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Record W2401337287 · doi:10.5539/ies.v9n6p158

The Investigation of Challenges in Developing and Implementing New Academic Disciplines in Iranian Universities: Views of the Faculty Members

2016· article· en· W2401337287 on OpenAlexvenueno aff
Mansuoreh Ghazavi, A R Nasr, Ebrahim Jafari, Neamatollah Mosapour

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedical educationCurriculum developmentProfessional developmentFaculty developmentDisciplineProcess (computing)PsychologyPedagogyEngineering ethicsSociologyMedicineSocial scienceEngineering

Abstract

fetched live from OpenAlex

<p class="apa">The move on decentralization of curriculum development in recent decade has become one of the major tasks in developing scientific fields in Iran. By implementing these programs some drawbacks have become evident. The objective of this study was to identify and assess the existing challenges involved in the development of academic disciplines from the faculty members’ views. For this aim, through a descriptive study, a body of 125 faculty members involved in academic disciplines development from state universities of Isfahan, Tehran and Ferdowsi are randomly selected. The study pursued seven research questions using a researcher-made questionnaire. Findings showed that interdisciplinary challenges, structural challenges and management challenges significantly exceeded the moderate level. Moreover, scientific-professional and financial challenges significantly affected the curriculum development of the academic disciplines. Results of MANOVA further showed that there were significant differences between the mean scores of faculty members’ views regarding the structural and management challenges in different universities. In general, results of the study highlighted the challenges which can be considered as important obstacles in the development process of disciplines and society at large. Optimization of this process needs the correctly addressed opinions of the faculty members in this respect.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.416
GPT teacher head0.536
Teacher spread0.120 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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