UGC NET Questions (Paper – 1)

Triangulation involves combining different methods, investigators, theories or data sources to study the same phenomenon. When these independent strands of evidence converge on similar conclusions, confidence in the findings increases, enhancing credibility and trustworthiness.

Option A:
Option A suggests reducing data, whereas triangulation often increases data because more than one method or source is used.

Option B:
Option B is correct as it emphasizes corroboration of findings across methods or sources. This cross-checking helps to offset the limitations of any single approach.

Option C:
Option C restricts analysis to numerical data, which is contrary to the qualitative aspects often central to triangulation.

Option D:
Option D proposes avoiding comparison, while triangulation explicitly involves comparing evidence from different angles.

Triangulation enhances the credibility and validity of research conclusions by combining different approaches. Researchers may use multiple data collection methods, such as interviews, observations and documents, or draw information from different sources. When evidence from these diverse streams converges, confidence in the findings increases. Thus triangulation is fundamentally about cross checking through methodological or data diversity.

Option A:
Option A refers to using only one instrument, which is the opposite of triangulation. Reliance on a single tool may leave findings vulnerable to specific biases or limitations.

Option B:
Option B correctly highlights the deliberate use of multiple methods or sources to confirm patterns. This strategy is frequently recommended in qualitative and mixed methods research to improve trustworthiness and depth of understanding.

Option C:
Option C suggests avoiding comparison between data types, which neglects the real purpose of triangulation. Comparing and integrating findings from different sources is central to this technique.

Option D:
Option D restricts the study to one theoretical perspective, which may narrow interpretation. Triangulation often benefits from multiple perspectives to enrich analysis, although theoretical triangulation is only one form among several.

Triangulation involves combining multiple data sources, methods, theoretical perspectives or investigators to study the same phenomenon. The rationale is that if different approaches converge on similar conclusions, confidence in the findings increases. Triangulation can be methodological (using surveys and interviews), data-based (using data from different times or settings) or investigator-based (having multiple researchers analyse the data). Because the stem highlights using multiple methods or sources to enhance credibility, it is describing triangulation.

Option A:
Standardisation refers to making procedures uniform across participants or settings, such as using the same instructions or instruments, to reduce variability and bias. While helpful for reliability, it does not by itself involve combining multiple sources or methods. Therefore, standardisation is not the right term for the process described in the stem.

Option B:
Triangulation helps offset the weaknesses of one method with the strengths of another, providing a more nuanced and robust understanding of the research problem. For example, quantitative survey data might be complemented by qualitative interviews that explain underlying reasons. This deliberate use of multiple approaches to reinforce credibility is exactly what the question refers to, making triangulation the correct answer.

Option C:
Stratification is a sampling procedure in which the population is divided into homogeneous subgroups (strata) and samples are drawn from each. Its purpose is to ensure adequate representation of subgroups, not to combine diverse methods or sources for credibility. Consequently, stratification does not fit the description given.

Option D:
Randomisation is the process of assigning participants to groups purely by chance, usually to control for confounding variables in experiments. While it contributes to internal validity, it does not involve the use of multiple methods or investigators as triangulation does. Hence, randomisation is not the appropriate completion here.

Triangulation involves deliberately combining different methods, data sources, investigators or theoretical perspectives to study the same phenomenon. When findings converge across these diverse approaches, confidence in their accuracy increases. Triangulation can reduce method-specific biases and provide a more comprehensive understanding. Thus, the practice of using multiple forms of evidence to cross-check results is correctly known as triangulation.

Option A:
Standardisation refers to keeping procedures and instructions consistent for all participants to control variability, but it does not necessarily involve multiple methods or sources.

Option B:
Triangulation can include method triangulation (e.g., interviews plus observation), data triangulation (different times or groups) and investigator triangulation (multiple researchers), all aimed at corroborating evidence. This multi-angle approach matches the stem’s emphasis on cross-checking findings, so this option is correct.

Option C:
Randomisation assigns participants to conditions by chance to control for selection bias, which is distinct from validating results via diverse evidence.

Option D:
Extrapolation means extending findings beyond the studied conditions or populations, and while it relies on strong evidence, it is not itself the process of collecting convergent evidence from multiple sources.

Triangulation involves combining different methods, sources, investigators or theoretical perspectives to cross-check findings. When similar results emerge from diverse lines of evidence, confidence in the conclusions increases. This strategy is especially valued in qualitative research but can be used in mixed methods as well. Thus, the practice described in the stem is called triangulation.

Option A:
Standardisation refers to applying consistent procedures and instructions across participants, which reduces variability but does not necessarily involve multiple sources of evidence.

Option B:
Randomisation is a technique for assigning participants to groups or selecting samples by chance to control bias; it is distinct from corroborating results with multiple approaches.

Option C:
Triangulation might include, for example, combining interviews, observations and document analysis to study classroom interaction. If all three sources point to similar themes, the findings are considered more credible. This multi-angle confirmation is exactly what the stem highlights, making this option correct.

Option D:
Stratification refers to dividing a population into subgroups for sampling and does not inherently involve using multiple methods to study the same phenomenon.