Research on the Innovation of Ideological Political Education Teaching Mode in English Reading Courses from the Perspective of Human Machine Collaboration

Abstract

Against the dual backdrop of the digital transformation of education and the development of the holistic ideological‑political education system, human‑machine collaboration opens up new possibilities for in‑depth reforms of ideological‑political education in college English reading courses. At present, ideological‑political education in college English reading courses is confronted with three dilemmas: fragmented integration of ideological‑political elements, insufficient effectiveness of human‑machine collaboration, and difficulties in quantifying educational outcomes. Supported by distributed cognition theory, sociocultural theory and human‑machine collaborative teaching theory, this study constructs a “teacher‑student‑machine” ternary collaborative teaching mode for ideological‑political education in college English reading courses, and develops a three‑phase implementation pathway: pre‑class AI‑assisted pre‑mining of ideological‑political elements and learning situation analysis; in‑class human‑machine‑collaborative in‑depth reading and interactive critical thinking; post‑class AI‑driven value internalization and evidence‑based evaluation. This study also reflects on practical challenges concerning technology applicability, teachers’ competencies and evaluation systems in the practice of human‑machine‑collaborative ideological‑political education.