An AI-Driven Assistive Writing Framework for Sustainable and Inclusive Education

Research Paper | 2026 | Volume 1 | Issue 1 | Page 66-73

1. Gurmeet Kaur^, Research Scholar, Department of Computer Applications, CT University, Punjab, India

2. Dr. Arvind Kumar, Professor, School of Engineering and Technology, CT University

Corresponding Author:-

Gurmeet Kaur

Research Scholar,

Department of Computer Applications,

CT University, Punjab, India,

Email address: gurmeet.kaur.kalra55@gmail.com

An AI-Driven Assistive Writing Framework for Sustainable and Inclusive Education (1) (1).p

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ABSTRACT:

Writing is a fundamental academic process; nevertheless, numerous people with physical, motor, and learning disabilities have sustained problems with handwriting that tend to restrict the access of mainstream education. Traditional assistive technologies are partial and are not usually adaptable, individualized, or sustainable over time. As recent advancements in the field of Artificial Intelligence (AI), machine learning, and embedded systems have occurred, there is an increasing possibility of developing intelligent assistive solutions that act to address these shortcomings by a greater degree.

The purpose of this research is to develop an AI-powered assistive writing system that would provide writing disabled individuals with real-time handwriting guidance, speech recognition, and error detection and correction. The framework combines input acquisition via sensors, machine-learning methods of handwriting pattern recognition, and natural language processing (NLP) methods of adaptive feedback. The system is programmed to acquire user specific writing behavior, and give individualized instructions to enhance accuracy in writing, legibility and speed.

The concept of sustainability is included by focusing on energy saving hardware, modular system structure, and low-cost design applicable to long-term application in education and rehabilitation setting. The suggested structure is focused on access, cost, and its scalability, hence it can be applied to both inclusive classrooms and special education facilities and therapy facilities. The anticipated value of the research is a conceptual framework capable of being scaled and helping to develop prototypes and conduct real-world validation of the inclusive learning and assistive rehabilitation in the future.

Keywords: Artificial Intelligence, Assistive Technology, Sustainable Education, Inclusive Learning, Smart Writing Systems.