During the Research Methods and Professional Practice (RMPP) module, I had the opportunity to learn about research ethics, academic writing, statistical analysis, and how to evaluate existing literature critically. It has been both a challenging and transformative journey. I explored the whole research cycle, from formulating questions and reviewing sources to designing proposals and interpreting data. These experiences have deepened my understanding of what it means to conduct responsible and meaningful research as a computing professional.
Entering the module, I expected to gain foundational knowledge in academic research, but I did not anticipate the extent to which it would reshape my thinking about ethics, data, and professional responsibility. Each task, from literature review to research proposal, pushed me to think more critically about my role as a computing professional. Using the “What, So What, Now What” framework by Rolfe et al. (2001), I will reflect on my experiences, challenges, achievements, and why they mattered. I will also articulate a plan for leveraging the skills I have acquired in the real world.
The module opened with a reflective essay on ethics in the age of generative AI. This set the tone for the ethical considerations in all subsequent academic writing. In the first seminar, my tutor emphasised the importance of regular citations in academic writing. The first unit also prioritised peer review of academic writing as we discussed the Association for Computing Machinery (ACM) case studies. Various case studies, such as the Medical Implant Analysis, were explored in depth in the discussions. For instance, John highlighted the importance of ACM principles, such as building robust and secure systems (ACM, 2018). These riveting discussions continued into the second unit.
As the module progressed, I had to choose a topic for both my literature review, from the provided list, and my research proposal. Due to my technical background, I wanted a topic that was both technically engaging and socially impactful. I eventually selected explainable artificial intelligence (XAI) in the context of breast cancer diagnosis in Nigeria. This felt aligned with my long-term interest in AI ethics and healthcare accessibility.
Throughout the RMPP module, I explored various ethical considerations. I explored complex issues such as data privacy, bias in AI, and accountability in statistical reporting. The discussion on improper use of surveys stood out, illustrating how data collected under the guise of research can be weaponised for social manipulation (Cadwalladr and Graham-Harrison, 2018). In this discussion, I explored the manipulation and misuse of sensitive user data by Cambridge Analytica and the Flo app (Méndez Egea, 2021; Tovino, 2019). I reflected on my responsibility as a computing professional to prioritise user privacy.
Another formative moment was engaging with the case study of Abi, a statistical programmer facing the ethical dilemma of presenting conflicting data. It made me reflect on the ease with which data can be framed to support misleading narratives and the moral burden researchers carry (Resnik, 2020). The statistical tasks also helped me see how data interpretation can shape policy and public understanding, which underscored the importance of transparency in data communication (Panneerselvam, 2014).
Throughout, I balanced demanding coursework with full-time work, family life, and another concurrent module. At times, I was overwhelmed, but I kept coming back to my “why”. I am motivated by the desire to contribute to ethical, impactful research and grow as a responsible AI practitioner.
These experiences reshaped how I approach research. I now see research not only as a method for producing knowledge but also as a practice loaded with ethical, social, and legal responsibilities. The ethical discussions helped me understand that decisions made early in the research process, such as how we define variables or choose samples, can have significant consequences for individuals and communities.
The legal lens offered by the module was also revealing. For instance, learning about the UK’s Consumer Protection from Unfair Trading Regulations (GOV.UK, 2008) and Nigeria’s Consumer Protection Act (Bello et al., 2012) helped me understand how misleading data in product research or advertising is not just unethical, but it can be legally actionable. This reinforced my awareness of the importance of honest reporting and transparency in both academic and industry research.
The research proposal component offered an opportunity to bring everything together. For the first time, I had to critically evaluate existing literature, define a viable research question, and select an appropriate methodology. It pushed me to be more deliberate and structured in my thinking. I realised that intense research is built not just on innovation, but on clarity, feasibility, and ethical rigour.
Reflecting on the process of selecting and refining my research topic, I realised it had a more profound impact than I expected. It wasn’t just a task for meeting module requirements; it shaped how I now approach research as a responsible and ethically aware computing professional. Choosing a topic that balanced technical depth with societal relevance taught me how research can serve both innovation and the public good. I became more intentional about aligning research with local context, especially in underrepresented regions like Nigeria, where technology can either bridge or widen healthcare gaps.
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Moving forward, this module has set the standard for how I plan to conduct myself as both a researcher and computing professional. I intend to integrate ethical considerations into every stage of my work, from problem formulation to data collection, analysis, and communication. I am more committed than ever to building technology that is not only functional but fair and transparent.
As I approach my dissertation and consider a future Phd, I will draw on the experience of writing proposals, my improved ability to engage critically with literature, and the statistical skills I developed during this module. I now understand how to design a project that is not only academically sound but also socially meaningful. This module also taught me the value of reflection. I’ve learned to pause and assess not only my academic performance but also my mindset and motivations. This self-awareness will guide me through future challenges, reminding me that success in research requires not only knowledge but also integrity, purpose, and resilience.
ACM (2018) ACM Code of Ethics and Professional Conduct. Available at: https://www.acm.org/code-of-ethics
Bello, K.B., Suleiman, J.B.A. and Danjuma, I. (2012) ‘Perspectives on Consumerism and Consumer Protection Act in Nigeria’, Perspectives, 4(10).
Cadwalladr, C. and Graham-Harrison, E. (2018) Revealed: 50 million Facebook profiles harvested for Cambridge Analytica. The Guardian. Available at: https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election
GOV.UK (2008) GUIDANCE on the UK Regulations (May 2008) implementing the Unfair Commercial Practices Directive. Available at: https://assets.publishing.service.gov.uk/media/5a74d389e5274a3cb28677f4/oft1008.pdf
Panneerselvam, R. (2014) Research Methodology. PHI Learning Pvt. Ltd.
Resnik, D. B. (2020). What is Ethics in Research & Why is it Important? National Institute of Environmental Health Sciences. Retrieved from https://www.niehs.nih.gov/research/resources/bioethics/whatis/index.cfm
Rolfe, G., Freshwater, D. and Jasper, M. (2001) Critical reflection for nursing and the helping professions. Basingstoke, England: Palgrave Macmillan.
e-Portofolio: (https://yemigabriel.github.io/UniEssexMsc/rmpp/)