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Engineering drawing is a cornerstone course for engineering students, focusing primarily on the communication and interpretation of visual and spatial concepts (Wankat & Oreovicz, 2015). Historically, physical models have been used to elucidate fundamental principles; however, this approach faces several limitations, particularly in larger classrooms where visibility and interactivity are often compromised (Churchill et al., 2012; Barker & Garvin-Doxas, 2004). Additionally, the logistics of transporting these models and the expenses related to their upkeep can be substantial barriers (Schultmann et al., 2006; Ben Mohamed et al., 2017). In light of these challenges and the rapid advancements in artificial intelligence (AI) and computing capabilities, there is a compelling opportunity to innovate the teaching methodology (Pedro et al., 2019; Guan et al., 2020; Luan et al., 2020).
The emergence of AI technologies has enabled educators to overcome these issues through the development of a virtual model repository (Cope et al., 2021). Such a digital platform facilitates clearer and more dynamic presentations, significantly reducing the dependency on physical resources (Langley & Leyshon, 2017). Furthermore, aligning course content with Bloom's taxonomy—a framework for categorizing educational objectives—allows educators to tailor their teaching strategies to accommodate diverse learning needs (West, 2023; Barari et al., 2022). Consequently, a blended learning approach, which combines the strengths of traditional face-to-face instruction with the advantages of online resources, has emerged as a viable solution (Singh et al., 2021; Cheung & Hew, 2011).
This manuscript explores the redesign of engineering drawing courses using a blended learning model, supported by an online education integrated platform. We underscore the importance of structuring content that is both pedagogically robust and technologically enhanced. Our focus includes the design of teaching objectives, the creation of an information-rich learning environment, the organization of course content, the facilitation of teaching activities, and the implementation of evaluation methods. The overarching goal is to create a learning experience that is not only informative but also adaptive and engaging, thereby enhancing students' understanding and mastery of the subject matter.
Early implementations have yielded promising results, indicating that this blended approach could serve as a model for other technical courses aiming to incorporate modern teaching practices. The integration of AI into educational contexts promises to revolutionize teaching, administration, and assessment, leading to a qualitative improvement in educational outcomes. Intelligent technology is expected to catalyze disruptive changes, ushering in a new era of education marked by personalization, adaptability, and effectiveness.