Improving data integrity through institutional mechanisms:
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Date
2026-02
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Association for Computing Machinery
Abstract
This study presents a comprehensive analysis of graduate research practices at DMMMSU-CGS, focusing on data processing integrity, statistical tool selection, and methodological transparency. Findings revealed critical inconsistencies in the documentation of software tools, with over half of the studies failing to specify the programs used, thereby limiting reproducibility. Among those that did, SPSS emerged as the predominant software, followed by MS Excel and other specialized applications—an indication of methodological dependence on a single platform. To address these gaps, a standardized Data Processing Manual was developed and validated using Lawshe's Content Validity Index. The manual received high expert ratings in content relevance, usability, and organizational structure. Its adoption is expected to strengthen research rigor, enhance transparency in data analysis reporting, and elevate the overall quality and reproducibility of academic research within the institution.
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Ochoa, M. A. (2026). Improving data integrity through institutional mechanisms: A policy study on graduate research advising. In 2026 The 15th International Conference on Informatics, Environment, Energy and Applications (IEEA 2026) (pp. 61–66). Association for Computing Machinery. [https://doi.org/10.1145/3803833.3803844](https://doi.org/10.1145/3803833.3803844)
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