Teachers need psychological instruments to be able to measure extent of students’ educational interests. The present research paper reports efforts related to construction and standardization of an educational interest inventory for measuring students’

interests in their academic subjects. The try-out form had 21 situations and each situation had a list of ten tasks. Students were asked to indicate the intensity of their preference for each given activity/task related to each situation by choosing one of the

five responses namely- ‘very less, less, average, much and very much’ Scoring was done by assigning a score of 1, 2, 3, 4 or 5 for ‘very less, less, normal, much and very much’ responses. Scores on all items related to an area of interest were added together to get

ten interest scores. Item analysis was done by calculating Chi-squares and item-total correlations for each item. Final form of the inventory has 15 situations and the 97 items included under them. Test-retest reliability were computed for different dimensions of

interest. They were .89 for physical science, 88 for biological science, .98 for commerce, .84 for literary, .78 for social service, .74 for office management, .89 for mathematics, .81 for religious, .88 for Music, and .78 for home science. Face validity was established.

This study examines the perceptions and usage of Learning Management Systems (LMS) in a language university through a multidimensional lens, focusing on awareness, accessibility, usability, interactivity, and barriers to adoption. Drawing insights from

the B.Ed. students, the findings highlight the pedagogical value of LMS platforms while also identifying key challenges such as limited digital preparedness and infrastructure gaps. The study underscores the need for targeted training, inclusive design, and sustained institutional support to improve LMS integration. These insights make a meaningful contribution to the advancement of digital learning environments in language-based higher education, fostering more inclusive, engaging, and effective academic experiences.

In the field of education, Artificial intelligence teaching approaches not only modify but also enhance students’ learning experience. In modern times, AI-based machine learning, natural language learning tools, data analytical tools, and personalized learning tools help students experience new things and intensify their motivation. AI in education analyzes huge data to identify patterns and provide suitable recommendations to improve student engagement and performance. AI can also provide immediate and beneficial feedback to allow students to understand their strengths and weaknesses. AI supports collaborative learning environments, promoting

active participation, critical thinking, and problem-solving skills to modify learning paths and deliver adaptive feedback to fulfill the aim of STEM education. AI has completely changed STEM education to provide personalized and flexible learning opportunities. Artificial intelligence helps to analyze data, provide instant feedback, and foster cooperative learning, like machine learning, natural language processing, and data analytics.

The integration of digital tools into literature classrooms has significantly transformed teaching methodologies, enabling greater interactivity, accessibility, and learner engagement. E-Pedagogy—defined as the systematic application of digital platforms,

multimedia resources, and online pedagogical strategies—offers innovative avenues for literature teaching beyond traditional methods. This study evaluates the effectiveness of e-pedagogy in enhancing literature teaching among undergraduate students. Data

was collected from 100 literature students across three universities through surveys and classroom observation over 8 weeks. Findings revealed a 35% increase in students’ comprehension scores, greater engagement during sessions using tools such as Google

Classroom, Padlet, and YouTube lectures, and improved critical analysis skills through discussion forums and interactive quizzes. However, challenges such as digital divide issues, lack of technological training for teachers, and inconsistent internet connectivity

were also noted. The study concludes that integrating e-pedagogy into literature teaching significantly improves learning outcomes and suggests the need for blended models to balance digital and traditional methods.

neP-2020 envisions a future where Indian students are well-versed in both their mother tongues and english, enabling them to navigate both local and global contexts effectively. Success hinges on robust implementation, addressing the identified challenges, and fostering a supportive environment that values linguistic diversity while prioritizing quality English language education. The National Education Policy (NEP) 2020 presents a transformative framework for English Language Teaching (ELT) in India, aiming to balance the promotion of mother tongue instruction with the continued importance of English as a global language.