Due to the COVID-19 pandemic, there has been a rapid shift from traditional classroom-based education to sustainable online classrooms. This has brought attention to the importance of comprehending the intricacies of students’ engagement during virtual learning. Drawing upon the concept of community of inquiry in cognitive, social, and teaching presence, a mixed-methods approach involved data collected via a structured questionnaire administered to 452 university students to identify the factors that influence students’ participation during online classes. Through the application of the CHAID (Chi-Squared Automatic Interaction Detection) decision tree algorithm, the quality of course content is identified as a cognitive predictor of students’ engagement. It is worth mentioning that a significant proportion of students, specifically 61.7%, demonstrated a considerable degree of engagement with faculty content due to its high quality. With respect to the role of social presence, possession of a designated private space boost (69.2%) and requiring students to use their webcams are found to be critical for students’ engagement. Lastly, teaching presence as a factor in enhancing students’ engagement is demonstrated by promoting interactive classrooms and providing rapid feedback to students by teachers. The findings demonstrate the importance of teachers’ quality course material, interactive classes, and the benefits of a physical environment free from distractions for optimizing students’ engagement.

Objective: The objective of this study is to investigate the transformative potential of generative AI in advancing Sustainable Development Goal 4 (SDG 4), with the aim of enhancing equity, accessibility, and quality in higher education through the integration of AI-driven systems and practices. Theoretical Framework: This research is underpinned by the AI Academic Convergence (AIAC) Framework, which aligns with theories such as constructivism, Vygotsky’s cultural-historical theory, and Bloom’s Taxonomy. These frameworks provide a solid basis for understanding the interplay between personalized learning, cognitive engagement, stakeholder collaboration, and ethical governance in educational ecosystems. Method: The methodology adopted for this research comprises a Literature-Driven Conceptual Framework Development approach, synthesizing peer-reviewed studies across key themes: personalized learning, operational efficiency, collaborative learning, and ethical AI governance. Data collection involved systematic literature reviews of scholarly articles, books, and conference proceedings within the past decade. Results and Discussion: The results reveal that the AIAC Framework promotes tailored, adaptive learning pathways, enhances faculty roles as AI-enabled mentors, and optimizes administrative workflows through predictive analytics. The discussion contextualizes these findings within existing theories, emphasizing the framework's ability to mitigate challenges such as algorithmic bias, equity gaps, and data privacy concerns. Limitations include the need for empirical validation and addressing resource disparities in underprivileged contexts. Research Implications: The practical and theoretical implications of this research are significant for higher education institutions, policymakers, and AI practitioners. These include fostering innovative teaching practices, advancing equitable access to AI-enhanced tools, and aligning educational strategies with labor market demands through predictive analytics and collaborative governance. Originality/Value: This study contributes to the literature by introducing the AIAC Framework, an innovative and scalable model for integrating generative AI into education. Its value lies in bridging the digital divide, fostering lifelong learning, and positioning higher education institutions as leaders in ethical and sustainable AI integration, ultimately advancing the mission of SDG 4.

: The present study investigates the influence of faculty-related and ICT-related variables on the overall online learning experience of students. The study involved the participation of 348 engineering students, and data analysis was carried out using a Chi-square Automatic Interaction Detector (CHAID) decision tree. The results of this research highlight the significance of delivering superior quality content and providing a designated learning environment, which can enhance students' level of satisfaction and involvement in online education. A positive correlation was observed between the employment of virtual laboratories and enhanced academic performance among students. The present research provides evidence for the impact of faculty engagement, the provision of suitable virtual learning environments, and the incorporation of online laboratory simulations in enhancing students' virtual learning encounters. The findings have noteworthy implications for educational institutions that aim to enhance student satisfaction and optimise online learning environments. Keywords: Faculty Engagement, Online Learning Experience, CHAID Decision Tree, High-Quality Content Delivery, Virtual Laboratories.

Infrastructure Development is critical for economic growth. It plays a significant role in setting up of an enabling platform for sustainable economic development. It includes services such as Power (electricity), telecommunications, sewage and sanitation, gas, roads, railways, seaports, and airports which promote commercial activities, production and consumption. Government of Andhra Pradesh has been pursuing Mission Based Approach for leveraging the sectoral strengths to enable the state reach sustainable double digit growth of GSDP. The paper briefly reviews recent data for the newly formed Sunrise State of Andhra Pradesh in terms of Gross Value Added (GVA) and Gross State Domestic Product (GSDP) for the period 2013–17 through sectoral share and growth rates, and focuses on a few areas of infrastructure perspectives for Andhra Pradesh. During 2015–16, the State has recorded growth rate of 10.99% for GSDP (India 7.6%), and 10.5% for GVA (India 7.3%). Per capita income at current prices for the State crossed Rs. one lakh for the first time in 2015–16 (Rs. 1, 07, 532 for the State, India Rs.93, 231). During 2016–17, for the first half year (H1), GSDP growth rate was 12.23% for the State (India 7.2%), and GVA growth rate was 12.0% for the State (India 7.2%). Growth rates have been worked out at constant prices with 2011–12 as the base year, and share of various sectors in GVA is presented at current prices. This encouraging trend needs to be sustained and improved upon to reach 15% sustainable target growth rate that the State is hopeful of achieving in the next few years. Infrastructure areas covered for Andhra Pradesh are: Road network, railways, seaports, airports, power (electricity and solar power), water, optical fibre, social infrastructure, and specialised industrial infrastructure such as Export Promotion Parks, Software Technology Parks (STPs), and Special Economic Zones (SEZs). Plans for seaport-led development, power, and optical fibre network are emphasised.