To optimize the training mode of academic morphological awareness for English majors, this paper adopts Cognitive Load Theory as the analytical framework, systematically clarifies the three-dimensional structure of academic morphological awareness, and explicates the dynamic interaction mechanism of intrinsic, extraneous, and germane cognitive loads during morphological processing. It confirms that the balanced regulation of cognitive load is the key to achieving efficient cognitive processing of academic morphemes. On this basis, this paper proposes targeted implementation strategies, including constructing a hierarchical academic morpheme resource library, building an Artificial Intelligence (AI) prompting dynamic regulation model integrated with multimodal evaluation, and improving the teaching collaboration mechanism. These strategies aim to break through the limitation of traditional morphological teaching that prioritizes knowledge indoctrination over cognitive principles, achieve targeted regulation of cognitive load, and ultimately construct a new academic morpheme training model integrating technological empowerment and cognitive mechanisms. By constructing a theoretical bridge for the synergistic integration of AI technology and second language teaching, this study proposes practical approaches for academic vocabulary teaching among English majors and pioneers a novel paradigm for the intelligent transformation of second language instruction.

Lin Xin. The Processing Mechanism of Academic Morphological Awareness among English Majors from the Perspective of Cognitive Load Theory—Construction of a Dynamic Regulation Model Based on AI Hierarchical Prompting. Frontiers in Educational Research (2026), Vol. 9, Issue 1: 108-114. https://doi.org/10.25236/FER.2026.090116.

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