les processus d’etudes de cas. D'abord, je tiens a definir la notaion d’etudes de cas selon ses principes. Deuxiemement, les attentions seront mises aux caracteristiques et a la classification de la recherche d’etudes de cas. Troisiemement, j'ai l'intention d'expliquer le processus et des methodes d’etudes de cas. Quatriemement, je voudrais passer en revue les forces et les faiblesses de la recherche d’etudes de cas. Enfin, je vais faire un resume et des critiques d’une etude de cas sur l'apprentissage des langues. Mots-cles : etudes de cas; methodes de recherche; recherche pedagogique
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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 | 0.121 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.009 | 0.088 |
| Scholarly communication | 0.026 | 0.028 |
| Open science | 0.008 | 0.013 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".