The rapid integration of generative artificial intelligence (AI) into higher education raises questions about its pedagogical value and its role in sustainability-oriented learning. This study investigates the use of AI in a Challenge-Based Learning (CBL) engineering hackathon (INDUSHack) focused on the Sustainable Development Goals (SDGs), examining patterns of AI adoption, perceived benefits and risks, and its contribution to SDG integration in project design. A descriptive exploratory design was employed, collecting questionnaire data from 60 undergraduate participants and complementing these with expert committee evaluations of project outcomes. Results indicate widespread AI use, primarily for idea generation, information synthesis, and project structuring. Participants reported perceived improvements in efficiency, creativity, and the clarity of SDG alignment; however, difficulties persisted in translating sustainability concepts into measurable, technically grounded criteria. The findings suggest that while AI can support learning processes and sustainability framing in CBL environments, its effective use requires structured guidance and critical AI literacy to ensure meaningful integration of SDGs.
Sandra Delfa-Baena, Maria Boluda-Prieto, Carla Terron-Santiago et al.· Knowledge· 0 citations
Induction machine fault diagnosis using current spectral analysis is a well-established diagnostic technique based on the identification of the characteristic harmonic components generated in the machine current by each type of fault. However, one of the main problems with the application of this technique to the diagnosis of rotor asymmetry faults in induction machines is that the fault components have much lower amplitudes than the fundamental component and can be very close to it, making their detection difficult, especially in transient regimes. To improve the detection of fault harmonics, this work proposes a new diagnostic current signal, the backward-rotating transient current signal, which is generated in the time domain using the Hilbert transform of the stator currents and is free of the strong influence of the fundamental component. The key novelty of this proposal is the combination of the analytical current signals and the symmetrical components method, which produces a purely backward-rotating transient current signal that cannot be obtained using the raw phase current signals. This proposal is presented theoretically and validated in transient regime using a commercial induction motor with rotor asymmetries.
J. Martínez-Román, R. Puche-Panadero, Carla Terron-Santiago et al.· IEEE Transactions on Instrum...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
