Self-learning is receiving great attention internationally in different fields, along with the best utilization of different computational applications or methods. This paper introduces a novel computational approach for supporting Architectural Design Education (ADE) in its early stages; a computational implementation through MATLAB has been developed to conduct the proposed processes. As a scope, spaces’ furnishing design has been selected to demonstrate the proposed computational approach and implementation, while office workspaces have been selected as a representative case. However, the proposed approach provides and enhances ADE through three main concepts: (a) generating design alternatives for different cases of furnishing spaces, (b) providing accurate and flexible evaluations to students’/designers’ works with different levels, and (c) tracking students based on their defaults and relevant sensitive modifications. Different applications of the proposed approach have been generated, analyzed, and validated.
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