The existence of learning without awareness has been debated for many years. Learning without awareness is said to occur when an individual's behavior has been affected without that individual being aware of the conditions affecting the behavior, of the relationship between those conditions and the behavior, or of the fact that the behavior has changed. This paper describes a series of experiments investigating this phenomenon. The findings support the existence of "learning without awareness." However, it is argued that the term "awareness" should be discarded as it is misleading. Instead, the results of the experiments are discussed in terms of behavior for which the individual does not provide a complete verbal account.
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http://dx.doi.org/10.1007/BF03393031 | DOI Listing |
JMIR Mhealth Uhealth
January 2025
Department of Learning and Workforce Development, The Netherlands Organisation for Applied Scientific Research, Soesterberg, Netherlands.
Background: Wearable sensor technologies, often referred to as "wearables," have seen a rapid rise in consumer interest in recent years. Initially often seen as "activity trackers," wearables have gradually expanded to also estimate sleep, stress, and physiological recovery. In occupational settings, there is a growing interest in applying this technology to promote health and well-being, especially in professions with highly demanding working conditions such as first responders.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Statistics and Data Science, Jahangirnagar University, Dhaka, 1342, Bangladesh.
Background: Child mortality is a reliable and significant indicator of a nation's health. Although the child mortality rate in Bangladesh is declining over time, it still needs to drop even more in order to meet the Sustainable Development Goals (SDGs). Machine Learning models are one of the best tools for making more accurate and efficient forecasts and gaining in-depth knowledge.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, 10300, Thailand.
Attention mechanisms such as the Convolutional Block Attention Module (CBAM) can help emphasize and refine the most relevant feature maps such as color, texture, spots, and wrinkle variations for the avocado ripeness classification. However, the CBAM lacks global context awareness, which may prevent it from capturing long-range dependencies or global patterns such as relationships between distant regions in the image. Further, more complex neural networks can improve model performance but at the cost of increasing the number of layers and train parameters, which may not be suitable for resource constrained devices.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Institute on Digital Health and Innovation, College of Nursing, Florida State University, Tallahassee, FL, United States.
Background: In Alabama, the undiagnosed HIV rate is over 20%; youth and young adults, particularly those who identify as sexual and gender minority individuals, are at elevated risk for HIV acquisition and are the only demographic group in the United States with rising rates of new infections. Adolescence is a period marked by exploration, risk taking, and learning, making comprehensive sexual health education a high-priority prevention strategy for HIV and sexually transmitted infections. However, in Alabama, school-based sexual health and HIV prevention education is strictly regulated and does not address the unique needs of sexual and gender minority teenagers.
View Article and Find Full Text PDFCBE Life Sci Educ
March 2025
Department of Chemistry, University of Utah, Salt Lake City, UT 84112.
There is a growing emphasis for professional development programs that teach instructors about inclusive Science, Technology, Engineering, and Mathematics (STEM) practices and the impact of instructor and student identities on these practices. As instructors implement these practices, there is a need for instructors, departments, and faculty developers to measure instructor progress and to help identify next steps in improving inclusive STEM teaching. This study describes the development of the Faculty Inclusive Teaching Survey (FITS) using scale-development theory, frameworks using Clarke and Hollingsworth's interconnected model of professional growth and Dewsbury's Deep Teaching model, and higher-education STEM, Diversity, Equity, and Inclusion, and professional development literature.
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