Transforming Teaching and Learning through LIFT: A Structured Dashboard for Education 5.0

The rapid advancement of digital technologies calls for innovative approaches in language and education that are inclusive, adaptive, and future-ready. This project introduces LIFT (Learning Input Feedback Transformation), a structured dashboard designed to elevate teaching and learning by guiding students from initial input to meaningful outcomes through continuous feedback. The core innovation of LIFT lies in its integration of AI with multilingual and assistive tools, ensuring that learning is both personalized and inclusive, particularly for marginalized and differently abled students. The dashboard is structured into four interconnected components. Learner Engagement (Input Layer) collects data on learning styles, language proficiency, progress, and accessibility needs using tools such as voice-to-text, real-time translation, and sign language recognition. AI Analytics (Processing Layer) applies adaptive algorithms and natural language processing to tailor content, forecast learner performance, and deliver timely support. Teaching and Learning Enhancement generates individualized lesson plans, interactive learning materials, automated grading, and AI-assisted coaching to improve engagement and outcomes. Finally, Feedback and Continuous Improvement ensures personalized feedback for learners and provides educators with actionable insights for refinement. By blending educational creativity with technological inclusion, LIFT ensures that AI complements rather than replaces educators. Its adaptive, multilingual design supports Education 5.0 and advances Sustainable Development Goal 4 (Quality Education). Ultimately, LIFT redefines knowledge delivery and accessibility, making education a powerful enabler of empowerment, equity, and innovation.

Digital technologies, teaching and learning, language, education

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