AI-Assisted Design and Implementation of Teaching-Learning-Assessment Integration in Junior High School English

Abstract

Teaching-learning-assessment integration represents a core educational principle outlined in the 2022 Compulsory Education English Curriculum Standard. Within conventional junior high school English in-struction, lesson planning largely depends on teachers’ accumulated practical experience. Such subjective decision-making often creates misalignment among instructional objectives, classroom activities, and assessment tasks. Objectives cannot effectively guide classroom practice, learning tasks drift away from intended teaching outcomes, and assessment fails to deliver timely, targeted evidence of student progress. Artificial intelligence opens new practical possibilities to ease these persistent instructional challenges. This study constructs a complete implementation model supported by artificial intelligence, and elaborates its practical operation through a concrete classroom case based on PEP (People’s Education Press) junior high English teaching materials implemented in Zhengzhou, Henan Province. With AI-enabled data analysis, instructional planning, multi-dimensional feedback, and adaptive guidance, educators can interpret textbook content in depth, generate objective learner profiles, and obtain actionable teaching suggestions. Human teachers and artificial intelligence function as collaborative partners throughout the whole in-structional cycle. Joint efforts support the coherent design of teaching objectives, learning activities and assessment tasks, facilitate the effective achievement of curriculum goals, and foster comprehensive core-competence development among junior high English learners.