Introduction
This essay examines the methodological shortcomings evident in the described research project concerning student reactions to online teaching policies at Exploits University. From the perspective of an accounting undergraduate, reliable data collection underpins evidence-based decision-making, much as accurate sampling supports valid financial reporting and policy evaluation. The researcher’s approach relies on non-probability sampling at a single location, interviewing every fourth-year student visiting the dean’s office until reaching 100 participants. Key problems include selection bias, limited representativeness, and overgeneralisation in the published title. These issues undermine the study’s credibility and illustrate broader challenges in business research where flawed methods can distort conclusions applied to accounting and management contexts.
Non-Probability Sampling and Selection Bias
The decision to position herself near the dean’s office and interview every fourth-year student who visits introduces clear selection bias. Students seeking the dean typically do so for specific reasons, such as academic appeals, complaints, or exceptional circumstances. This group does not reflect the wider population of Faculty of Business Administration students, many of whom never interact directly with senior administration. In accounting research, analogous sampling problems arise when studies of financial reporting practices draw only from firms facing regulatory scrutiny, producing results that cannot inform general standards (Saunders et al., 2019).
Furthermore, restricting interviews to fourth-year students narrows the sample further. Earlier-year students may hold different views shaped by varying exposure to online platforms, yet their perspectives remain excluded. The phrase “every fourth year student” appears to target final-year undergraduates exclusively, compounding the bias. Consequently, findings risk capturing only the experiences of a self-selecting and demographically narrow cohort rather than the intended population.
Lack of Representativeness and Generalisation Issues
Even with 100 completed interviews, representativeness remains questionable. Probability sampling techniques, such as simple random or stratified sampling across all year groups and departments, would have offered every student a known chance of inclusion. The convenience-based method employed here violates this principle, as location and timing dictate participation. Accounting students learn early that sample frames must encompass the full population to support inferences, whether analysing audit populations or surveying management accounting practices (Bryman, 2016).
The published title claims coverage of “faculty of business administration students” without qualification. This overgeneralisation misleads readers by implying broader applicability than the data warrant. In professional accounting settings, similar misrepresentations appear in internal surveys used to justify system changes; when samples exclude key user groups, resulting policies often fail to address widespread needs. The researcher’s approach therefore exemplifies how convenience sampling can produce internally coherent yet externally invalid results.
Implications for Research Validity in Business Contexts
From an accounting standpoint, validity concerns extend beyond academic grading to practical decision-making. Online teaching policies influence resource allocation, student performance metrics, and institutional funding claims—areas where accounting graduates frequently contribute through budgeting and performance analysis. Data derived from biased samples may lead administrators to adopt platforms or procedures that satisfy only vocal minorities.
Additionally, the single-site, time-bound collection period introduces temporal bias. Student attitudes towards online learning fluctuate with assessment deadlines, technical outages, or external events. Capturing opinions solely from those visiting the dean during one period limits insight into evolving reactions. Robust accounting research typically employs multiple data collection points or longitudinal designs to mitigate such limitations, supporting more stable conclusions (Saunders et al., 2019).
Conclusion
The researcher’s reliance on convenience sampling at the dean’s office, restriction to fourth-year visitors, and subsequent overgeneralisation in publication title render the study’s findings unreliable for the stated population. These flaws highlight fundamental sampling principles essential to both academic inquiry and professional accounting practice. Improved designs incorporating probability methods and broader inclusion criteria would yield more credible evidence capable of informing university policy without risking misrepresentation of diverse student experiences.
References
- Bryman, A. (2016) Social Research Methods. 5th edn. Oxford: Oxford University Press.
- Saunders, M., Lewis, P. and Thornhill, A. (2019) Research Methods for Business Students. 8th edn. Harlow: Pearson.
