UGC NET Questions (Paper – 1)

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.

External validity refers to the degree to which research results obtained from a particular sample and context can be applied to broader populations, different environments and future periods. High external validity suggests that findings are not limited to the specific conditions under which the study was conducted. It depends on factors such as sampling methods, realism of the setting and replication in different contexts. Because the stem highlights generalisation to other settings, populations and times, external validity is the correct term.

Option A:
External validity is enhanced when the sample is representative and when the research conditions resemble real-world situations, increasing the likelihood that similar results will be observed elsewhere. Studies with narrow samples or artificial settings may show strong internal validity but weaker external validity. The generalisability focus in the stem aligns directly with the concept of external validity, confirming it as the right option.

Option B:
Internal consistency is a type of reliability that concerns how well items on a test measure the same underlying construct, often assessed with coefficients like Cronbach’s alpha. It does not address whether findings generalise beyond the sample, so internal consistency is not the correct answer.

Option C:
Item difficulty refers to how hard individual test items are for examinees, usually expressed as the proportion of test takers who answer each item correctly. While important in test construction, it is unrelated to the generalisability of study findings across settings or populations. Thus, item difficulty does not fit the description in the stem.

Option D:
Standard error is a statistical index that indicates the variability of a sample statistic, such as the mean, across repeated samples from the same population. Although it relates to sampling accuracy, it is not itself the term for generalisability across broader contexts. Therefore, standard error is not the appropriate completion here.

Statement D is wrong because convenience sampling does not guarantee high external validity; it often leads to biased samples that limit generalisation. Statements A, B, C and E are correct: external validity concerns generalisation, narrow or atypical samples restrict it, replication strengthens it and realistic settings can enhance ecological validity. Hence, the only wrong statement is D.

Option A:
Option A is incorrect because it also labels A, which properly defines external validity, as wrong along with D. Treating A as incorrect misrepresents a basic concept in research design.

Option B:
Option B is wrong because it groups B with D as wrong, even though B accurately describes how an atypical sample can limit generalisability. Misclassifying B obscures a key threat to external validity.

Option C:
Option C is also incorrect because it treats C, which rightly notes the value of replication, as wrong. Replication is a standard strategy to test the robustness of findings across contexts.

Option D:
Option D is correct as it singles out D as the only statement that wrongly exaggerates the merits of convenience sampling for generalisation, while implicitly accepting the rest as accurate.

Interaction of selection and treatment occurs when the characteristics of those selected for the study, such as being volunteers or highly motivated individuals, interact with the treatment in such a way that results may not hold for a broader population. This threatens external validity because the findings may not generalise beyond the specific type of participants used. Recognising and minimising such biases is important when designing experiments. Therefore, the threat described in the stem is the interaction of selection and treatment.

Option A:
Selection refers to how participants enter the study and the ways in which they may differ systematically from the target population. When these differences influence how they respond to treatment, generalisation becomes problematic, capturing the idea in the stem and making this option correct.

Option B:
Testing as a threat to validity involves effects of taking a pretest on later performance, not differences between volunteers and non-volunteers. It is more about sensitisation than about participant characteristics.

Option C:
History refers to external events occurring between measurements that affect outcomes for all participants, which is different from the differential response of specific selection groups.

Option D:
Instrumentation concerns changes in measurement tools or observers over time, affecting scores independently of the treatment and is unrelated to how volunteers might differ from non-volunteers in responsiveness.

External validity is concerned with whether findings obtained in a particular study context hold under different conditions. It includes population validity, which deals with other groups of people, and ecological validity, which addresses other settings and situations. High external validity implies that results are not highly context-bound. Therefore, the generalisability described in the stem is called external validity.

Option A:
Internal validity relates to whether observed effects can be attributed confidently to the treatment rather than to extraneous factors. It focuses on causal inference inside the study, not on generalisation beyond it.

Option B:
Content validity refers to how well test items represent the domain of content, such as curriculum topics, and is primarily a measurement property rather than a property of study generalisation.

Option C:
External validity is influenced by factors such as sampling, realism of settings and interaction of selection with treatment. Researchers may conduct replication studies in diverse contexts to strengthen external validity. Because the stem refers explicitly to other populations, settings and times, this option is correct.

Option D:
Criterion validity deals with how well a test correlates with a relevant outcome measure or criterion, not with generalisability of results across contexts.

External validity refers to how far the conclusions drawn from a specific study can be applied beyond the particular participants, conditions and time frame of that study. It addresses questions such as whether results would hold in different institutions, regions or age groups. High external validity increases the practical usefulness of research findings for policy and practice. Since the stem focuses on generalisation to other populations, settings or times, external validity is the correct term.

Option A:
Internal validity deals with ruling out alternative explanations within the study so that causal inferences are sound, but it does not by itself guarantee that findings generalise. A study may be internally valid yet externally limited if the sample or context is narrow. Therefore, internal validity does not match the emphasis in the stem.

Option B:
Construct validity concerns whether the research appropriately operationalises and measures the theoretical constructs involved. While it contributes to meaningful interpretation, it is not primarily about generalisability across contexts. Hence, construct validity is not the right completion here.

Option C:
Content validity focuses on whether an instrument adequately represents the relevant content domain or syllabus, which is a different issue from applying results to new settings or populations. Thus, content validity is not the term being defined in the question.

Option D:
External validity can be enhanced by using diverse samples, realistic settings and replication across contexts. These strategies help ensure that the observed relationships are not peculiar to one specific group or environment, aligning with the stem’s focus on generalisation.

Generalisability concerns the extent to which the findings of a particular study can be validly extended beyond the specific sample, setting and time in which the data were collected. High generalisability implies that similar results would likely be obtained in other contexts with comparable conditions. It is closely linked to external validity, which evaluates how well study results apply in real-world situations. Therefore, a statement about how far results may be applied elsewhere refers to the generalisability of the findings.

Option A:
Reliability addresses the consistency of measurement within the study and does not by itself indicate whether results can be extended to other populations or settings. A measure can be reliable in one context but may not generalise to different groups. Hence, reliability is not the correct completion.

Option B:
Generalisability is influenced by factors such as sampling method, sample size, and ecological validity of the research setting. Researchers often discuss limitations on generalisability to avoid overstating the applicability of their results. These concerns match the description in the stem.

Option C:
Standardisation involves using uniform procedures and conditions when administering instruments or conducting experiments, which supports reliability and fairness but is not the same as extending findings to other contexts. Therefore, standardisation is not the best answer.

Option D:
Objectivity refers to freedom from researcher bias in collecting and interpreting data, ensuring that findings are based on evidence rather than personal preferences. While it contributes to the credibility of results, it does not directly describe their scope of application, so objectivity is not appropriate here.