CDIO (Conceiving-Designing-Implementing-Operating), crowdsourcing and gamification are gaining more popularity in IT education. However, factors that influence learners' attitude toward this method are yet to be discovered. Therefore, this study aims to develop and test a conceptual model of implementing CDIO-based curriculum in IT education. For this purpose, CDIO dimensions were conceptualized and developed into questionnaire items. Then 141 students who experienced the CDIO method in information security course and lab, were sampled through action-research approach to investigate their perceptions and experiences about the learning stages, dimensions and values of this teaching method. Data gathered were analyzed by multiple regression algorithm using Partial Least Squares-Structural Equation Modeling (PLS-SEM) statistical approach. The results reveal that the 'mastery of the concept', 'implement and operate', 'perceived values', 'demonstration and resources', and 'admin' could significantly (in direct and indirect paths) affect learner's intention to accept the CDIO method and adopt it in IT classes. Finally, implications to theory and practice were indicated, and future research directions were suggested.
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http://dx.doi.org/10.1016/j.heliyon.2022.e11433 | DOI Listing |
Med Phys
January 2025
Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Background: A cylindrical free-air chamber, the Attix FAC, is used for absolute air-kerma measurements of low-energy photon beams at the University of Wisconsin Medical Radiation Research Center. Correction factors for air-kerma measurements of specific beams were determined in the 1990s. In order to measure air-kerma rates of beams in development, new correction factors must be computed.
View Article and Find Full Text PDFNeural Netw
January 2025
School of Cyber Science and Engineering, Xi'an Jiaotong University, China. Electronic address:
Detecting anomalies in attributed networks has become a subject of interest in both academia and industry due to its wide spectrum of applications. Although most existing methods achieve desirable performance by the merit of various graph neural networks, the way they bundle node-affiliated multidimensional attributes into a whole for embedding calculation hinders their ability to model and analyze anomalies at the fine-grained feature level. To characterize anomalies from each feature dimension, we propose Eagle, a deep framework based on bipartitE grAph learninG for anomaLy dEtection.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Artificial Intelligence of Sichuan Province, Yibin 644000, China.
Accurately predicting the remaining useful life (RUL) is crucial for ensuring the safety and reliability of aircraft engine operation. However, aircraft engines operate in harsh conditions, with the characteristics of high speed, high temperature, and high load, resulting in high-dimensional and noisy data. This makes feature extraction inadequate, leading to low accuracy in the prediction of the RUL of aircraft engines.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electronic and Telecommunications Systems, Rzeszów University of Technology, Wincentego Pola 2, 35-959 Rzeszow, Poland.
The production of consumer electronics using electrically conductive materials is a dynamically developing sector of the economy. E-textiles (electronic textiles) are also used in radio frequency identification technology, mainly in the production of tag antennas. For economic reasons, it is important that the finished product is universal, although frequencies in radio systems have different values in different regions of the world.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Institute of Microelectronics and Optoelectronics, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland.
A review of natural materials that exhibit negative permittivity or permeability, including gaseous plasma, metals, superconductors, and ferromagnetic materials, is presented. It is shown that samples made of such materials can store large amount of the electric (magnetic) energy and create plasmonic resonators for certain values of permittivity, permeability, and dimensions. The electric and the magnetic plasmon resonances in spherical samples made of such materials are analyzed using rigorous electrodynamic methods, and the results of the analysis are compared to experimental data and to results obtained with other methods.
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