A Review On  AI (Artificial Intelligence) In Teaching And Learning Pharmaceutical Sciences And Medicine.

Dr.Ajinkya U. Fandade; Ms. Nandinee P. Lavhe; Mr. Atharva R. Sankhe; Ms. Runali D. Patil

A Review On AI (Artificial Intelligence) In Teaching And Learning Pharmaceutical Sciences And Medicine.

Authors: Dr.Ajinkya U. Fandade, Ms. Nandinee P. Lavhe, Mr. Atharva R. Sankhe, Ms. Runali D. Patil

Unique Paper ID: 172862
Volume: 11
Issue: 9
PageNo: 1083-1090

Keywords: Artificial intelligence pharmaceuticals science Machine learning teaching methodologies

Abstract:
Artificial Intelligence (AI) has emerged as a transformative force in education, particularly in pharmaceutical sciences and medicine. AI-driven technologies, including machine learning, natural language processing, and intelligent tutoring systems, are reshaping traditional teaching methodologies by enhancing personalized learning, improving knowledge retention, and facilitating real-time feedback. This review explores the various applications, benefits, and challenges of AI in teaching and learning within these fields.One of the most significant contributions of AI in pharmaceutical and medical education is its ability to create adaptive learning environments. AI-powered platforms analyze students’ learning patterns and tailor educational content to match individual needs, thereby improving comprehension and engagement. Virtual and augmented reality (VR/AR) applications, coupled with AI, provide immersive simulations that enhance the understanding of complex biological and pharmacological concepts. These tools allow students to practice clinical decision-making, drug formulation, and patient interactions in a risk-free setting, bridging the gap between theoretical knowledge and practical application.Moreover, AI enhances medical and pharmaceutical research education by offering predictive analytics and big data analysis. AI algorithms process vast amounts of clinical and pharmacological data, enabling students and researchers to identify patterns, predict drug interactions, and understand disease mechanisms more efficiently. AI-powered chatbots and virtual assistants also support learners by providing instant access to medical literature, answering queries, and offering explanations for complex topics, thereby improving knowledge accessibility and self-directed learning.Another promising aspect of AI in education is its role in automating assessments and providing instant, data-driven feedback. AI-driven evaluation tools help educators assess student performance more accurately, identify areas requiring improvement, and personalize remedial actions. Additionally, AI enhances peer-to-peer learning by facilitating discussion forums, intelligent tutoring systems, and collaborative research platforms, fostering a more interactive and engaging learning environment.Despite its numerous advantages, the integration of AI in pharmaceutical and medical education presents several challenges. Ethical considerations regarding data privacy, algorithm bias, and the potential reduction of human interaction in education must be carefully addressed. Additionally, the implementation of AI requires substantial investment, technical expertise, and faculty training to ensure its effective utilization. Resistance to change among educators and institutions further complicates the adoption of AI-based learning tools. AI has the potential to revolutionize teaching and learning in pharmaceutical sciences and medicine by personalizing education, improving engagement, and enhancing research capabilities. However, its successful implementation requires addressing ethical concerns, technological limitations, and institutional barriers. Future research should focus on optimizing AI-driven educational models, ensuring their accessibility, and evaluating their long-term impact on medical and pharmaceutical education. As AI continues to evolve, its integration into academia will be instrumental in shaping the future of healthcare education and practice.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 9
PageNo: 1083-1090

A Review On AI (Artificial Intelligence) In Teaching And Learning Pharmaceutical Sciences And Medicine.

Available:https://ijirt.org/Article?manuscript=172862

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Impact Factor
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UGC Approved
Journal no 47859

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