Character Data Mining in Educational Scene

Abstract

Teaching and learning have been completely transformed by the quick growth of information technologies like big data, artificial intelligence, and the Internet of Things. Traditional educational methods can no longer satisfy the demands of modern fast-paced and lifelong learning, making the mining of educational data more urgent. Character mining in images is increasingly applied in educational settings. Artificial intelligence and machine learning algorithms, learning behaviors, such as CNN(Convolutional Neural Networks and RNN()Recurrent Neural Networks), have been used, to predict student performance, and provide personalized recommendations for educational resources. Therefore, research on the application of character mining in educational scenes should be conducted and implemented using OCR technology and the CRNN algorithm. The prediction and mining results are promising and hold commercial value. With the diversification of educational scenarios, the adaptability and flexibility of algorithms will become important research directions. Ultimately, the advancement of these technologies will further drive the digital transformation of education, providing learners with richer and more efficient learning resources.