introduction

Generative artificial intelligence technology has demonstrated the ability to create text, image, audio, and video content in the field of education, bringing new changes to educational research. The educational community has studied its effective application, innovative methods, ethical issues, risk avoidance, and impact on the role of teachers in classroom teaching. In foreign language education, generative artificial intelligence assisted teaching has received attention, such as helping students with self-evaluation, enhancing learning awareness, reconstructing reading teaching models, and creating interactive learning environments. However, there is still insufficient research on the integration and application of new technologies in the teaching of high school English reading continuation.

Reconstruction of Read and Write Teaching Supported by Generative Large Models

The teaching of post reading continuation faces challenges such as vague daily teaching objectives, heavy burden of teacher grading, and lack of personalized guidance for students. The research team found through research that generative models can assist teachers in correcting and polishing, creating continuation plots, generating personalized materials, and improving teaching efficiency. In terms of teaching content, artificial intelligence systems make evaluations more personalized, improve teacher review efficiency, and provide personalized feedback to students. In terms of teaching organization, teachers and students can co create knowledge, creating a more dynamic learning environment. Before class, teachers refer to feedback on learning situations to determine teaching objectives. During class, group learning is used to organize students for in-depth interpretation. After class, generative models are used to design layered assignments to meet students' personalized learning needs and promote the development of critical thinking and practical abilities.

Application of Generative Large Models in Teaching Post reading Continuation

This chapter explores the application of generative models in English reading and writing teaching. By analyzing the college entrance examination question "David's Run", this paper demonstrates how to use generative big models to assist teachers in precise lesson preparation, classroom teaching, and homework design. Teachers can use large models to diagnose learning situations, optimize teaching design, and guide students to practice writing through human-computer interaction. Large models can provide diagnostic evaluations, polishing examples, and modification explanations to help students understand the intention of modifications and improve their writing skills. In the classroom, teachers can design human-computer collaborative creative activities to stimulate students' creative writing, and develop students' critical thinking through teacher-student collaborative evaluation. In addition, the large model can generate diverse descriptive materials and micro writing tasks based on the teacher's instructions, innovate homework design, and improve teaching effectiveness.

conclusion

This study constructs a new model of "teacher+student+big model" for reading, writing, and evaluating courses, aiming to promote students' active learning and evaluation, enhance their learning ability and higher-order thinking through generative big models. Teachers should actively explore the application of generative technology in teaching, becoming facilitators of students' ability development and guides for technology application.