<![CDATA[Abstract Mathematics education faces persistent challenges in the form of learning approaches that do not adequately accommodate the diverse cognitive profiles of students. Howard Gardner's Multiple Intelligences (MI) theory asserts that human cognitive capacity extends far beyond the linguistic-logical axis that has dominated mathematics learning in schools. At the same time, Deep Learning (DL), as a contemporary pedagogical paradigm, emphasizes the development of transferable, meaningful, and reflective understanding, rather than merely memorizing superficial procedures. This theoretical study systematically examines the conceptual intersections between MI theory and DL principles in the context of mathematics learning. The findings demonstrate that the alignment between MI and DL is structurally coherent: MI provides an individualized entry point, while DL sets the target for cognitive depth. The integration of the two frameworks results in a differentiated mathematics learning ecosystem capable of fostering critical thinking, problem-solving, metacognitive awareness, and creativity across diverse learner profiles. Keywords: Multiple Intelligences; Deep Learning; Mathematics Education]]>
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