Authors
Thi-Hoa-Hue Nguyen, Ngo Thanh Doan, Hoang Duy Kien, Dang Trong Hop, Nguyen Thi Kim Son
Published in
Data in brief. Volume 69. Pages 113320. Epub Oct 09, 2026.
Abstract
This article presents a high-dimensional longitudinal dataset (1,656 student records x 56 variables) synthesized from institutional academic administrative records of undergraduate students in an automotive engineering program at an application-oriented university in Vietnam. Unlike static datasets derived from fixed schemas, this resource was extracted from disparate, spreadsheet-based management files across multiple academic years, requiring a systematic process of cleaning, standardization, and harmonization to resolve inconsistencies in nomenclature and coding. The dataset retains real-world curriculum variation across academic years, including differences in course naming, course sequencing, semester placement, and elective pathways. The released data are provided in two parallel tabular formats: a labeled version for immediate interpretation and a harmonized coded version designed for reproducible analytical pipelines. The 56 variables encompass student-level contextual information, harmonized course grades, cumulative performance indicators, scholarship records, and academic status. Beyond descriptive analysis and learning analytics, this repository provides a standardized reusable resource for educational data mining, feature engineering, interpretable machine learning, and predictive modeling studies, including analyses of academic performance and student progression. It also provides a reference dataset for methodological research on data harmonization, the reuse of heterogeneous administrative records, and curriculum analytics.
PMID:
42927250
Bibliographic data and abstract were imported from PubMed on 25 Oct 2026.
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