{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:42:20Z","timestamp":1760060540301,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T00:00:00Z","timestamp":1757376000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The rapid development of smart home and building technologies requires educational methods that facilitate the integration of theoretical knowledge with practical, system-level design skills. Computer-assisted tools play a crucial role in this process by enabling students to experiment with complex Internet of Things (IoT) and building automation ecosystems in a risk-free, iterative environment. This paper proposes a pedagogical framework that integrates simulation-based prototyping with collaborative and spatial design tools, supported by elements of design thinking and blended learning. The approach was implemented in a master\u2019s-level Smart Building Systems course, to engage students in interdisciplinary projects where virtual modeling, digital collaboration, and contextualized spatial design were combined to develop user-oriented smart space concepts. Analysis of project outcomes and student feedback indicated that the use of simulation and visualization platforms may enhance technical competencies, creativity, and engagement. The proposed framework contributes to engineering education by demonstrating how computer-assisted environments can effectively support practice-oriented, user-centered learning. Its modular and scalable structure makes it applicable across IoT- and automation-focused curricula, aligning academic training with the hybrid workflows of contemporary engineering practice. Concurrently, areas for enhancement and modification were identified to optimize support for group and creative student work.<\/jats:p>","DOI":"10.3390\/computers14090379","type":"journal-article","created":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T12:15:17Z","timestamp":1757420117000},"page":"379","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Design Thinking Approach and Simulation Tools in Smart Building Systems Education: A Case Study on Computer-Assisted Learning for Master\u2019s Students"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9186-2444","authenticated-orcid":false,"given":"Andrzej","family":"O\u017cadowicz","sequence":"first","affiliation":[{"name":"Department of Power Electronics and Energy Control Systems, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Krakow, al. Mickiewicza 30, 30-059 Krakow, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,9]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Naccarelli, R., Casaccia, S., Pirozzi, M., and Revel, G.M. (2022). Using a Smart Living Environment Simulation Tool and Machine Learning to Optimize the Home Sensor Network Configuration for Measuring the Activities of Daily Living of Older People. Buildings, 12.","key":"ref_1","DOI":"10.3390\/buildings12122213"},{"doi-asserted-by":"crossref","unstructured":"Littlewood, J.R., Jain, L., and Howlett, R.J. (2024). A Data-Driven Approach to Evaluate the Smart Readiness Indicator for the Functionality \u201cRespond to Users\u2019 Needs\u201d. Sustainability in Energy and Buildings 2023, Springer Nature.","key":"ref_2","DOI":"10.1007\/978-981-99-8501-2"},{"doi-asserted-by":"crossref","unstructured":"Koh, J.H.L., Chai, C.S., Wong, B., and Hong, H.-Y. (2015). Design Thinking and Education. 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