Bloomarch Learning Framework: Integration of Generative Ai and Cognitive Progression In The Teaching of Architecture and Computer Organization

Architecture and Computer Organization is a demanding first-year course in which students must connect abstract concepts with procedural skills. This paper presents the BloomArch Learning Framework (BELF), an instructional model that integrates generative AI (GenAI) with explicit cognitive progression (Bloom’s Taxonomy) and cognitive engagement (ICAP). BELF implements a spiral TP–LP–AS cycle: (i) theoretical-practical classes using active micro-challenges, guided discussion and feedback, supported by NotebookLM and a teacher-curated self-study prompt for ChatGPT; (ii) supervised labs where GenAI is constrained to explanation and reasoning support, preserving authenticity in tasks such as Assembly programming; and (iii) autonomous study emphasizing metacognition, self-assessment and formative assessment aligned with Bloom/ICAP. BELF was evaluated with a cross-sectional questionnaire (33 items, 7-point Likert) completed by 60 students; analyses included 47 who confirmed using BELF. Reliability was high (α_total=0.955; α=0.81–0.90 per dimension). All dimension means were significantly above the neutral midpoint (p<0.001), and an exploratory factor analysis indicated a single dominant factor accounting for 74.43% of the variance. Multiple regression showed overall satisfaction is mainly predicted by perceived GenAI integration and metacognition/autonomy (F(2,44)=40.403; R²=0.647; adjusted R²=0.631).