UGC NET Questions (Paper – 1)

Statement D is wrong because probability sampling typically requires a sampling frame or some representation of the population to ensure known selection probabilities. Statements A, B, C and E are correct: the sampling frame is the list from which samples are drawn, its quality affects representativeness, outdated frames cause coverage errors and an ideal frame covers the entire target population. Therefore, the only wrong statement is D.

Option A:
Option A is incorrect because it also labels A, which correctly defines the sampling frame, as wrong along with D. This misrepresents a basic concept in sampling.

Option B:
Option B is wrong because it groups C with D as wrong, even though C accurately states that outdated frames cause coverage errors. Coverage error is a standard threat to representativeness.

Option C:
Option C is correct because it isolates D as the sole statement inconsistent with probability sampling principles and implicitly accepts A, B, C and E as true.

Option D:
Option D is incorrect because it treats B and E as wrong along with D, despite both B and E properly describing the relationship between frame quality and sample representativeness.

A double-blind design ensures that both participants and the researchers who have contact with them are unaware of which individuals are in the experimental or control group. This reduces expectancy effects, such as participants changing behaviour because they think they are receiving a special treatment, and experimenter bias, where researchers unintentionally influence outcomes. By keeping group assignment concealed from both parties, the design enhances the credibility of observed differences. Therefore, the arrangement described in the stem is correctly called double-blind.

Option A:
Single-blind designs keep group assignment hidden from participants but not from researchers, so experimenter expectations can still influence data collection or interpretation. This makes single-blind less effective than double-blind in controlling expectancy effects, so it does not fully match the stem.

Option B:
Open-label studies are those in which both participants and researchers know who receives the treatment, making them vulnerable to numerous biases. They are not designed to control expectancy effects and therefore are not an appropriate completion.

Option C:
Option C, double-blind, is widely used in clinical trials and psychological experiments to address both participant and experimenter expectations simultaneously. This dual masking corresponds exactly to the description in the question, making it the correct option.

Option D:
Matched-pairs designs pair participants based on similarity in key characteristics before assigning them to different conditions but do not inherently prevent either party from knowing group assignments. Thus, matched-pairs is not the right answer here.

Statements A, B, C and E correctly represent the main features of common attitude scaling techniques. Likert scales use agreement ratings, semantic differential scales use bipolar adjectives and Thurstone scales rely on judges’ weights. These tools generate numerical scores that allow researchers to quantify attitudes for analysis, so E is also correct. Statement D is false because attitude scales are a hallmark of quantitative research and explicitly produce numeric data.

Option A:
Option A is correct because it includes all four true statements and excludes D, which mischaracterises the quantitative nature of attitude scales. It captures both the structural features of the scales and their function in converting subjective attitudes into numerical form.

Option B:
Option B is incomplete as it omits E, failing to highlight that the purpose of these scales is to create data suitable for statistical analysis. Without E, the significance of assigning numbers to attitudes remains implicit rather than explicit.

Option C:
Option C includes B, C and E but leaves out A, so it does not mention Likert scaling, which is one of the most widely used attitude measures. This omission makes the overview of attitude scales incomplete.

Option D:
Option D contains A, C and E but omits B, ignoring semantic differential scales, which are important for measuring connotative meaning. Leaving out this type of scale means the option cannot be considered a full set of correct statements.

Statements A, B, D and E correctly describe why and how sampling is used in research. Sampling helps when studying an entire population is impractical, and a well-drawn sample can yield useful estimates about population parameters. Probability sampling ensures known selection chances, and practical issues such as time and access must be considered in sampling decisions. Statement C is false because convenience samples may be biased and are not guaranteed to be representative.

Option A:
Option A is incomplete because it omits D and E, both of which highlight key aspects of sampling such as probability-based selection and practical constraints. Without these, the combination underplays how representativeness is achieved and what factors shape sampling choices.

Option B:
Option B is correct because it combines A, B, D and E, the set of statements that align with standard sampling principles. It rightly excludes C, which overstates the merits of convenience sampling. The option therefore captures both methodological and practical dimensions of sampling.

Option C:
Option C is incorrect because it includes C, which wrongly claims that convenience sampling always produces representative samples. Convenience samples are often prone to bias, so including C corrupts the otherwise correct set of statements.

Option D:
Option D is wrong because it omits A, failing to mention the basic rationale for using samples rather than censuses. It also does not explicitly recognise that sampling is a response to practical limitations, which is central to its role in research.

The dependent variable represents the effect or outcome that may change as a result of manipulations of the independent variable. It is the main variable of interest whose variation the researcher wishes to explain or predict. Measurements of the dependent variable are compared across groups or conditions to evaluate the impact of the treatment. Thus, the outcome described in the stem is correctly called the dependent variable.

Option A:
The dependent variable is “dependent” in the sense that its values are expected to depend on or be influenced by the independent variable under investigation. In educational experiments, typical dependent variables include achievement scores, attitudes or skills. Because the stem refers to the outcome measured to assess treatment effect, this label is appropriate and correct.

Option B:
A control variable is a factor that the researcher keeps constant to prevent it from confounding the relationship between the independent and dependent variables. It is not the main outcome of interest.

Option C:
A moderator variable affects the strength or direction of the relationship between independent and dependent variables, rather than being the primary outcome. It answers questions about for whom or under what conditions the treatment works.

Option D:
A confounding variable is an uncontrolled factor that influences the dependent variable along with the independent variable, making it difficult to interpret causal effects. It is considered a threat rather than the planned outcome.

Statements A, B, C and D describe central aspects of evaluation and policy research, and F adds an important methodological note. A is true because evaluation research systematically judges programme effectiveness, while B correctly notes that formative evaluation is conducted during implementation to improve it. C is accurate in defining summative evaluation as focusing on end results, and D properly characterises policy research as evidence-oriented. F is also true since both domains often combine qualitative and quantitative methods, whereas E is false because evaluation is not restricted to randomised trials or purely quantitative approaches.

Option A:
Option A omits statement F, thereby neglecting the fact that mixed-methods designs are common and useful in both evaluation and policy research. While A, B, C and D are correct, the absence of F leaves out an important contemporary practice. Hence, this option is incomplete.

Option B:
Option B includes B, C, D and F but leaves out A, ignoring the fundamental role of evaluation research in assessing programme effectiveness. Without A, the combination does not fully capture what evaluation research entails. Therefore it cannot be considered correct.

Option C:
Option C is correct because it lists A, B, C, D and F, providing a comprehensive and accurate picture of what these research types do and how they are conducted. It excludes E, which unjustifiably narrows evaluation research to one design and excludes qualitative data. This combination therefore contains all and only the true statements.

Option D:
Option D wrongly includes statement E and omits B, misrepresenting both the scope of evaluation methods and the concept of formative evaluation. Since it mixes a false statement with correct ones and overlooks a true statement, this option is not acceptable.

Debriefing is an ethical step taken after participants have completed their involvement in a study, especially when deception or incomplete disclosure was used. During debriefing, researchers explain the true purpose of the research, clarify any misleading information and answer participants’ questions. This helps restore trust and ensures that participants leave without misconceptions or distress. Because the stem refers to providing a full explanation of the true purpose after participation, debriefing is the correct term.

Option A:
Anonymity concerns whether researchers can link responses to individual identities and is not about post-study explanations. While both relate to ethics, anonymity does not describe the process mentioned in the question.

Option B:
Confidentiality focuses on protecting participants’ personal information from being disclosed to others, not on giving explanations after the study. Therefore, confidentiality is not the appropriate completion here.

Option C:
Briefing typically refers to giving initial instructions or information before a study or task, which is the opposite temporal sequence to what the stem describes. Since the question is about explanations given after participation, briefing is not correct.

Option D:
Debriefing allows participants to understand why certain procedures were used, including any necessary deception, and offers them an opportunity to withdraw their data if they feel uncomfortable. This process upholds respect for persons and aligns exactly with the description in the stem.

A cross-sequential design involves selecting multiple cohorts of different ages and following them over time, thus combining features of cross-sectional and longitudinal designs. It allows researchers to disentangle age effects, cohort effects and time-of-measurement effects more effectively than using either approach alone. This design is particularly useful in developmental research. Because the stem describes studying several cohorts over time using both cross-sectional and longitudinal elements, cross-sequential design is the correct term.

Option A:
Cross-sectional designs collect data from different age groups at a single point in time, providing a snapshot but not tracking changes within individuals. They do not incorporate repeated measurement over time for the same cohorts. Thus, cross-sectional is not the best completion here.

Option B:
Longitudinal designs follow the same group of participants over an extended period but do not necessarily include multiple age cohorts at the outset. They capture intra-individual change but may confound age and cohort effects. The stem, however, refers to combining several cohorts and following them, which is distinctive of cross-sequential designs.

Option C:
Cross-sequential designs reduce some limitations of purely longitudinal or cross-sectional approaches by allowing researchers to compare patterns across cohorts and time. This structure matches the description in the question precisely, confirming cross-sequential as the appropriate answer.

Option D:
Time series designs involve repeated measurements of a single group over time, often in quasi-experimental contexts, but they usually do not include multiple distinct age cohorts studied concurrently. Therefore, time series is not the correct term for the design described.

Construct validity concerns whether a measurement instrument accurately represents and captures the underlying theoretical construct, such as intelligence or motivation. It is established by examining relationships with other variables, factor structure and theoretical coherence. High construct validity means the test behaves as the theory predicts. Therefore, the type of validity described in the stem is called construct validity.

Option A:
Option A names construct validity, which integrates evidence from multiple sources such as convergent and discriminant validity. It focuses on the match between the abstract concept and its operational indicators. Because the stem refers to measuring the intended theoretical construct, this option is correct.

Option B:
Content validity assesses whether an instrument adequately covers the full range of the domain of content, such as syllabus topics, but does not directly address theoretical constructs beyond the domain. It focuses on item coverage rather than theoretical meaning, so it is not the best completion.

Option C:
Criterion-related validity evaluates how well test scores predict or relate to an external criterion, such as future performance, either concurrently or predictively. While related to accuracy, it is not specifically about alignment with theoretical constructs. Hence, it is not correct here.

Option D:
Face validity refers to the extent to which a test appears to measure what it intends to measure, based on superficial judgment by users or experts. It is more about appearance than deep theoretical accuracy. Therefore, it does not match the stem.

Delimitations are self-imposed boundaries that the researcher chooses in order to narrow down the study to a manageable focus, such as restricting the sample to certain grades or institutions. They indicate what will be included and what will be excluded by design. These boundaries help maintain clarity and feasibility without being imposed by external constraints. Therefore, intentional scope boundaries are correctly called delimitations.

Option A:
Limitations refer to weaknesses or constraints that the researcher cannot fully control, such as time, resources or measurement imperfections. They may restrict the generalisation of findings but are not deliberately chosen boundaries. Hence, limitations are different from the intentionally set scope defined in the stem.

Option B:
Delimitations are decided at the planning stage so that the research remains coherent and realistic with available resources. By specifying these boundaries explicitly, the researcher makes the focus and context of the study transparent. This matches the description in the question, confirming that delimitations is the appropriate term.

Option C:
Assumptions are underlying conditions or statements accepted as true without proof for the purpose of the study, such as the honesty of respondents. They do not define the geographic, temporal or conceptual confines of the research. Thus, assumptions cannot be equated with the boundaries referred to in the stem.

Option D:
Hypotheses are tentative predictions about relationships between variables to be tested empirically. They arise from the research problem and literature rather than defining the limits of the study’s scope. Therefore, hypotheses are not the correct completion.

Statement C is wrong because research questions do not have to be yes/no questions; they may be descriptive, comparative or explanatory in form. Statements A, B, D and E are correct: questions should be clear, hypotheses testable, vagueness leads to design problems and exploratory work may proceed with questions but no formal hypotheses. Therefore, C alone is the incorrect statement here.

Option A:
Option A is wrong because it combines C with D, even though D accurately highlights that vague questions make it difficult to choose appropriate designs and methods. By classifying D as wrong, this option misrepresents a genuine methodological risk.

Option B:
Option B is incorrect because it labels A, which rightly demands clarity and focus, as wrong along with C. This undermines a basic principle of good research question formulation.

Option C:
Option C is correct because it isolates C as the only statement inconsistent with accepted research practice. It acknowledges the diversity of question forms that can guide inquiry.

Option D:
Option D is incorrect because it pairs C with E, wrongly implying that using questions without hypotheses in exploratory work is a mistake. E is actually a true description of how exploratory studies often proceed.

Ethnography involves prolonged engagement with a cultural or social group, often through participant observation and in-depth interviews. The researcher seeks to understand shared meanings, rituals and patterns of interaction from an insider’s perspective. Thick description of the culture is a hallmark of ethnographic work. Therefore, the immersion-based strategy described in the stem is known as ethnography.

Option A:
Grounded theory aims to generate theory from data through constant comparison and theoretical sampling. While it may involve fieldwork, its primary goal is theory construction rather than rich cultural description. Hence, it is not the correct term here.

Option B:
Option B, ethnography, focuses on culture, social practices and collective meanings. The researcher often lives or spends extensive time in the setting to capture natural behaviour. Because the stem emphasises immersion and shared patterns of behaviour, this option is correct.

Option C:
Narrative inquiry concentrates on people’s stories and how they make sense of experiences through narrative form. It does not require long-term immersion in a culture, so it does not match the description.

Option D:
A case study examines a bounded system such as an organisation or programme in depth. While it may overlap with ethnography, it is not defined primarily by cultural immersion and study of shared patterns, so it is not the best completion.

Statements A, B and C distinguish delimitations, limitations and assumptions, and E highlights their reporting value. Delimitations are intentional boundaries set by the researcher, limitations are largely uncontrollable constraints and assumptions are unverified conditions accepted for practical purposes. Statement E is correct because acknowledging limitations and assumptions helps readers judge the scope and strength of conclusions. Statement D is false since reporting delimitations is seen as a mark of transparency, not a weakness.

Option A:
Option A is incomplete because it leaves out statement E, which emphasises why explicit reporting of these elements is vital for interpretation. Without E, the option does not fully convey the role of these concepts in communicating research quality.

Option B:
Option B is correct because it includes all the true statements that both define these terms and explain their interpretive function. It excludes D, which discourages honest reporting, and therefore aligns with good research practice and reporting norms.

Option C:
Option C is incorrect as it incorporates D, which wrongly tells researchers to hide delimitations, and omits A, which accurately defines them. This mixture of a false statement and an omission makes the combination unsatisfactory.

Option D:
Option D leaves out statement B, ignoring the essential idea that limitations are often beyond the researcher’s control. Although A and C are correct and E is true, the absence of B means that the picture of constraints is incomplete.

Option E is also wrong because it includes D, the false claim that delimitations should not be reported, and omits B. A correct option cannot encourage concealment of key design information.

Mixed methods research integrates quantitative and qualitative approaches within one study or a programme of research to capitalise on the strengths of each. Quantitative data can provide breadth and generalisability, while qualitative data offer depth and contextual understanding. Integration can occur at design, data collection, analysis or interpretation stages. Hence, the approach described in the stem is accurately termed mixed methods research.

Option A:
Experimental research refers to designs involving manipulation and control of variables, but it need not combine qualitative and quantitative approaches. It may be purely quantitative, so it does not match the stem’s emphasis on intentional combination.

Option B:
Longitudinal research focuses on repeated observations over time and can be conducted in qualitative, quantitative or mixed ways, but the term itself does not specify method integration. Thus, it is not the best answer here.

Option C:
Option C, mixed methods, acknowledges that different forms of data can complement each other through triangulation, expansion or explanation. This multi-strand design corresponds exactly to the description of combining quantitative and qualitative methods for more complete understanding.

Option D:
Historical research investigates past events using documents and records and may use qualitative or quantitative techniques, but it is not defined by their intentional combination in a single design. Therefore, historical is not appropriate here.

The conclusion section summarises the main findings in relation to the study’s objectives or hypotheses and articulates the key message the researcher wants readers to take away. It often highlights the practical or theoretical implications of the results and may point out suggestions for future research. This section is usually concise and located near the end of the article. Therefore, the part described in the stem is correctly called the conclusion section.

Option A:
The review of literature discusses previous research, theoretical perspectives and gaps before the new study is conducted. It provides background and justification but does not typically present or summarise the study’s own conclusions. Hence, review of literature is not the correct answer.

Option B:
The abstract offers a brief overview of the entire article at the beginning, including purpose, method and main findings, but it is not the internal section that discusses implications and future directions in detail. Thus, abstract is not the best completion.

Option C:
The methodology section explains the design, sampling, instruments and procedures used in the research. It focuses on how the study was carried out rather than on summarising the final outcomes and implications, so methodology does not fit the stem.

Option D:
The conclusion section provides closure by tying the results back to the original problem and emphasising what has been learned, which is exactly what the question is describing.