Societal pressures, accreditation organizations, and licensing agencies are emphasizing the importance of ethics in the engineering curriculum. Traditionally, this subject has been taught using dogma, heuristics, and case study approaches. Most recently a number of organizations have sought to increase the utility of these approaches by utilizing the Internet. Resources from these organizations include on-line courses and tests, videos, and DVDs. While these individual approaches provide a foundation on which to base engineering ethics, they may be limited in developing a student's ability to identify, analyze, and respond to engineering ethics situations outside of the classroom environment. More effective approaches utilize a combination of these types of approaches. This paper describes the design and development of an internet based interactive Simulator for Engineering Ethics Education. The simulator places students in first person perspective scenarios involving different types of ethical situations. Students must gather data, assess the situation, and make decisions. This requires students to develop their own ability to identify and respond to ethical engineering situations. A limited comparison between the internet based interactive simulator and conventional internet web based instruction indicates a statistically significant improvement of 32% in instructional effectiveness. The simulator is currently being used at the University of Houston to help fulfill ABET requirements.
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http://dx.doi.org/10.1007/s11948-008-9109-y | DOI Listing |
Mol Neurodegener
January 2025
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA.
TREM2 is a signaling receptor expressed on microglia that has emerged as an important drug target for Alzheimer's disease and other neurodegenerative diseases. While a number of TREM2 ligands have been identified, little is known regarding the structural details of how they engage. To better understand this, we created a protein library of 28 different TREM2 variants that could be used to map interactions with various ligands using biolayer interferometry.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
Background: Quantitative susceptibility mapping (QSM) can study the susceptibility values of brain tissue which allows for noninvasive examination of local brain iron levels in both normal and pathological conditions.
Purpose: Our study compares brain iron deposition in gray matter (GM) nuclei between cerebral small vessel disease (CSVD) patients and healthy controls (HCs), exploring factors that affect iron deposition and cognitive function.
Materials And Methods: A total of 321 subjects were enrolled in this study.
BMC Health Serv Res
January 2025
School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Background: China has always been a country with a high burden of tuberculosis. In order to end TB, the Chinese government launched three plans for TB prevention and control. The Chinese government implemented the National 13th Five-Year plan for Tuberculosis Prevention and Control (2016-2020) to promote TB prevention and control from policy, technology, health promotion and other aspects from 2016 to 2020.
View Article and Find Full Text PDFSelf-regulated learning (SRL) has been regarded as one of the indispensable factors affecting students' academic success in online learning environments. However, the current understanding of the mechanism/causes of SRL in online ill-structured problem-solving remains insufficient. This study, therefore, examines the configural causal effects of goal attributes, motivational beliefs, creativity, and grit on self-regulated learning.
View Article and Find Full Text PDFPlant Methods
January 2025
School of Electronic and Information Engineering, Liaoning Technical University, Huludao, 125105, China.
Apricot trees, serving as critical agricultural resources, hold a significant role within the agricultural domain. Conventional methods for detecting pests and diseases in these trees are notably labor-intensive. Many conditions affecting apricot trees manifest distinct visual symptoms that are ideally suited for precise identification and classification via deep learning techniques.
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