UGC NET Questions (Paper – 1)

Learning analytics involves collecting and analysing data about learners and their contexts to understand and optimise learning. Metrics such as logins, resource views and assessment results are typical inputs for such analysis. They help educators identify patterns of engagement, at-risk students and effective materials. Hence the reports described in the stem are examples of learning analytics data.

Option A:
Option A is correct because LMS-generated activity and performance indicators are central sources for learning analytics dashboards and research. These data are explicitly used to improve teaching strategies and student support.

Option B:
Option B, random noise, suggests meaningless or unstructured data, which is not accurate here because the metrics are systematically recorded and interpretable.

Option C:
Option C, fiscal accounting, pertains to financial transactions and budgets rather than learner behaviours and outcomes.

Option D:
Option D, biometric surveillance, would involve physical or physiological measurements like fingerprints or facial recognition, which are not mentioned in the stem.

Statements A, B, D and E correctly describe higher education responses to Industry 4.0. A is true because automation, AI, IoT and data analytics are central to Industry 4.0. B is true as curricula need updating to include new technologies and skills. D is true since combining computing with other disciplines helps address complex Industry 4.0 demands. E is true because industry partnerships inform curriculum relevance and provide practical exposure. C is false because Industry 4.0 fundamentally changes skill expectations, and F is false because ethical and social implications are important considerations in technology education.

Option A:
Option A is incorrect because it omits E and therefore fails to emphasise the importance of active collaboration with industry in designing relevant curricula.

Option B:
Option B is incorrect because it excludes B, meaning it does not clearly state that curricula themselves must be revised, even though that is a major expectation under Industry 4.0 reforms.

Option C:
Option C is incorrect because it ignores A and includes only B, D and E, thus omitting the core description of what Industry 4.0 actually involves.

Option D:
Option D is correct because it includes all four true statements (A, B, D and E), capturing the nature of Industry 4.0 and the curricular and partnership responses needed, while excluding C and F, which deny skill implications and ethical concerns.

The Bhopal gas tragedy of 1984 highlighted serious gaps in India’s environmental and industrial safety regulations. In response, the Government of India enacted the Environment (Protection) Act, 1986 as a comprehensive, umbrella legislation. It empowered the central government to coordinate environmental policies, set standards, and take measures for the protection and improvement of the environment. Therefore, option B correctly identifies the act enacted after Bhopal as a broad framework law.

Option A:
Option A, the Wildlife (Protection) Act, 1972, predates the Bhopal disaster and focuses specifically on wildlife conservation and protection of endangered species. It is not the umbrella act for environmental protection enacted after 1984.

Option B:
Option B is correct because the Environment (Protection) Act, 1986 provides a framework for integrating various environmental policies, rules and standards. It was explicitly passed in the aftermath of Bhopal to strengthen environmental regulation.

Option C:
Option C, the Forest (Conservation) Act, 1980, deals mainly with restricting the diversion of forest land for non-forest purposes. It is important but not an umbrella act enacted post-Bhopal.

Option D:
Option D, the Water (Prevention and Control of Pollution) Act, 1974, aims to control water pollution and establish Pollution Control Boards. It predates Bhopal and is sector-specific rather than a comprehensive environmental framework.

Open access journals remove price and many permission barriers for readers by making articles freely available on the internet. They often use Creative Commons or similar licences that allow broad reuse with attribution. ICT infrastructures such as institutional repositories and online platforms make open access feasible at scale. Thus, the journals described are open access journals.

Option A:
Option A is correct because open access is defined by free online availability and permissive reuse conditions, matching the characteristics given.

Option B:
Option B, impact factor, measures citation frequency of journals and is not a type of access model.

Option C:
Option C, peer reviewed, describes the quality control process, which may apply to both open access and subscription journals.

Option D:
Option D, predatory, journals charge authors fees without proper editorial standards and are considered unethical, which is not implied by simply being free to read.

Statements A, B and C correctly describe the three main cloud service models, while statement D is false. In SaaS, complete applications are provided over the Internet; in PaaS, developers obtain an environment to run their code; and in IaaS, virtual machines, storage and networks are offered as services. Users typically do not handle the underlying physical hardware, which is managed by the cloud provider, so D must be excluded. Therefore the correct combination is A, B and C only.

Option A:
Option A is incorrect because it includes only A and B and omits C. While SaaS and PaaS are described accurately, IaaS is also a key model that must be included for a complete answer. Excluding C makes the option incomplete.

Option B:
Option B is incorrect because it groups A, C and D as correct statements. Although A and C are true, D is false because cloud users rarely manage physical data centre infrastructure. Including D invalidates the combination.

Option C:
Option C is correct because it gathers the three accurate statements defining SaaS, PaaS and IaaS and leaves out the misleading claim in D. It reflects the layered nature of cloud services where physical hardware is abstracted away from end-users.

Option D:
Option D is incorrect because it treats B, C and D as correct, again accepting D. Even though B and C are true, including the incorrect description of user responsibility for hardware makes this option wrong.

The relational model represents data as relations, each of which can be visualised as a table with rows and columns. Each row corresponds to a record, and each column represents an attribute. Tables can be linked through keys to express relationships between entities. Thus, the basic structure described in the stem is correctly termed a table.

Option A:
Option A, spreadsheet, also uses rows and columns but is typically a general purpose tool for calculations rather than a formal relational database structure with keys and constraints.

Option B:
Option B, file folder, refers to a directory in a file system and does not itself contain rows and columns in the relational sense.

Option C:
Option C is correct because relational database theory explicitly defines a relation as a table like structure, and DBMS software uses the word table to describe these objects.

Option D:
Option D, node, is a more general term used for connection points in data structures or networks and does not specifically denote a row column arrangement.

Solving 2x + 3 ≤ 11, we subtract 3 from both sides to get 2x ≤ 8. Dividing both sides by 2 yields x ≤ 4. On the real number line, this corresponds to all numbers less than or equal to 4. In interval notation, that set is written as (−∞, 4], with a square bracket at 4 indicating that 4 is included.

Option A:
Option A, (−∞, 4), excludes 4 itself and would represent x < 4, which is a strict inequality, not the given ≤ relation. Option B: Option B correctly captures x ≤ 4 by including all values up to and including 4, thus satisfying the inequality exactly. Option C: Option C, (−∞, 7], includes many values greater than 4, violating the upper bound imposed by 2x ≤ 8. Option D: Option D, [4, ∞), represents x ≥ 4, the opposite direction of the inequality, and only includes 4 and greater values.

The polluter pays principle states that the cost of pollution control and remediation should be borne by the polluter. It internalises environmental costs that would otherwise be external to the market. This principle provides an economic incentive for firms and individuals to reduce pollution. Therefore the description in the question clearly refers to the polluter pays principle.

Option A:
The precautionary principle advocates taking preventive action in the face of uncertainty to avoid serious or irreversible damage. It does not specifically assign costs to the polluter. Thus it does not match the definition given.

Option B:
Equity relates to fairness in the distribution of benefits and burdens among different groups. While polluter pays may promote a kind of equity,it is a more general value and not the specific policy rule defined in the question. Therefore it is not the most precise answer.

Option C:
The polluter pays principle directly links responsibility for pollution with financial liability. By making polluters responsible for the full environmental costs,it encourages cleaner technologies and processes. This is exactly the logic captured by the stem.

Option D:
Subsidiarity is a governance principle that decisions should be taken at the lowest appropriate level. It concerns allocation of authority rather than allocation of environmental costs. Hence it is not relevant to the concept described in the question.

Experimental research aims to determine whether changes in one variable cause changes in another. This requires deliberate manipulation of the independent variable and control over other factors that might influence the outcome. By holding extraneous variables constant or randomizing them, the researcher can attribute observed differences in the dependent variable more confidently to the treatment.

Option A:
Option A describes qualitative interviewing, which is useful for exploration but does not by itself establish causality through controlled manipulation.

Option B:
Option B is correct because it combines the two essential ingredients of true experimentation: manipulation and control. Without these, causal claims remain weak or speculative.

Option C:
Option C refers to biased selection of participants, which can threaten internal validity and does not help in establishing causal relationships.

Option D:
Option D mentions very small samples and lack of control group, both of which weaken the ability to infer causality and generalize findings.

A, B, D and E are correct; C is false. The gavaya case involves prior verbal description and memory plus later perception and comparison, so it is not “without memory”. Some schools subsume upamāna under other pramāṇas; UGC NET may ask to identify it via examples.

Option A:
Option A is incomplete because it omits E (exam identification), which is true.

Option B:
Option B is correct because it includes all true statements and excludes C (false).

Option C:
Option C is incomplete because it omits A (Nyaya recognises upamāna distinctly), which is true.

Option D:
Option D is incorrect because it includes C (false).

Statements A, B, C, D and E accurately describe sampling techniques, whereas F is false. Statement A is true because probability sampling ensures each element has a known non-zero chance of selection. Statement B correctly defines stratified random sampling, and statement C is right in classifying purposive sampling as non-probability. Statement D is correct since snowball sampling is used to access hidden populations, and E is true as probability methods reduce researcher selection bias, while F is false because convenience sampling does not guarantee representativeness.

Option A:
Option A includes all the correct statements and excludes the incorrect one. By presenting A, B, C, D and E together, it reflects standard textbook definitions of sampling techniques and their implications. Since it leaves out F, which wrongly promises guaranteed representativeness, this option is the correct answer.

Option B:
Option B omits statement E, thereby ignoring the important point that probability sampling minimises researcher bias. Although A, B, C and D are true, excluding E makes the combination incomplete. A correct option must list all relevant true statements for the concept.

Option C:
Option C brings F into the combination along with the correct statements. Because F falsely claims that convenience sampling ensures full representativeness, including it contaminates the set of statements. Any option that mixes false and true statements cannot be accepted as correct.

Option D:
Option D also contains F and even omits A, which is central to the definition of probability sampling. Leaving out a key true statement and adding a false one makes this combination doubly problematic. Consequently this option is invalid.

Statements A, B, C and E describe realistic uses of ICT for enhancing student support, whereas D and F are overly rigid. While online channels can reduce pressure on in-person desks, completely eliminating physical support may not suit all contexts. Feedback mechanisms are also valuable for improving services, so banning them makes little sense. Therefore, the combination A, B, C and E only is correct.

Option A:
Option A is incomplete because it leaves out E, which highlights the role of integrated knowledge bases in delivering consistent answers. Without E, the systemic improvement aspect of ICT-based support is underplayed.

Option B:
Option B is incomplete because it omits A, so it fails to mention basic portal functions such as access to grades and attendance, which are central to many student systems.

Option C:
Option C is incomplete because it excludes A and includes only B, C and E. Although those statements are true, not mentioning portal access to academic and financial records leaves the description of support somewhat narrow.

Option D:
Option D is correct because it groups together portals, chatbots, reminders and knowledge bases as complementary components. By excluding D’s extreme claim about abandoning physical desks and F’s rejection of feedback, it aligns with flexible, student-centred support models.

A necessary condition must be present whenever the outcome occurs. If having a valid admit card is necessary for entry, then anyone who is inside the hall must have such a card. In conditional form this becomes “If a person enters the hall, then the person has a valid admit card.” The statement does not claim that possessing a card alone is enough for entry, only that entry cannot happen without it.

Option A:
Option A treats possessing the card as sufficient for entry, which goes beyond necessity and may ignore other requirements like identity proof.

Option B:
Option B captures the idea that entry implies the presence of the necessary condition, aligning with the logical form “Outcome → Condition.”

Option C:
Option C reverses the direction in a way that ties receiving the card to entering, which is not what the original statement asserts.

Option D:
Option D explicitly mislabels the condition as sufficient but not necessary, contradicting the claim that it is necessary.

NRF is designed as a funding and facilitation body to strengthen research in universities and colleges. It will support projects in sciences, social sciences, arts and humanities. The goal is to build a robust research culture throughout the higher education system, not just in elite institutions.

Option A:
Regulating school exams is not part of NRF’s mandate; that lies with assessment bodies and boards.

Option B:
This option reflects NEP’s intent to make research more inclusive and adequately funded across the system.

Option C:
Sports tournaments, while important, are not the focus of a research foundation.

Option D:
Accreditation is managed through NAC and related bodies, not NRF.

Research is understood as an organized process guided by clearly defined objectives and questions. It relies on systematic procedures for collecting, analyzing and interpreting data to address a problem or gap in knowledge. Objectivity and careful control of bias are emphasized to make the findings credible.

Option A:
Option A is correct because it includes the key features: planning, objectivity, systematic method and knowledge orientation. It covers both discovery of new knowledge and validation of existing knowledge through evidence.

Option B:
Option B presents research as casual and opinion based, which contradicts the disciplined nature of scientific inquiry.

Option C:
Option C reduces research to a single guess, ignoring the need for sustained investigation, data collection and analysis.

Option D:
Option D focuses only on data collection and neglects interpretation and reasoning, without which raw data cannot contribute meaningfully to knowledge.