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How AI in education reduces inequality

ByRishabh Ranjan
Oct 18, 2024 09:00 AM IST

This article is authored by Rishabh Ranjan, chief data scientist, ConveGenius.AI.

The advent of Artificial Intelligence (AI) and especially, large language models (LLMs) have transformed how we perform daily tasks–from drafting emails to generating creative content, from data analysis to language translation. This technological leap has not only increased productivity of employees across industries but has also made processes more efficient and robust. In education, AI is unlocking new possibilities that were once tedious and considered futuristic. The possibilities of AI in education are vast, encompassing improvements in administrative efficiency and the enhancement of student learning experiences. By examining the various applications of AI, we can see how it has fundamentally transformed the world of learning for students, offering a unique perspective on its far-reaching impact.

Artificial Intelligence.(Getty Images/iStockphoto)

Educators are leveraging AI powered tools to create personalised learning experiences in classrooms–catering to diverse learning needs of children, even those with special needs. Tuned AI learning engines and robust algorithms ensure that students receive timely support and resources to thrive, making learning more accessible. By tailoring instruction to individual learning styles and paces, AI can ensure that every student has an equal opportunity to succeed.

On the other hand, simultaneously being applied to automate manual tasks--AI-powered tools are assisting teachers in automating assessments, grading, and generating reports with smart and actionable insights as well as managing attendance records. Moreover, it is also bridging the communication channels between parents and students such as distributing classroom materials and resources. Automation of these tasks is helping teachers reduce the time they spend on administrative work and focus more on classroom teaching and improving student learning outcomes.

Making personalised learning a pedagogical approach that tailors instruction to the individual needs, interests, and abilities of each student. With the help of AI, it has become much easier to track a students’ learning level in real-time and provide personalised recommendations and feedback. AI can predict user behaviour and provide recommendations to teachers attributing drop-out rates across online learning modules. By analysing students’ performance, it is now made possible to provide them with targeted resources and study paths that suit the learning needs and pace of each student.

Adaptive learning is a technology-driven approach that adjusts the pace and content of instruction based on a student's performance. AI-powered platforms can continuously monitor student progress and adjust the difficulty level of assignments accordingly. It also gives hints and recommends supplementary material to assist students in adaptive learning. This responsive approach ensures students remain challenged while avoiding frustration, creating a more engaging learning experience.

Traditional assessment methods can be time-consuming, but AI streamlines the process of creating and conducting assessments. Automated tools can generate quizzes and tests tailored to the specific needs of a class or individual students. Moreover, many tools now empower teachers to reduce the time they spend on data entry of student scores through AI-powered scanning tools. Even proctoring of examinations has become more effective in remote or large settings. In addition, evaluating assessments has become much faster, specially grading and analysis of multiple-choice questions or true and false questions. Not only does it help analyse the performance of the classroom on learning outcomes, it also helps analyse the student wise trends across different tests. These insights are helping teachers focus on targeted interventions and take remedial actions.

Today, it is much simpler for educators to track daily practise assignments of students and their performance that was earlier not possible without technology. AI can provide educators with real-time data and insights into student performance, allowing them to identify areas where students may be struggling and intervene early. This data can also be used to inform instructional decisions and improve teaching practices.

AI-powered systems such as virtual tutors and learning assistants provide students with instant support for their doubts and queries. Rather than waiting for the next classroom session, students can receive help as soon as they face challenges, which promotes continuous learning. AI-powered chatbots are popular amongst students allowing them to ask doubts and get answers in the absence of a teacher. This has expanded the scope and scale of learning outside of teaching hours or in areas where access to teachers is limited.

Many education organisations are using AI to create immersive, interactive language learning experiences tailored to the learner’s progress and proficiency. These platforms offer personalised feedback, helping learners improve their grammar, pronunciation, and vocabulary in a more targeted and effective manner. In addition, the efficiency of language translation using technology has improved across the globe. These technological advancements have made access to learning different languages much simpler over the years, helping students to develop and polish their language skills.

Teachers can now use AI to simplify the process of creating lesson plans. AI systems analyse curriculums, student data, and educational standards to suggest optimised lesson plans that align with specific learning objectives. This helps teachers deliver more organised and coherent lessons, improving the overall learning experience for students.

Furthermore, decision makers and policy makers are increasingly leveraging real-time and more accurate data to inform their decisions and improve education governance. By analysing large datasets on student performance, teacher effectiveness, and resource allocation, policymakers and decision-makers can identify trends, identify areas for improvement, and allocate resources and budgets more efficiently. AI-powered data analytics can also help to measure the impact of educational policies and interventions, allowing policymakers to make evidence-based decisions and refine their strategies accordingly.

AI is transforming the effectiveness of teaching, administration, and learning across various educational settings. Whether in small classrooms or large, AI's ability to personalise learning, streamline administrative tasks, and provide real-time support is enhancing both teacher effectiveness and student engagement. As AI continues to evolve, its role in promoting equitable, high-quality education will only grow, benefitting diverse groups and helping bridge educational divides.

This article is authored by Rishabh Ranjan, chief data scientist, ConveGenius.AI.

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