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Record W3006902979 · doi:10.5430/ijhe.v9n3p55

Action Research as Perceived by Student-Teachers in the Field Training Program at Hashemite University / Jordan

2020· article· en· W3006902979 on OpenAlexvenueno aff
Sadeq Hassan Al-Shudaifat

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAction (physics)Mathematics educationPsychologyTraining (meteorology)Action researchFace (sociological concept)Perspective (graphical)Field (mathematics)PedagogyMedical educationSociologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Field Training plays a key role in narrowing the gap between theory and practice in the preparation of teachers. University professors and in-service teachers who work in cooperative schools coordinate their efforts to help student-teachers at the Hashemite University link teaching theories to practice.Student-teachers, sometimes, find themselves isolated from theories learned at the universities and feel the gap between theory and practice. As a result, they tend to use traditional teaching methods in the same way they were taught in the past.One of the important requirements of the Field Training Program is asking student-teachers to do action research to clarify issues they face during training. Student-teachers face different problems related to action research: selecting issues, preparing, modeling, implementing, and evaluating the results of the research. Therefore, this study attempts at investigating the student-teachers’ weakness in carrying out Action Research from the students’ own perspective.To achieve the study objectives, the researcher administered a test on (47) student-teachers, and interviewed (6) others.The majority of responses conveyed that student-teachers know how to design action research theoretically but they lack the ability and necessary skills to put this into practice. Based on these findings, this research concludes with some suggestions and recommendations to solve the problem.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.127
GPT teacher head0.467
Teacher spread0.339 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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