World Wide Journals

A STUDY OF PSHYCOLOGICAL RESILIENCE CORMAC McCARTHY'S THE ROAD

K. Perumal, Dr. C.Govindaraj — Wed, 22 Jul 2026 00:00:00 +0000

In the novel The Road (2006), the theme of psychological resilience is prominently explored amidst a post-apocalyptic
landscape devoid of hope. This study investigates how the characters, particularly the father and son, exhibit resilience
while navigating a desolate world plagued by scarcity, violence, and moral decay. where the human psyche is tested to
its limit. Subsequently, the research article examined the existential dimensions of resilience depicted in “The Road”
highlights the characters' enduring commitment to survival despite the absence of conventional societal structures and
norms. Here, research exploring the mechanisms for handling the devasted environment. This paper explores the theme
of psychological resilience in the novel by examining the coping mechanisms, survival instincts, and moral struggles of
the characters. By examining McCarthy's novel, The Road, the study portrays psychological resilience. Human
understandings thought and courage for endurance and adaptation in the face of overwhelming devastating situations

Enhancing Reading Comprehension Skills through Small Group Interaction Techniques: A Comparative Study

Arthy. V, Dr.P Nagaraj — Tue, 30 Jun 2026 00:00:00 +0000

Reading is the basic foundation on which the academic skills of an individual are built. Several recent reviews
and syntheses of research offer key information about effective comprehension strategy instruction. Cooperative
learning is the instructional use of small groups so that students work together to maximize their own and each other’s to
learning. Cooperative learning has been demonstrated to be an effective method for improving reading comprehension. The present study investigates the relative effectiveness of two cooperative learning techniques namely the Reciprocal Method and the Jigsaw method in enhancing the reading comprehension of the Engineering students.

ARTIFICIAL INTELLIGENCE IN ERP AND ENTERPRISE SYSTEMS: A REVIEW OF APPLICATIONS, CHALLENGES, GOVERNANCE CONSIDERATIONS, AND FUTURE TRENDS

Bismit Pratapsingh — Thu, 16 Jul 2026 00:00:00 +0000

Enterprise Resource Planning (ERP) systems have evolved from transaction-processing platforms into strategic enterprise systems that support decision-making, operational efciency, and business transformation. Recent advances in Articial Intelligence (AI) have accelerated this evolution by introducing capabilities such as predictive analytics, intelligent automation, machine learning, natural language processing, and decision-support mechanisms into enterprise environments. Organizations across industries are increasingly integrating AI-enabled technologies into ERP and enterprise systems to improve forecasting accuracy, optimize business processes, enhance customer experiences, and support datadriven decision-making. Despite these benets, AI adoption within enterprise systems presents challenges related to data quality, governance, integration complexity, security, explainability, and organizational readiness.This review article examines the current landscape of AI applications in ERP and enterprise systems by synthesizing ndings from existing academic and industry literature. The paper explores key application areas,
including nance, procurement, supply chain management, manufacturing, and customer operations, while highlighting the benets and challenges associated with AI adoption. The review further discusses governance considerations, human oversight requirements, and emerging trends shaping the future of intelligent enterprise systems. The ndings suggest that AI is transforming ERP systems from systems of record into systems of insight and intelligent decision support. However, successful implementation requires a balanced approach that combines technological innovation, effective governance, and human expertise. The paper concludes by identifying future research opportunities and practical considerations for organizations pursuing AI-enabled enterprise transformation.