UGC NET Questions (Paper – 1)

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 D correctly distinguish internal and external validity and the roles of random assignment and random sampling. Internal validity is about attributing effects to the treatment rather than confounds, while external validity is about generalising beyond the study context. Random assignment strengthens internal validity by equalising extraneous variables across groups, and random sampling supports external validity by making the sample more representative. Statement E is false because a study can have strong internal validity yet limited generalisability, so high internal validity does not guarantee high external validity.

Option A:
Option A is incomplete because it omits D, which correctly highlights the relation between random sampling and external validity. Without D, the link between sampling and generalisability is not fully represented.

Option B:
Option B leaves out statement A, overlooking the fundamental definition of internal validity as ruling out alternative explanations. Even though B and D address external validity and sampling, omitting A weakens the conceptual pair.

Option C:
Option C is correct because it includes all four accurate statements about internal and external validity and their methodological supports. It deliberately excludes E, which wrongly assumes that internal and external validity always go together. Thus this combination precisely reflects textbook distinctions.

Option D:
Option D is incorrect because it includes E, which overstates the relationship between internal and external validity, and it omits B, which defines external validity itself. This mixture of omission and error makes the option unacceptable.

Option E is also wrong because it incorporates E, the false automatic link between internal and external validity. A correct option must not contain this overgeneralisation.

Statements A, B, C and E accurately depict quasi-experimental designs. They frequently use intact groups without random assignment, are practical where full control is not feasible, and accept that such designs typically face greater threats to internal validity than true experiments. Statement D is false because many quasi-experiments in fact employ pre-tests and comparison groups to strengthen inferences. Therefore, the combination that includes A, B, C and E and excludes D is correct.

Option A:
Option A is incomplete because it does not include E, thereby omitting the important point that quasi-experiments may suffer more from internal validity threats. Without E, the description lacks a key limitation of this design type.

Option B:
Option B is incorrect because it includes D, which wrongly claims that quasi-experiments never use pre-tests or comparison groups. Including D contradicts common quasi-experimental formats like non-equivalent control group designs.

Option C:
Option C is correct because it recognises the typical lack of random assignment, the use of intact groups, the practical and ethical motivations for quasi-experiments and their higher vulnerability to validity threats. It also properly rejects D as inaccurate.

Option D:
Option D is wrong since it accepts D and omits A. By ignoring the central feature that quasi-experiments lack random assignment and by endorsing the incorrect statement that they never use pre-tests or comparison groups, this option misrepresents the design.

The control group is included in an experiment to provide a baseline against which the effects of the experimental treatment can be judged. It either receives no treatment or a standard condition, while the experimental group receives the new or varied treatment. Any differences in outcomes between the groups can then be attributed more confidently to the manipulation of the independent variable. Thus, the group described in the stem is correctly called the control group.

Option A:
Control groups help isolate the effect of the independent variable by holding all other conditions as constant as possible. They strengthen internal validity by allowing researchers to rule out alternative explanations such as maturation or history. This critical comparison role matches the definition given in the question.

Option B:
The experimental group is the set of participants that receives the treatment or intervention under investigation. It does not serve as the baseline but rather as the group whose outcomes are compared with those of the control group. Hence, experimental group is not the correct completion.

Option C:
Random group is not a standard term in experimental design; randomness refers instead to the method of assigning participants to groups. While random assignment is important, it does not name the specific group that receives no or standard treatment. Therefore, random group is inappropriate here.

Option D:
A matched group refers to participants paired or grouped based on similar characteristics to control for confounding variables, but such groups may still be either experimental or control groups. The term does not by itself identify the no-treatment comparison group described in the stem.

A research design provides an overall plan that connects research questions with methods of data collection and analysis. It specifies the type of study, sampling strategy, tools, timing and procedures to be used. By planning these elements coherently, the design enhances internal validity and feasibility, ensuring that the study can meaningfully address its questions. Therefore it is often called a blueprint of research.

Option A:
Option A suggests random decisions, which contradict the idea of design as planned and systematic. Randomness at the planning stage can lead to weak or invalid studies.

Option B:
Option B correctly highlights that design is a logical plan linking questions, data and analysis. It underlines the purpose of design as providing structure and direction to the study before implementation begins.

Option C:
Option C confuses design with bibliography. References are important but are not a plan of procedures.

Option D:
Option D refers to raw data, which are outcomes of research activities, not the plan that precedes them.

A control variable is a factor that the researcher deliberately keeps constant across conditions or statistically adjusts for during analysis. By doing so, its potential influence on the dependent variable is minimised, allowing clearer interpretation of the effect of the independent variable. Control variables are chosen because they are known or suspected to be related to the outcome. Therefore, the constant factor described in the stem is correctly called a control variable.

Option A:
Control variables might include factors such as prior achievement, age or socioeconomic status when these could influence outcomes. By holding these factors constant, the researcher reduces alternative explanations for observed differences. This aligns with the stem’s emphasis on preventing confounding, making this option correct.

Option B:
A moderator variable interacts with the independent variable to change the strength or direction of its effect on the dependent variable. It is not typically held constant; rather, its variability is studied.

Option C:
A mediating variable explains the mechanism through which the independent variable affects the dependent variable, forming part of the causal pathway, not something to be simply held constant.

Option D:
A random variable is a statistical concept referring to a variable whose values result from random phenomena. It is not the term used in research design for a variable that is intentionally controlled.

A research design links research questions with appropriate methods of data collection and analysis. It lays down what will be done, when, where and how, ensuring internal coherence and feasibility. This planned structure helps in controlling extraneous factors and enhances the credibility of conclusions. Therefore, it is often described as the blueprint of the study.

Option A:
Option A implies randomness, which contradicts the deliberate planning needed for scientific inquiry. Random activity can lead to weak or invalid findings.

Option B:
Option B is correct because it captures the idea of a systematic plan that guides the entire research process. It emphasizes both data collection and analysis in relation to the questions posed.

Option C:
Option C confuses design with bibliography. References support the background and justification but do not constitute the design of procedures.

Option D:
Option D narrows design to sampling only, ignoring other vital components such as instruments, data sources and analytical strategies.

The history threat to internal validity arises when events outside the experiment, such as policy changes or natural disasters, occur between measurements and influence participants’ responses. These events are not part of the planned treatment but can mimic or obscure treatment effects. If not controlled, they make it difficult to attribute changes solely to the intervention. Thus, the external event effect described in the stem is known as history.

Option A:
Maturation refers to natural changes within participants over time, such as ageing, fatigue or learning. These are internal to the individuals rather than external events affecting the group. Therefore, maturation is a different threat from the one described.

Option B:
Option B, history, focuses on time-related external events that coincide with the experiment and influence outcomes. For example, a media campaign or institutional change during the study period could create a history effect. Because the stem highlights external events between pre-test and post-test, this option is correct.

Option C:
Testing effects arise when taking a test influences performance on later administrations of the same test, such as through practice or sensitisation. This does not involve outside events, so it does not match the question.

Option D:
Instrumentation refers to changes in measurement instruments or observers over time, which can alter scores independently of the treatment. It is another threat to internal validity but not the one defined in the stem.

A quasi-experimental design includes an active intervention or manipulation of an independent variable but does not use full random assignment of participants to groups. As a result, groups may differ on important characteristics before the treatment, making causal inferences more tentative. Such designs are common in real-world settings where randomisation is impractical or unethical. Therefore, the design described in the stem is known as quasi-experimental.

Option A:
Pre-experimental designs often involve one-group pre-test–post-test structures or static group comparisons with very weak control of threats to internal validity. They are usually considered methodologically weaker than quasi-experiments and may lack proper comparison groups. So pre-experimental is not the best completion.

Option B:
Correlational designs examine relationships between variables without manipulation, using naturally occurring variation. They do not involve assigning a treatment or intervention, so they do not match the stem.

Option C:
Ex post facto designs investigate potential causes after outcomes have occurred, without manipulating the independent variable. They are retrospective and non-manipulative, which differs from the active intervention element in quasi-experiments. Hence, ex post facto is not appropriate here.

Option D:
Option D, quasi-experimental design, specifically denotes studies where the researcher manipulates the treatment but uses existing or non-random groups such as intact classes. This fits the question exactly, so it is correct.

Internal validity refers to the extent to which a study’s design and execution permit a clear causal interpretation of the relationship between independent and dependent variables. High internal validity means that alternative explanations, such as the influence of extraneous variables or selection biases, have been effectively controlled or ruled out. In experimental research, techniques like random assignment, control groups and standardised procedures are used to enhance internal validity. Since the stem focuses on confidently attributing differences in the dependent variable to the treatment, it is explicitly referring to internal validity.

Option A:
External validity is concerned with the generalisability of findings to other populations, settings and times, not with the internal logic of causal inference within the study itself. A study could have strong internal validity but limited external validity if the sample or conditions are highly specialized. Because the stem emphasises attribution of observed differences to the treatment within the experiment, external validity is not the correct answer.

Option B:
Reliability addresses the consistency or stability of scores obtained with a measurement tool, rather than whether those scores are due to the intended experimental manipulation. A measure can be reliable but still be influenced by confounding factors that threaten causal inference. Therefore, reliability does not capture the idea described in the question.

Option C:
Objectivity relates to the freedom of measurements and interpretations from subjective bias on the part of the researcher or assessor. While objectivity can support internal validity, it does not by itself guarantee that observed differences are due to manipulation of the independent variable. As such, objectivity is not the term that best fits the stem.

Option D:
Internal validity is strengthened when potential threats, such as maturation, history, instrumentation changes and selection effects, are addressed in the design. By minimizing these threats, the researcher can argue more convincingly that changes in the dependent variable are caused by the treatment. This reasoning matches the description in the stem, making internal validity the appropriate completion.

Random assignment uses chance procedures to place participants into different experimental conditions so that groups are equivalent on both known and unknown characteristics at the outset. It strengthens internal validity by making it more likely that observed differences in outcomes are due to the treatment rather than pre-existing differences. This process is distinct from random sampling, which concerns how participants are chosen from the population. Therefore, the term that correctly completes the stem is random assignment.

Option A:
Sampling refers to selecting individuals from the population for inclusion in the study, which occurs before participants are divided into groups. It addresses external validity rather than internal group equivalence.

Option B:
Allocation is a general word for distributing participants among conditions and may or may not be done randomly; the stem emphasises assignment “by chance,” which points specifically to random assignment.

Option C:
Random assignment ensures that every participant has an equal probability of being in any group, reducing systematic bias and supporting causal inference. Because the stem describes this process in experimental research, assignment is the appropriate completion and this option is correct.

Option D:
Randomisation is a broader term for using chance procedures in research (and may include random assignment), but the specific term for placing participants into experimental/control groups is random assignment, which is what the stem targets.

Control variables are factors that the researcher deliberately holds constant or accounts for so that they do not confound the relationship between the independent and dependent variables. By stabilising these variables, the researcher reduces alternative explanations for observed effects. This enhances the internal validity of the experiment. Because the stem refers to variables kept constant to prevent them from influencing outcomes, it is describing control variables.

Option A:
Independent variables are intentionally manipulated to assess their impact on outcomes, not held steady. Their variation is central to testing hypotheses about cause and effect. Thus, independent variables are the opposite of what the stem indicates and cannot be the correct answer.

Option B:
Dependent variables are the outcomes measured to see whether they change as a result of the independent variable. They are expected to vary and are not kept constant. Since the question is about variables that are purposely held constant, dependent is not appropriate.

Option C:
A moderator variable influences the strength or direction of the relationship between independent and dependent variables, helping to specify “when” or “for whom” an effect is observed. Although researchers may sometimes create conditions based on moderators, the classic notion of control variables is more directly about holding factors constant. Therefore, moderator does not fit the stem’s description.

Option D:
Control variables are chosen and managed to remove their potential influence, such as keeping room temperature constant in a cognitive experiment. This deliberate stabilisation ensures that observed differences in the dependent variable are more likely due to the independent variable. These functions match the description in the stem, so control is the correct completion.

Statements A, B, C, D and F correctly describe threats to internal validity, while E is false. Statement A is true because events between measurements can influence outcomes. Statement B is correct as maturation refers to participant changes over time, and statement C rightly defines the testing effect. Statement D accurately explains instrumentation changes, and statement F is true for attrition or mortality, whereas E is false because random assignment is a control technique that strengthens, not threatens, internal validity.

Option A:
Option A includes all the genuine threats named (A, B, C, D and F) and excludes E, which misinterprets the role of random assignment. It thus presents a complete and accurate set of internal validity threats mentioned in the list. Therefore this option is the correct answer.

Option B:
Option B leaves out F, ignoring the issue of differential dropout across groups. Since attrition can seriously bias results, omitting it gives an incomplete picture of internal validity threats. As a result, this combination is not acceptable.

Option C:
Option C contains E in addition to B, C, D and F, thereby treating random assignment as a threat. This is incorrect because random assignment is used to control extraneous variables and enhance internal validity. Including a false statement disqualifies this option.

Option D:
Option D omits B, which is an important threat related to participant changes, and therefore fails to recognise the full range of threats in the list. By leaving out a true statement, it offers only a partial account and cannot be considered correct.

Random assignment is the process of allocating participants to experimental and control groups purely by chance, such as by using random numbers or drawing lots. It ensures that, on average, the groups are equivalent with respect to both known and unknown variables before the treatment is applied. This greatly strengthens internal validity by reducing selection bias. Because the stem highlights equal and independent chances of being placed in any group, random assignment is the correct term.

Option A:
Random assignment ensures that individual differences are distributed approximately evenly across groups, so observed post-treatment differences are more likely due to the intervention. It is a defining feature of true experimental designs. This role matches the stem’s description, confirming random assignment as the appropriate completion.

Option B:
Matching involves pairing participants who are similar on certain variables and then assigning them to different groups, which partially controls for those variables but does not guarantee equal independent chance of group placement for all participants. Thus, matching is not the correct answer.

Option C:
Blocking is used to control for the effects of one or more nuisance variables by forming homogeneous blocks and then randomly assigning treatments within each block, especially in agricultural or industrial experiments. While it involves randomisation, the stem’s focus on general equal and independent chances for all participants is more directly captured by random assignment.

Option D:
Clustering usually refers to grouping participants based on natural units such as classes or schools in sampling or design and does not necessarily imply random allocation of individuals to treatment conditions. As such, clustering is not the proper term for the procedure described.

The Solomon four-group design uses two groups that receive a pre-test and two that do not, with both pre-tested and non-pre-tested groups being split into treatment and control subgroups. This structure allows researchers to evaluate both the main effect of the treatment and any interaction between pre-testing and treatment. It is particularly useful when there is concern that pre-testing may sensitise participants. Hence, the design mentioned is the Solomon four-group design.

Option A:
Latin refers to the Latin square design, which controls for two extraneous variables arranged in rows and columns; it is a different form of experimental design.

Option B:
The Solomon design maintains random assignment and includes both pre-test and post-test observations for some groups while others receive only post-tests. By comparing patterns across the four groups, researchers can detect testing effects and adjust interpretations accordingly. This comprehensive control for testing effects fits the stem, making this option correct.

Option C:
Factorial designs study the combined effects of two or more independent variables by including all combinations of their levels, but they do not inherently incorporate the four-group structure designed for testing effects.

Option D:
Quasi experimental designs lack full random assignment or control groups and are therefore different from the rigorously controlled Solomon design described.