Industrial development has been one of the principal drivers of India's economic transformation by promoting structural change, employment generation, technological advancement, and productivity growth. Despite substantial progress in manufacturing during the last decade, industrial development remains unevenly distributed across Indian states. The present study examines regional industrial imbalances in India during 2014-2024 by analysing recent industrial trends, identifying the determinants of regional disparities, and discussing their policy implications. The study is based entirely on secondary data obtained from official sources, including the Annual Survey of Industries (ASI), Ministry of Statistics and Programme Implementation (MoSPI), Reserve Bank of India (RBI), Department for Promotion of Industry and Internal Trade (DPIIT), Economic Survey of India, and NITI Aayog publications. Descriptive and comparative analytical techniques have been employed to analyse regional differences in manufacturing output, employment, investment, infrastructure, and industrial concentration. The findings indicate that industrial development continues to be concentrated in a limited number of western and southern states, while several eastern, central, and northeastern states remain relatively less industrialized. Recent ASI results show that Tamil Nadu accounts for the largest share of registered factories (15.43%) and persons engaged (15.24%), Gujarat leads in fixed capital (19.53%) and industrial output (17.22%), whereas Maharashtra contributes the highest share of manufacturing Gross Value Added (15.95%). These patterns clearly demonstrate the continued concentration of industrial activity in a few states. The study concludes that balanced industrial development requires region-specific industrial policies, improved physical infrastructure, enhanced logistics, greater private investment, skill development, and stronger institutional support for industrially lagging regions. Such interventions are essential for achieving inclusive and sustainable industrial growth across India.

English has become one of the essential languages for academic achievement, higher education and all the career opportunities in contemporary India. Therefore, many rural learners encounter considerable amount of anxiety while learning and using the language, which affects their involvement and overall language development. This article explores English language anxiety among rural learners in the area of Dadra Nagar Haveli & Daman Diu through observations and experiences gathered during an educational internship conducted in schools serving students from diverse linguistic backgrounds. The study adopts a qualitative and descriptive approach based on classroom observations, informal interactions with students and reflective field notes. The limited exposure to English beyond the classroom, translation-oriented teaching practices, dependence on mother tongue and concerns about peer judgment occurred as significant factors contributing to the language anxiety. These challenges often hinder student’s confidence and willingness to converse in English. The study highlights the importance of creating positive classroom environments and providing learners with meaningful opportunities to use English. It reinforces the need for learner-centered pedagogical practices that encourage participation and reduce fear of making mistakes. By addressing these factors, teachers can help rural learners develop enhanced confidence, improve their communicative competence, and enhance their overall English language proficiency.

This study examines the relationship between cost of governance and public infrastructure financing in Nigeria over the period 1990–2025. Rising governance costs have increasingly attracted policy concern in Nigeria due to the growing share of public resources devoted to recurrent expenditure while infrastructure deficits continue to widen. The study therefore investigates how key components of governance expenditure influence government investment in infrastructure development. Specifically, the study considers personnel cost, debt servicing expenditure, and administrative or overhead expenditure as proxies for the cost of governance, while capital expenditure on infrastructure serves as the dependent variable. The study adopts a time series research methodology and utilizes secondary data obtained from the Central Bank of Nigeria Statistical Bulletin and publications of the National Bureau of Statistics. The data were analyzed using both descriptive and econometric techniques. Trend analysis through line graphs was used to examine the behaviour of the variables over time, while descriptive statistics were employed to summarize their statistical properties. The stationarity of the series was tested using the Augmented Dickey-Fuller unit root test to avoid spurious regression results. The Autoregressive Distributed Lag (ARDL) modelling approach was then applied to examine the dynamic relationship between governance expenditure and infrastructure financing in both the short run and the long run. The empirical results reveal that components of governance expenditure exert significant dynamic effects on infrastructure financing in Nigeria. Personnel cost shows mixed but significant effects across different lag periods, indicating that rising wage bills can constrain infrastructure spending in some periods while adjustments occur over time. Administrative expenditure exhibits a positive relationship with infrastructure financing, whereas debt servicing expenditure shows a negative relationship, suggesting that rising debt obligations may reduce funds available for infrastructure development. The study concludes that the increasing cost of governance poses a challenge to sustainable infrastructure financing and recommends stronger fiscal discipline, improved expenditure management, and prioritization of capital investment in infrastructure to support long-term economic development.

In today’s language classrooms, reading comprehension remains a core literacy skill but it’s even harder to master in digital environments. Conventional text-based instructional materials often lack interactivity and multimodal support, which limit learner engagement and slow comprehension development. With the emergence of artificial intelligence and multimodal technologies, instructional resources can now be transformed into dynamic, interactive, and learner-centered materials that integrate visual, auditory, and interactive elements. Grounded in the materials development principles of Brian Tomlinson and supported by multimedia and multimodal learning perspectives, this study responds to the need for pedagogically sound, technology-enhanced resources in language instruction within the Philippine educational context. This study aimed to design, develop, and evaluate an AI-assisted multimodal e-book toolkit intended to enhance the reading comprehension and engagement of Grade 7 students. The study specifically examines the content of the multimodal features integrated into the selected e-books through AI-assisted transformation, evaluates the relevance of the developed material in supporting students’ reading comprehension and engagement, and determines the appropriateness of the multimodal elements in facilitating language learning and comprehension development. Moreover, it investigates the effects of the developed multimodal materials on students’ reading comprehension, particularly in enhancing learner engagement, understanding of texts, and overall language learning experiences. Additionally, the scaffolded activities, interactive learning tasks, and assessment components, including the pre-test and post-test, were systematically aligned with the learning competencies prescribed in the revised Department of Education curriculum to ensure instructional relevance, curriculum consistency, and pedagogical appropriateness. The study employed a Developmental Research Design approach guided by the ADDIE instructional design model, encompassing the phases of Analysis, Design, Development, Implementation, and Evaluation. The participants consisted of forty (40) Grade 7 learners from Universidad de Sta. Isabel of Pili, Inc. during the School Year 2025–2026. The developed AI-assisted e-book toolkit was pilot-tested in an authentic classroom setting to assess its usability, clarity, engagement, and instructional value. Data were collected using a researcher-developed survey questionnaire validated by experts in English education and instructional materials development, adapted from the Department of Education LRMDS Evaluation Template for non-print materials. Descriptive statistical tools, particularly the weighted mean, were utilized to analyze the data and determine the level of acceptability of the developed instructional material. The findings revealed that the multimodal features integrated into the AI-transformed e-book were highly evident, coherent, and pedagogically appropriate. Participants strongly agreed that visual supports, interactive prompts, multimedia elements, and scaffolded activities were effectively incorporated and significantly contributed to their understanding of the text. The use of the AI-assisted e-book was found to enhance students’ reading comprehension by improving their ability to interpret ideas, think critically, and engage actively with the material. Moreover, the results indicated a high level of learner engagement, with students reporting increased motivation and sustained attention during reading tasks. Among the multimodal features, visual aids, interactive questioning, and structured scaffolded activities emerged as the most helpful in supporting comprehension and higher-order thinking skills. These findings affirm that the support of artificial intelligence and integration multimodal design fosters meaningful learning experiences and supports cognitive processing. The study concludes that AI-assisted multimodal e-book toolkits are effective instructional resources that enhance reading comprehension, learner engagement, and higher-order thinking skills. The AI-assisted transformation of traditional e-books into interactive and learner-centered materials supports contemporary language learning and multimedia cognition theories. Furthermore, purposeful multimodal integration and sound pedagogical design maximize the instructional effectiveness of digital learning resources. It is therefore recommended that educators integrate AI-assisted multimodal materials into language instruction, that instructional designers continuously refine multimedia and interactive elements based on learner feedback, and that future research explore broader applications and long-term impacts of AI-enhanced instructional tools across diverse educational contexts.