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Record W7103757117 · doi:10.5281/zenodo.17506574

Assessing the Impact of Institutional-Based Research on Teaching Effectiveness in Early Childhood Education: A Case Study of Jigawa State College of Education and Legal Studies, Ringim

2025· article· W7103757117 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldDecision Sciences
TopicEducational Assessment and Improvement
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPremiseEarly childhoodCurriculumEarly childhood educationQualitative researchProfessional developmentQuality (philosophy)Qualitative property

Abstract

fetched live from OpenAlex

Institutional-Based Research (IBR) has emerged as a vital instrument for enhancing the quality of teaching and learning, improving professional competence, and advancing educational innovation in higher institutions. This study investigates the impact of IBR on teaching effectiveness within the Department of Early Childhood Care and Education (ECCE) at Jigawa State College of Education and Legal Studies, Ringim. The research is anchored on the premise that effective teaching, especially at the early childhood level, thrives on reflective inquiry and evidence-based practices that address context-specific educational challenges.The study adopts a mixed-methods approach that integrates both quantitative and qualitative paradigms to provide a comprehensive understanding of the phenomenon. Data will be collected from lecturers, administrators, and student-teachers through questionnaires, interviews, and document reviews. Quantitative data will be analyzed using descriptive and inferential statistical tools, while qualitative data will be examined thematically to reveal deeper insights into participants’ experiences and perceptions. Preliminary expectations suggest that lecturers’ engagement in IBR enhances pedagogical creativity, classroom management, and student learning outcomes through reflective teaching and knowledge generation. Moreover, IBR fosters collaboration among academic staff, strengthens research culture, and bridges the gap between theory and practice. However, the study also anticipates identifying key challenges such as inadequate funding, limited institutional incentives, heavy teaching workloads, and insufficient research facilities that hinder active participation in IBR.Findings from this study are expected to contribute to policy and institutional reforms aimed at promoting a sustainable research culture and integrating IBR outcomes into curriculum development and teacher professional growth. The study underscores the importance of institutional commitment to supporting research-driven teaching as a pathway toward achieving educational excellence in Early Childhood 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)0.012
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.142
GPT teacher head0.473
Teacher spread0.330 · 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 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
Published2025
Admission routes1
Has abstractyes

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