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Record W4406586570 · doi:10.5539/ies.v18n1p47

Enhancing Graduate Research Skills via Action Research and Book Clubs

2025· article· en· W4406586570 on OpenAlexvenueno aff
Noha Altowairiki

Bibliographic record

VenueInternational Education Studies · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsAction researchMathematics educationPsychologyGraduate studentsAction (physics)PedagogySociology

Abstract

fetched live from OpenAlex

This study investigates the application of action research to enhance the development of research methodology knowledge among graduate students. Students, in this study context, were dissatisfied with current courses, leading to knowledge gaps and limited application of research approaches. Through iterative cycles of action research, a book club intervention was implemented. Key findings highlight several critical design elements: selecting engaging textbooks, optimizing group size for interaction, scheduling sessions during breaks, actively facilitating discussion and misconception correction, and integrating technological tools for communication and reflection. Overall, this study underscores the potential of action research as a valuable framework for developing effective educational methodologies, emphasizing the need for thoughtful design in creating supportive learning environments. Future studies should explore innovative teaching approaches that incorporate diverse perspectives to further enrich graduate education.

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)0.008
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.626
GPT teacher head0.685
Teacher spread0.058 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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