Best Researcher Award
Ebrahim Khodaie — University of Tehran
| Ebrahim Khodaie | |
|---|---|
| Affiliation | University of Tehran |
| Country | Iran |
| Scopus ID | 23492563700 |
| Documents | 64 |
| Citations | 64 |
| h-index | 4 |
| Subject Area | Social Sciences |
| Event | World Top Scientist Awards |
| ORCID | 0000-0002-5634-5003 |
Ebrahim Khodaie is a researcher affiliated with the University of Tehran whose work focuses on educational assessment, psychometrics, learning analytics, and quantitative methodologies in the social sciences. His scholarly contributions emphasize evidence-based approaches to educational measurement and academic evaluation.[1]
Contents
Abstract
This article presents an overview of Ebrahim Khodaie’s academic profile in consideration for the Best Researcher Award. His work spans educational measurement, psychometric modeling, data mining, and learning analytics. Through interdisciplinary research, he has contributed to methodological advancements in assessment and educational decision-making.[2]
Keywords
Educational Assessment, Social Sciences, Psychometrics, Learning Analytics, Data Mining, Item Response Theory, Academic Evaluation.
Introduction
Educational assessment research increasingly depends on statistical and computational techniques for evaluating learning outcomes. Ebrahim Khodaie has contributed to this field through studies focused on fairness, predictive analytics, psychometric evaluation, and evidence-based educational methodologies. His work reflects a strong commitment to quantitative educational research.[3]
Research Profile
As a scholar at the University of Tehran, Khodaie has developed expertise in educational measurement and social science analytics. His publications address assessment systems, student performance evaluation, and statistical modeling techniques. His ORCID and Scopus records demonstrate continuous engagement in international scholarly communication.[1]
Research Contributions
Khodaie’s contributions include innovative approaches to cut-score determination, fairness in classroom assessment, educational data mining, and item response theory applications. His studies provide practical insights for researchers, institutions, and policymakers seeking reliable educational evaluation frameworks.[2]
Publications
- Data-driven Cut Score Method Based on IRT, Clustering, and Gaussian Otsu Thresholding (2026).
- Comparative Approach to Define Cutoff Scores Using Youden Index, Hurwicz Criterion and MLP Neural Networks (2025).
- Fairness in Classroom Assessment: A Systematic Review (2022).
- Application of Data Mining Techniques in Determining Student Academic Failure (2020).
- Family Background and Socioeconomic Status Effects on Educational Performance (2016).
Research Impact
The researcher’s publications contribute to contemporary discussions on educational assessment quality and predictive learning analytics. His studies support improved measurement reliability, assessment fairness, and data-informed academic decision-making. These contributions have relevance across educational institutions and research communities.[4]
Award Suitability
The Best Researcher Award recognizes scholarly excellence, research quality, and sustained academic contribution. Khodaie’s publication portfolio and focus on rigorous methodological development align with the principles of academic recognition programs that emphasize innovation, impact, and scientific integrity.[5]
Conclusion
Ebrahim Khodaie has established a scholarly profile centered on educational measurement, data analytics, and social science research. His contributions demonstrate the value of quantitative methodologies in improving educational assessment practices. These achievements support consideration for recognition through international academic award programs.
External Links
References
- ORCID. (2026). Ebrahim Khodaie ORCID Record.
https://orcid.org/0000-0002-5634-5003
- Parsaeian M, Khodaie E, Naderi H. Data-driven Cut Score Method Based on IRT, Clustering, and Gaussian Otsu Thresholding. Behaviormetrika. 2026.
DOI: https://doi.org/10.1007/s41237-026-00298-5
- Parsaeian M, Khodaie E, Izanloo B, Salehi K, NaghiZadeh S. Comparative Approach to Define Cutoff Scores Using Youden Index, Hurwicz Criterion and MLP Neural Networks. SN Computer Science. 2025.
DOI: https://doi.org/10.1007/s42979-025-03974-7
- Khodaie E. Fairness in Classroom Assessment: A Systematic Review. The Asia-Pacific Education Researcher. 2022.
DOI: https://doi.org/10.1007/s40299-021-00636-z
- Khodaie E. Application of Data Mining Techniques in Determining the Accuracy of the Models Predicting Student Academic Failure. Journal of Ilam University of Medical Sciences. 2020.
DOI: https://doi.org/10.29252/sjimu.28.1.36