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Record W4415294828 · doi:10.5430/jct.v14n4p26

Faculty Perceptions of the Research-Teaching Nexus in Oman Business School

2025· article· W4415294828 on OpenAlexvenueno aff
Bashir Ahmad Fida, Umar Ahmed, Shahala Nassim, Sauda Al-Marhoobi, Ibrahim Gambo

Bibliographic record

VenueJournal of Curriculum and Teaching · 2025
Typearticle
Language
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)AccreditationEmployabilityMultivariate analysis of varianceHigher educationQuality (philosophy)WorkloadPerception

Abstract

fetched live from OpenAlex

The research–teaching nexus (RTN) is a core accreditation requirement of the Oman Authority for Academic Accreditation and Quality Assurance of Education (OAAAQA). Embedding research into teaching enhances educational quality, bridges the gap between theory and practice, and develops students’ critical and analytical skills. This study investigates faculty perceptions and practices of RTN within a business college in Oman. A quantitative research design was employed, using a structured survey administered to academic staff and analyzed through descriptive statistics and a one-way multivariate analysis of variance (MANOVA). Results reveal strong engagement with RTN: 76% of faculty integrate their research, 83% embed external research, 80% involve students in projects, and 79% supervise and provide feedback on theses. Moreover, 92% reported that research keeps them updated on emerging trends, 87% indicated it introduces new insights that enrich teaching, and another 87% affirmed it stimulates pedagogical innovation. Significantly, 97% agreed that RTN directly enhances students’ competencies and employability skills. The MANOVA results indicate a statistically significant multivariate effect on respondents’ perceptions of RTN practices, educational quality, and student skill development. In contrast, neither gender nor teaching experience produced statistically significant differences, suggesting that these demographic variables exert limited influence on how respondents evaluate institutional RTN practices or their associated outcomes. Despite these positive practices, challenges remain, including heavy teaching loads, limited time, and restricted research funding. The study concludes that effective implementation of RTN requires institutional support, workload alignment, and faculty development initiatives. The findings provide practical implications for academic leaders and quality assurance bodies seeking to advance innovation and educational quality in higher 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.399
Teacher spread0.369 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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