UGC NET Questions (Paper – 1)

An institutional review board (IRB) or ethics committee is responsible for examining research proposals to ensure that risks to participants are minimised, benefits are reasonable and ethical principles such as respect, beneficence and justice are upheld. It has authority to approve, require modifications to or disapprove studies. IRBs play a crucial role in protecting vulnerable populations and maintaining public trust in research. Therefore, the committee described in the stem is correctly called an institutional review board.

Option A:
Institutional review boards are typically established within universities, hospitals or research organisations and operate under formal guidelines and regulations. They review consent procedures, safeguards for confidentiality and risk–benefit analyses before granting approval. This oversight role fits the stem’s description, so this option is correct.

Option B:
An academic review board might focus more broadly on programme quality or curriculum issues and is not specifically charged with evaluating ethical aspects of research involving human participants.

Option C:
Advisory committees provide guidance or recommendations but may lack the formal regulatory authority of an IRB to approve or reject studies based on ethical criteria.

Option D:
Evaluation boards may assess project outcomes or performance rather than pre-emptive ethical compliance, so they are not the correct term here.

A standardised instrument is one that has been constructed according to established procedures, with documented reliability and validity, and often with norms based on large representative samples. Such tests come with manuals describing administration, scoring and interpretation. Using standardised instruments allows researchers to compare scores with known benchmarks. Because the stem describes a test already developed, validated and normed, it is clearly referring to a standardised instrument.

Option A:
Teacher-made tests are locally developed by teachers for use in specific classes or courses and may not have undergone rigorous psychometric evaluation or norming on large samples. While useful for classroom decisions, they lack the standardisation described in the stem. Therefore, teacher-made is not the correct completion.

Option B:
Standardised instruments provide consistent procedures across administrators and contexts, enhancing comparability and reducing subjective variation. Their technical properties are well documented, which supports more confident interpretation of results. This matches the description in the question, confirming standardised as the appropriate answer.

Option C:
Informal tools are loosely structured methods such as casual observations or unstructured interviews without fixed scoring rules. They may help in exploratory understanding but do not possess the formal validation and norms associated with standardised instruments. Hence, informal is not suitable here.

Option D:
Projective tests invite respondents to interpret ambiguous stimuli, with their responses believed to project underlying motives or attitudes, and are common in clinical settings. While some projective tests may be standardised, the term projective alone does not necessarily imply prior validation and norming as highlighted in the stem. Thus, projective is not the best option.

Basic research is designed primarily to extend theoretical understanding of fundamental principles. It is driven by curiosity about how phenomena work rather than by the direct need to solve an immediate practical problem. The findings of basic research often provide the conceptual foundation on which later applied studies build interventions. Therefore, a study focused on theory refinement without immediate application is best described as basic research.

Option A:
Basic research explores underlying mechanisms and relationships, such as how learning occurs in the brain or how motivation is structured, even when there is no direct classroom intervention planned. Over time, these insights may inform practice, but the initial intention is theoretical. This matches the stem’s emphasis on developing or refining theory, making this option correct.

Option B:
Applied research concentrates on using existing theories and findings to address specific practical problems, such as improving a particular reading programme. Because the stem explicitly downplays immediate application, applied research does not fit.

Option C:
Action research is carried out by practitioners like teachers to solve context-specific problems and improve their own practice. It is highly practical and local, which is the opposite of the theoretically oriented aim mentioned.

Option D:
Evaluative research focuses on judging the merit or worth of programmes and policies, typically using criteria such as effectiveness or efficiency. Although it may use theory, its primary goal is assessment, not theory development.

The references section of a research report contains detailed bibliographic information for all sources that have been cited in the text. Its purpose is to enable readers to locate the original works and to acknowledge intellectual debts accurately. The items are usually arranged in a standardised format, such as APA or MLA style. Because the stem specifies works that have actually been cited in the text, it is referring to the references list.

Option A:
An appendix contains supplementary material such as questionnaires, lengthy tables or additional analyses that support the study but are not essential to the main narrative. It does not primarily list the sources cited in the text. Therefore, appendix is not the correct answer.

Option B:
A bibliography may include not only works cited in the report but also other relevant readings that were consulted but not directly referenced. In many styles, it is broader than the references list described in the stem. Since the question emphasises only those works actually cited, references is more accurate than bibliography.

Option C:
Footnotes appear at the bottom of pages to provide additional comments, clarifications or source notes related to specific points in the text. While they may occasionally include brief citations, they do not constitute the organised list of all cited works at the end of the report. Hence, footnotes cannot complete the stem correctly.

Option D:
The references section is an essential part of scholarly writing, demonstrating transparency about sources and enabling verification of evidence. Its focus on cited works aligns exactly with the description given in the stem, making references the appropriate completion.

Statement E is the only wrong statement because random assignment actually strengthens internal validity by equalising groups on extraneous variables. History, maturation, testing and instrumentation are all recognised threats that can introduce alternative explanations for observed changes if not controlled. Thus, A, B, C and D accurately name and describe typical threats, while E reverses the protective role of random assignment.

Option A:
Option A is incorrect because it groups A with E as wrong, even though A correctly defines history as external events occurring during the study period. Misclassifying A undermines the standard taxonomy of threats.

Option B:
Option B is also wrong because it treats B along with E as incorrect, even though B adequately describes maturation as internal changes over time. Including B among wrong statements disrupts the understanding of developmental influences on participants.

Option C:
Option C is correct because it isolates E, the statement that conflicts with experimental logic, and implicitly affirms the accuracy of A, B, C and D. It recognises that random assignment is a remedy, not a threat.

Option D:
Option D is incorrect because it pairs C with E, even though C correctly identifies testing effects. By labelling C as wrong, this option denies a well-acknowledged validity threat.

A counterbalanced design systematically varies the order in which treatments are administered so that each treatment appears in each position equally often across participants. This procedure helps control for order and carryover effects that could confound the results of repeated-measures experiments. By distributing potential order effects evenly, researchers can attribute observed differences more confidently to the treatments themselves. Because the stem describes using every possible order of treatments equally often, counterbalanced design is the correct answer.

Option A:
Matched-groups designs involve pairing participants on certain characteristics and then assigning members of each pair to different groups, reducing variability between groups but not directly addressing order effects in repeated measures. Thus, matched groups is not the appropriate completion.

Option B:
Counterbalancing ensures that practice, fatigue or other sequence-related influences are not confounded with specific treatments. It is especially valuable when the same participants receive multiple conditions. The stem’s emphasis on controlling order effects by using all possible orders aligns exactly with this strategy, confirming counterbalanced as the right term.

Option C:
Factorial designs study the effects of two or more independent variables simultaneously, examining both main effects and interactions. They concern the structure of independent variables rather than the order of administration in repeated measures. Hence, factorial design is not suitable here.

Option D:
Single-subject designs focus on repeated observations of a small number of participants, often using AB or ABA patterns, and may or may not involve counterbalancing. The term single-subject alone does not capture the systematic variation in treatment order described in the stem. Therefore, single-subject is not the correct answer.

The Indian Council of Social Science Research (ICSSR) is a key national body dedicated to promoting research in disciplines such as education, sociology, economics and political science. It provides project grants, fellowships and support for research infrastructure. ICSSR also encourages publication and dissemination of social science findings. Hence, the agency described in the stem is ICSSR.

Option A:
AICTE primarily regulates and supports technical and management education institutions rather than focusing specifically on funding social science research projects through competitive grants. While it may support some initiatives, it is not the main social science funding body mentioned.

Option B:
ISRO is India’s space research organisation and funds projects related to space science and technology, not general social science research. Therefore, it does not match the description.

Option C:
ICMR is concerned with medical and health-related research, including public health, and while it funds many important projects, its core mandate is not social science in general.

Option D:
ICSSR specifically provides financial assistance and guidance to social science researchers, making it the correct answer for a question about national-level support for this field.

Statement C is wrong because correlation alone does not justify causal conclusions; without establishing time order and ruling out alternative explanations, causal claims are premature. Statements A, B, D and E are correct: positive correlation indicates a tendency for variables to move together, zero correlation suggests no linear relationship, causal claims need stronger evidence and confusing correlation with causation can misguide policy. Hence, C alone is the incorrect statement.

Option A:
Option A is incorrect because it combines A, which is true, with C as wrong, implying both are incorrect. This would deny the standard interpretation of positive correlation.

Option B:
Option B is also wrong as it labels B, a correct definition of zero correlation in the linear sense, as incorrect along with C. Treating B as wrong would confuse interpretation of correlation coefficients.

Option C:
Option C is incorrect since it includes D, which correctly notes that causal claims require more than correlation. Grouping D with C misrepresents the conditions for causal inference.

Option D:
Option D is correct because it isolates C as the only flawed statement and acknowledges implicitly that the others warn appropriately about the limits of correlational evidence.

Systematic sampling involves arranging the population in some order, choosing a random starting point and then selecting every kth element, where k is the sampling interval determined by the ratio of population size to desired sample size. This method is simpler to implement than simple random sampling while still maintaining an element of randomness. Because the stem explicitly mentions selecting every kth element after a random start, it describes systematic sampling.

Option A:
Cluster sampling focuses on selecting entire groups or clusters, such as schools or classes, often for reasons of cost and convenience. It does not rely on selecting every kth element from a list, so it does not match the feature described in the question.

Option B:
Systematic sampling ensures that the sample is spread relatively evenly across the ordered list, which can be advantageous when the list has no hidden periodicity that coincides with the sampling interval. The process of choosing a random start and then every kth case corresponds exactly to the stem’s description, confirming systematic as the correct answer.

Option C:
Quota sampling is a non-probability method in which the researcher fills pre-specified quotas for particular subgroups, often using convenience within each subgroup. It does not involve selecting elements at a fixed interval from a list and does not rely on random starts. Therefore, quota is not an appropriate answer here.

Option D:
Purposive sampling involves deliberately choosing cases judged to be particularly informative rather than following a fixed interval rule. It is commonly used in qualitative research and does not follow the mechanical pattern described in the stem. Hence, purposive sampling is not correct for this question.

Statements A, B, C and E capture the practical, cyclical and developmental nature of action research. It is carried out in the teacher’s own setting to solve immediate problems, uses a cycle of planning, action, observation and reflection, and supports professional growth and sharing of insights with colleagues. Statement D is false because action research is usually context-specific and does not necessarily seek grand universal theories. Therefore, the combination that includes A, B, C and E and excludes D is the only completely correct set.

Option A:
Option A is incorrect because it omits statement E, which rightly points out that sharing action research findings can improve institutional practices. Leaving out E underestimates the collaborative and school-improvement potential of action research. Although A, B and C are true, the set is incomplete.

Option B:
Option B is correct as it includes all four true statements A, B, C and E while excluding D, which wrongly claims that action research must pursue universal theory. This option reflects the local, problem-focused and reflective character of teacher action research.

Option C:
Option C is wrong because it includes statement D, which misrepresents the aims of action research, and excludes A, which correctly notes the focus on immediate contextual problems. Mixing a false statement with some true ones means this option cannot be accepted.

Option D:
Option D is incorrect because it again incorporates D, the false statement about universal theories, and also omits B, which is important for describing the cyclic nature of action research. As a result, the combination is both conceptually and descriptively flawed.

Statements A, C and D correctly describe correlational research and the correlation coefficient, while B and E are false. Correlational studies examine relationships without experimental manipulation, positive correlations show variables moving in the same direction and correlation coefficients usually vary between –1 and +1. However, a high correlation does not by itself establish causation, and zero correlation may occur even when measurements are accurate, for example when there is genuinely no linear relationship.

Option A:
Option A is correct because it includes all the true statements and excludes B and E, which confuse correlation with causation and misinterpret zero correlation. It provides a clear picture of what correlational research reveals and what its limits are.

Option B:
Option B wrongly includes B, which claims that high correlation implies causation, a common but serious misunderstanding in research interpretation. Because it accepts this false statement, the whole combination is invalid.

Option C:
Option C includes both B and C, thereby mixing a correct statement about positive correlation with an incorrect causal claim. The presence of B prevents this option from being correct, even though it also contains true statements.

Option D:
Option D adds E, the assertion that zero correlation always signals measurement error, which is false. Zero correlation can reflect a true lack of linear relationship, so this option misinterprets the meaning of r = 0.

Option E combines A and D with E, again bringing in the false idea that zero correlation must be due to error. This contaminates an otherwise partially correct set and makes the option unacceptable.

Longitudinal studies involve repeated observations of the same individuals, groups or phenomena over an extended period. This design allows researchers to analyse changes, trends and developmental patterns that cannot be seen in single time-point studies. It is especially important in education, psychology and health research for understanding growth and long-term effects. Thus, a design collecting data from the same participants at multiple times is correctly termed a longitudinal study.

Option A:
Cross-sectional studies take a snapshot at one time point and cannot track individual changes over time. They may compare different groups but do not revisit the same participants, so cross-sectional does not match the stem.

Option B:
Option B, longitudinal, highlights that the time dimension is essential and that repeated measurements of the same units are central to the design. This fits the description of studying change over time, making this option correct.

Option C:
Experimental designs focus on manipulation and control; they may be conducted in cross-sectional or longitudinal formats, but experiment is not defined solely by repeated measurement of the same participants. Hence, experimental is not the best completion.

Option D:
Causal-comparative (ex post facto) designs compare existing groups after an outcome has occurred and do not necessarily involve repeated measurements across time. Therefore, they are not the correct answer here.

Grounded theory is a qualitative approach in which researchers collect and analyse data simultaneously, allowing concepts and categories to emerge from the data rather than imposing a preconceived theory. Through constant comparison and theoretical sampling, they refine these categories into a substantive theory that is grounded in participants’ experiences. The emphasis is on building theory inductively rather than testing an existing framework. Because the stem describes developing theory inductively from field data, it is referring to grounded theory.

Option A:
Grounded theory seeks to move beyond rich description to generate explanatory frameworks that account for patterns in the data. Researchers continually compare incidents, refine codes and write memos to articulate emerging theoretical relationships. This iterative, inductive process matches the stem’s focus on theory development from field data, making grounded theory the correct completion.

Option B:
Phenomenology aims to describe the essence of individuals’ lived experiences of a phenomenon, often bracketing the researcher’s preconceptions. While it analyses qualitative data, its goal is not primarily to build a theory but to capture experiential meanings. Therefore, phenomenology does not fit the description of inductive theory development.

Option C:
Case study research involves an in-depth investigation of a bounded system such as an individual, group or institution. It may use multiple sources of data and can be descriptive, explanatory or exploratory, but it does not necessarily aim to produce a formal theory in the specific grounded-theory sense. Hence, case study is not the best label here.

Option D:
Narrative research focuses on the stories individuals tell about their lives and experiences and analyses these narratives for structure and content. Although it may generate insights and concepts, its primary orientation is toward narrative construction rather than systematic theory building from constant comparison. Thus, narrative research is not the correct term.

A nominal scale involves categorising observations into distinct groups that have no inherent order, such as gender, religion or blood type. The categories are mutually exclusive and exhaustive but cannot be ranked meaningfully. Only counts and mode are appropriate descriptive measures. Therefore, classifying respondents by gender uses a nominal scale.

Option A:
Nominal measurement simply names or labels categories without implying that one category is greater or less than another. In the gender example, categories like male, female or other do not fall into a natural order, confirming that the scale is nominal and making this option correct.

Option B:
An ordinal scale ranks categories in terms of order, such as low, medium and high, but does not guarantee equal intervals; this is not what is happening in simple gender classification.

Option C:
Interval scales have equal intervals and allow meaningful differences, as in temperature measured in degrees, but do not apply to purely categorical variables like gender.

Option D:
Ratio scales add a true zero point and support meaningful ratios, such as weight or height; these properties are irrelevant to categorising gender, so ratio is not the correct answer.

Statements A, B, C and D clearly differentiate descriptive from inferential statistics, and F explains how they are used in practice. A is true because descriptive statistics summarise raw data, while B correctly states that inferential statistics support generalisation. C is accurate in classifying central tendency and dispersion as descriptive, and D correctly labels t-tests and ANOVA as inferential tools. F is also true, as most research reports present both descriptive summaries and inferential tests, whereas E is false because descriptive statistics remain important even when inferential methods are applied.

Option A:
Option A omits statement F, ignoring the common practice of combining descriptive and inferential statistics to present a complete analysis. Although A, B, C and D are correct, missing F makes the option incomplete.

Option B:
Option B leaves out statement A and therefore loses the basic definition of descriptive statistics, even though it captures some roles of inferential analysis and joint reporting. Without A, the explanation is not comprehensive, making this option unsuitable.

Option C:
Option C excludes statement B, failing to address the core purpose of inferential statistics: generalising from sample to population. Even with A, C, D and F included, the absence of B means that the description of inferential statistics is incomplete.

Option D:
Option D is correct because it includes A, B, C, D and F, covering both the definitions and typical uses of descriptive and inferential statistics. It excludes E, which incorrectly suggests that descriptive statistics become redundant once inferential statistics are used. Hence, this combination presents all and only the true statements.