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Research on the Systematization of Discrete Mathematics Knowledge Guided by Big Ideas
LI Gaolin, ZHONG Yaoyao
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DOI:10.17265/2161-623X/2026.05.005
Yancheng Teachers University, Yancheng, China
Discrete Mathematics plays a vital role in formal reasoning and systematic thinking training in computer science education. However, current teaching often faces a structural dilemma of “fragmentation” and “difficulty in establishing a global perspective” due to the differences in symbol systems, proof paradigms, and representation methods across modules. This study introduces the “Big Ideas” and backward instructional design, constructing a knowledge systematization reconstruction paradigm for Discrete Mathematics oriented towards “Five Core Big Ideas - Cross-module Inquiry Units - Two-way Specification Table Evaluation”. The effectiveness is further examined through qualitative methods including classroom observation, teacher interviews, and student interviews. The findings show that systematized teaching guided by Big Ideas helps students form cross-module holistic knowledge frameworks, promotes the development of formal reasoning transfer capability, and significantly enhances learning engagement and self-efficacy.
Discrete Mathematics, Big Ideas, knowledge systematization, OBE, qualitative research
LI Gaolin, ZHONG Yaoyao. (2026). Research on the Systematization of Discrete Mathematics Knowledge Guided by Big Ideas. US-China Education Review A, May 2026, Vol. 16, No. 5, 303-310.
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