Higher Education Category Submission

359 – AI Learning System Designed to Address the Imbalance in Education Resource Distribution

In the current social situation, while education has become more widespread, the economy still remains uneven, leading a series of educational problem.The educational issues mainly manifest in the unequal distribution of resources and significant disparities between institutions, with some schools investing more in funding, facilities, and faculty. At the same time, there are variations in teaching quality within institutions, affecting both teaching effectiveness and student outcomes. Differences in student abilities further complicate the selection of teaching content and methods. To address the issue of imbalanced distribution of educational resources, we have decided to design an AI learning system. It is built on generative AI with big data algorithms as support. By analyzing students' test results, the system evaluates their understanding of various knowledge points and provides recommended exercises and courses. This system can assist students in learning, helping them overcome their weaknesses, while also easing the burden on teachers. To expand its range of application, we will add more materials to build up the datasets and simplify the system to ensure that everyone can use it easily. We believe this learning system can help solve the problem of unequal distribution of educational resources.

As students, this problem can be seen everywhere in our daily life. When entering high school, our city's key high schools adopted the target attendance system, and many schools had relatively few quotas, or even no quotas. Even if you enter the school through the target, there is a lot of gap with the same batch of students. This gap stems from the uneven educational resources in junior high schools, and the gap between the allocation of teachers in key classes and non-key classes is also very large. The resource gap between key high schools and ordinary high schools is even more obvious.

When I was in high school, the school provided us with a similar learning system, but the functions were still not perfect, and the system was unstable. Therefore, we already have an experimental foundation, and what we need to do is to optimize, improve functions and improve achieveness on this basis. So, that is why we want to design such an applications for every students.

However, we believe that the impact of secondary education on a person in all aspects, including but not limited to grades, vision is huge, and even determines the height of life, so our group raised this question.

Our assumption is that technology can enter the campus and life, make learning life-oriented and integrated into life, reduce students' resistance to learning, appropriately weaken the purpose of learning, and improve students' self-confidence and self-identification.

We chose stream 3.

We will design an AI application which can evaluate students' understanding of knowledge. After that it will recommend individual courses based on test results and provide other support during their study.

The system uses generative AI as the application's foundation. It can analyze student answers and spot gaps in understanding from their exam answers. When weaknesses are found, the system not only recommends relevant practices but also provides personal learning paths and related courses for every student. This function ensures that the student's learning experience is constantly suitable for their needs. By focusing on the student's individual needs, this approach create a more effective learning experience. Instead of simply presenting the same curriculum, the system adapts to each student's unique learning pace and method. It offers exercises to reinforce difficult topics and ensure that students can master the knowledge more effectively.

In order to create this learning system, I think we should use the follow methods. Firstly, we should collect the exam questions and answers from top schools and textbook knowledges from different subjects. Then use NLP to deal with the exam content datasets and turn them into vectors. And uses generative AI models to analyze exam answers and map them to key textbook concepts. It will establish the relationship between exams and courses, which can help build the recommendation system. It is very important to set the model output forms. At this project, the output are students' weakness, recommend exercises and courses. Next, students will be given regular testing opportunities. Based on their responses, the system adjusts the weight of weak knowledge points and the probability of these weak areas in the recommended will increased. At the same time, the system will provided some related courses to help student.

The creativity of this learning system is as follows:

The system combines large AI models with big data algorithms to create the main function. It integrates a variety of exam questions and high-quality course materials from different regions and covering all the subjects, and customizes its recommendations based on the individual needs of each student.

By offering some special learning content, the application aims to improve student scores and make sure they can master every points Its innovative approach ensures students engage with content at their level. And it also adjusts the material to meet their needs. It prevents repetitive practice of topics students have already mastered. Moreover, the intelligent recommendation function will help students learn at a comfortable pace by focusing on areas which they need more practice. So that they can reduce time that spends on the familiar material. It uses exam responses to predict student weaknesses, offering study support and helping students understand the question better.

For teachers, the application offers the strong support by reducing their workload. This will help teachers more focus on knowledge instruction. It can simplify the teaching form and make it more efficient.

In addition, the test function from the system can replace quizzes in class. This gives both students and teachers more flexibility and encourages active learning.

All in all, this application encourages students to learn at their own pace and also improve teacher teaching effectiveness, creating a more comfortable and supportive learning environment for everyone.

In order to improve this system and make it more suitable for every students, we think we should do some efforts in the future:

First of all, the learning system should be continually improved and expand its range of subjects and exam contents. It can make sure that the content of the system remains effective and follow the update of education.

Secondly, we should simplify the UI of system to ensure that everyone can use it easily. It allows students to enter the learning state without feeling anxious. The app will cater to different grades, covering from primary school to university.

Third, we need to use the updated generate AI so that it can make sure the system has the strong foundation of analysis. We also need the AI model can generate the new exam content. It will help improve the datasets and creates a dynamic learning environment that adapts to the individual needs.

In addition to supporting academic growth, the app gives a lot of importance or priority to the well-being of its users. It takes a simple approach to learning, helping to limit excessive screen time. This helps reduce the risk of eye strain and creates healthier habits. The combination of comprehensive content and a user-friendly design improve the sense of experience.

Our main purpose is to hope that AI can enter ordinary people's homes. Our plan can realize the above technologies through application software or applets, whether it is to provide cultural foundation and quality education for the age of education, preschool students who are in line with the learning stage of students, or for working and even middle-aged and elderly retirees. It is easy, simple, cheap and convenient to contact AI. Reduce the time and money costs of some offline education. In this way, relative fairness can be achieved as much as possible, and AI technology should not become a plaything for the rich.

We will regularly issue questionnaires to survey user satisfaction, and continuously correct our shortcomings and defects while ensuring quality. Our technology can also enter the school, keep pace with the times, and constantly absorb fresh opinions.

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