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Record W2787244561 · doi:10.5430/ijhe.v7n1p111

The Use of Qualitative Case Studies as an Experiential Teaching Method in the Training of Pre-service Teachers

2018· article· en· W2787244561 on OpenAlexvenueno aff
İlhami Arseven

Bibliographic record

VenueInternational Journal of Higher Education · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
Fundersnot available
KeywordsExperiential learningConceptualizationQualitative researchMathematics educationConstructivism (international relations)PsychologyComputer sciencePedagogySociologyArtificial intelligence

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.250
GPT teacher head0.575
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2018
Admission routes1
Has abstractyes

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