The current study sought to investigate the educational aspirations of secondary school adolescents concerning their parental education and types of schools. In this context, the research study's primary objective was to investigate the levels of educational aspirations of secondary school adolescents, as well as to examine their educational aspirations concerning parental education and the types of schools. The investigator gathered data from 400 adolescents in the government and private schools of Darbhanga, Bihar, India, who were in the 9th and 10th grades. A descriptive research design was implemented by the investigator. The data were collected using the survey method, with the support of a self-developed questionnaire on "Educational Aspirations of Secondary School Adolescents." Chi-square analysis was used to interpret the data. The study's findings revealed that the majority of secondary school students, i.e., 9th and 10th graders, have moderate levels of educational aspirations, and the secondary school adolescents' educational aspirations are independent of their parental education and the type of school. Furthermore, the finding revealed that secondary school boys' educational aspirations are independent of the type of school whereas secondary school girls' educational aspirations are dependent on the type of schools they attend. Based on the study's findings, it is suggested that special career-related guidance and counseling sessions for both secondary school adolescents and parents may be organized by the school to improve the educational aspirations of the adolescents.

Vocational interest refers to an individual’s preference for particular types of work and activities, reflecting personal strengths, values, and aspirations. This study focuses on the study of vocational interests of secondary school students of Murshidabad district of West Bengal. A total of 348 respondents were selected as a sample through multiple stage sampling techniques. The researchers used Kulshrestha (2009)'s Vocational Interest Record, consisting of 200 items across ten areas like, literacy, scientific, executive, commercial, constructive, artistic, agriculture, persuasive, social, and households. Both descriptive and inferential statistics were calculated for analyzing the data that was collected. The study concludes that females and private school students have higher vocational interest levels. Further, the study found that there is a significant difference between male and female, private and government students at secondary level in the vocational interest.

This thesis has examined socio-cultural factors that are also significant problems
for Indians. She is an Indian playwright, novelist, short-story author, illustrator, journalist, and cartoonist. She also composes plays for theatre presentations. I have studied to assess her two plays and two novels for my thesis. The two plays are Harvest and Lights Out, while the two novels are Escape and the Island of Lost Girls. Poverty, unemployment, gender issues, violence, trans sexuality, disability, technocracy, patriarchy, and marginalization have been examined. Current and urban conditions are exemplified by people who are perceptive and flexible. Padmanabhan has brought up one of the most important issues facing Indians, namely unemployment and poverty, which has given rise to the human organ trade. In her play Harvest, Manjula Padmanabhan explores the interaction between agrarian and industrial civilization via telecommunications’ Om Prakash is from a rural background.

It is the right of every child to get quality education. The quality of education depends on various factors one of which is the teacher. Teachers are the backbone and central figure of any education system. Since teaching is vitally linked with school improvement, it is important to work on teacher preparation. Apart from government, many non- government organizations (NGOs) have been working in this area. This paper aims to focus on the Necessary Teacher Training (NeTT) - an innovative two-year Pre-service Teacher Training Programme being implemented by Humana People to People India (HPPI), a non- government organization. HPPI collaborates with the state governments and private agencies to run the NeTT programme at District Institutes of Education and Training (DIETs).The unique training module of NeTT is designed in alignment with the state curriculum prescribed for D.El.Ed. course at DIET’s. The programme is aligned with the vision and goals of HPPI and tailored in accordance to the National Curriculum Framework for Teacher Education (NCFTE) 2009. Thus, the NeTT programme fills this gap where teacher educators aim at training teacher trainees towards improving the quality of teacher education.

Trust is a cornerstone of effective human-AI collaboration, particularly in an era of rapid digitalization where AI systems are increasingly integrated into decision-making processes across various sectors. This study investigates the critical factors influencing trust namely Transparency, Interpretability, and Satisfaction, and their sector-specific dynamics in healthcare, finance, and customer service. Utilizing a cross-sectional survey of 500 participants and stratified sampling, the research highlights pivotal role of transparency and interpretability in fostering trust, particularly in high-stakes sectors such as healthcare and finance. Transparency (β = 0.512, p < 0.001) and interpretability (β = 0.602, p < 0.001) significantly enhance trust, with stronger effects observed in healthcare (????2 = 0.494) and finance (????2 = 0.511) compared to customer service (????2= 0.374). Satisfaction had been emerged as a crucial mediating variable that amplifies the relationship between transparency and trust. The indirect effect of transparency on trust through satisfaction (β = 0.223, p < 0.001) underscores the importance of user-centric design in building trust. Furthermore, satisfaction demonstrates a stronger influence on trust in customer service (????=0.653), emphasizing its importance in customer-facing applications. This study provides theoretical contributions by extending trust frameworks to sector-specific contexts and offers actionable insights for AI system developers and policymakers. The findings advocate for tailored trust-building strategies, prioritizing transparency and interpretability in healthcare and finance, while emphasizing user satisfaction in customer service. The research will advances the understanding of trust dynamics in human-AI collaboration, addressing the ethical, operational, and design challenges of AI systems in a digitalized world.

This paper explores the complexities of multidimensional poverty in India by analyzing the interactions among various poverty dimensions and evaluating the impact of social protection policies on poverty alleviation. Utilizing the Multidimensional Poverty Index (MPI) methodology, the study identifies the interconnections between different deprivations and their implications for effective policy-making. It argues that while income-based measures are essential, a multidimensional approach provides a more comprehensive understanding of poverty, enabling the design of targeted interventions. The research highlights significant challenges within India's social protection system, including targeting inefficiencies and infrastructural gaps, and assesses the potential of policy innovations such as cash transfers and Universal Basic Income (UBI). Additionally, the study underscores the importance of integrating social protection policies with high-quality infrastructure to achieve sustainable poverty reduction. Findings indicate that although existing social protection schemes have made considerable progress, there is a need for a more cohesive strategy that addresses both preventive and remedial aspects of poverty. The paper concludes by recommending areas for future research, including the incorporation of new data from the India Human Development Survey (IHDS) and the exploration of urban poverty dynamics, thereby contributing to a deeper understanding of effective poverty alleviation strategies in India.

Artificial Intelligence (AI) has quickly changed different industries, with education being a key segment that stands to advantage significantly. This research paper investigates the integration of AI into education, from primary to higher education, analyzing how AI enhances educating and learning forms. The paper also highlights the benefits of AI within the classroom, counting personalized learning, improved engagement, and data-driven decision-making.

This research paper examines the evolution and impact of four key labour laws in India: The Factories Act, 1948; the Employee Provident Fund Act, 1952; the Maternity Benefit Act, 1961; and the Industrial Disputes Act, 1947. Recognising the inherent right to both equality and liberty for workers/employees, the study analyzes how these laws, within the framework of the Indian Constitution, have sought to balance these principles.

The researcher has used a comprehensive literature review, examined the historical context of labour law development in India, analysed the provisions of the four key acts, and incorporated insights from academic research, government reports, and expert opinions.

The study aims to critically evaluate the effectiveness of these laws in protecting the rights and improving the working conditions of workers/employees in both organized and unorganised sectors. Through this paper, the researcher has offered constructive recommendations for enhancing the existing legal framework and ensuring greater equity and justice for all workers/employees in India.

Artificial intelligence has become increasingly significant in today's society as it has turning out to be all the more generally used. Various experts accept that artificial intelligence algorithms can possibly be useful in giving a precise and objective assessment of the numerous threats that are posed by denounced criminals. Late research indicates that crime is something that can be expected; everything necessary of us is the capacity to foresee analytics accomplishing legitimate control. Because of the way that cybercriminals are increasingly taking advantage of the web of things (IoT) to create and transmit malware as well as send off ransomware assaults, the significant purpose is to analyze suspected offenders. The year 2023, Waldman. More than 2.5 million devices are supposed to be completely associated with the web inside the following five years, as per projections. The artificial intelligence (man-made intelligence), crime expectation, and crime prevention are the essential topics of discussion in this study. An investigation is being led to decide if it is ethically permissible to mark an electronic gear as a prospective criminal offense distinguishing gadget. The findings of the study show that the utilization of artificial intelligence to assess the consequences of criminal regulation is not just a mechanical process; rather, an assessment of a person has been sentenced for a crime that will be thought about.