Companion repository for Volume 9 of 10 in the Engineering-to-Research Monograph Series by Alan Biju Palayil.
Applied computing has a methods problem that masquerades as a results problem. Rigorous research is mixed-methods and reproducibility-first: quantitative methods establish whether an effect is real, qualitative methods establish why and for whom, and reproducibility makes the answer trustworthy.
- About this repository
- The monograph
- Framework at a glance
- Repository structure
- Figures
- How to cite
- The Engineering-to-Research series
- Versioning
- License
- Author
- Acknowledgments
This repository is the companion to the technical report Whether, Why, and For Whom: A Mixed-Methods, Reproducibility-First Research Framework for Applied Computing and Cybersecurity. It holds the paper and the source figures. The archival record of the paper lives on Zenodo with a permanent DOI.
The paper synthesizes the author's training in statistics, research design, and qualitative inquiry into one research-methods framework, and serves as the validation standard for the companion artifacts across the series and the seed of the author's dissertation methods chapter.
- Title: Whether, Why, and For Whom: A Mixed-Methods, Reproducibility-First Research Framework for Applied Computing and Cybersecurity
- Series: Engineering-to-Research Monograph Series, Volume 9 of 10
- Type: Technical report / methods monograph
- Version: 1.1 (June 2026)
- DOI: 10.5281/zenodo.20829174 (version 1.1)
- Paper:
paper/11_Monograph_9_Research_Methods_for_Applied_Computing.pdf
Abstract. Applied computing and cybersecurity research has a methods problem that masquerades as a results problem; the visible symptom is the reproducibility crisis and the underlying cause is insufficient research-methods rigor. This monograph synthesizes quantitative statistics, research design, and qualitative inquiry into a coherent mixed-methods, reproducibility-first framework, arguing that socio-technical questions require statistical validity to establish whether an effect is real, qualitative inquiry to establish why and for whom, design discipline to make the question answerable, and reproducibility practices to make the answer trustworthy. Grounded in the author's coursework (JASP regression, a doctoral research-design study, and a full qualitative interview study with thematic analysis), it serves as the validation standard for the series and the seed of the author's dissertation.
The research-methods pipeline: design, quantitative, qualitative, integration, reproducibility, from a question to a trustworthy, reusable result.
Design Principle 1 (Methods Follow the Question). The question, not the tool, decides whether a study is quantitative, qualitative, or mixed.
Design Principle 2 (Reproducibility Is a Property of the Whole Pipeline). Reproducibility is designed in from the question onward, not certified at the end.
Synthesized contributions.
- An integrated research-methods framework for applied computing.
- Two methodological design principles.
- A validation standard for the series and the dissertation.
whether-why-and-for-whom-vol9/
├── README.md
├── LICENSE # CC BY 4.0 (paper and figures)
├── CITATION.cff
├── .zenodo.json # Zenodo deposit metadata (root-level name required)
├── paper/
│ ├── 11_Monograph_9_Research_Methods_for_Applied_Computing.pdf
│ └── 11_Monograph_9_Research_Methods_for_Applied_Computing.docx
└── figures/
├── vol9_fig1_research_pipeline.svg / .png
└── vol9_fig2_mixed_methods_designs.svg / .png
- Figure 1, the research-methods pipeline (design, quantitative, qualitative, integration, with reproducibility spanning the whole).
- Figure 2, mixed-methods design types (sequential explanatory and exploratory, concurrent, embedded, with applied-computing examples).
Provided as editable SVG and rendered PNG.
A machine-readable CITATION.cff is included; GitHub renders a "Cite this repository" button from it.
IEEE. A. B. Palayil, "Whether, Why, and For Whom: A Mixed-Methods, Reproducibility-First Research Framework for Applied Computing and Cybersecurity," Engineering-to-Research Monograph Series, vol. 9, 2026. doi: 10.5281/zenodo.20829174.
@techreport{palayil2026methods,
author = {Palayil, Alan Biju},
title = {Whether, Why, and For Whom: A Mixed-Methods, Reproducibility-First Research Framework for Applied Computing and Cybersecurity},
institution = {Engineering-to-Research Monograph Series},
number = {Volume 9 of 10},
year = {2026},
version = {1.1},
doi = {10.5281/zenodo.20829174},
url = {https://doi.org/10.5281/zenodo.20829174}
}This is Volume 9 of a ten-volume program that turns a decade of engineering and research training into one coherent research identity, ending in explainable-AI governance. All ten volumes are published on Zenodo:
| Vol | Title | DOI |
|---|---|---|
| 1 | Securing Connected Systems | 10.5281/zenodo.20733453 |
| 2 | Computer Architecture as a Security Discipline | 10.5281/zenodo.20821993 |
| 3 | Getting the Foundations Right | 10.5281/zenodo.20828879 |
| 4 | Embedded-to-Edge-AI Reference Architecture | 10.5281/zenodo.20784402 |
| 5 | Teaching Offensive Security | 10.5281/zenodo.20821927 |
| 6 | Governance as the Integration Layer | 10.5281/zenodo.20828631 |
| 7 | Scalable Analytics for Enterprise Decisions | 10.5281/zenodo.20828327 |
| 8 | Data Mining for Financial Systems | 10.5281/zenodo.20802595 |
| 9 | Whether, Why, and For Whom | 10.5281/zenodo.20829174 — this volume |
| 10 | From Embedded Systems to Explainable AI Governance | 10.5281/zenodo.20829270 |
This repository follows the monograph version. Version 1.1 corresponds to its Zenodo deposit; future revisions are released as new Zenodo versions under the same concept DOI and tagged here with matching GitHub releases.
Paper and figures are licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE.
Alan Biju Palayil Independent Researcher; Doctoral Researcher, University of the Cumberlands; Financial Systems Practitioner. ORCID: 0009-0004-8302-5090 GitHub: @AlanP13
This work originated in doctoral coursework at the University of the Cumberlands: DSRT-734 Statistics, DSRT-837 Research Design, and DSRT-850 Qualitative Research. All synthesis, analysis, and writing are the author's own and were written from scratch for publication. The repository contains no confidential or proprietary employer information.