Background: Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education.
Objective: The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers.
Methods: Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities.
Results: All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such approaches in both the preparation and the effective use of these activities in the classroom. Specifically, the themes highlighted by a greater number of teachers after analyzing the responses to the open-ended questions were the usefulness of BioAnnote system to provide reliable sources of medical information and the usefulness of the bilingual nature of CLEiM system for learning medical terminology in English.
Conclusions: Three intelligent information access systems were successfully used to evaluate the teacher's perceptions regarding the utility of these systems in learning activities. The results of this study showed that integration of reliable sources of information, bilingualism and selective annotation of concepts were the most valued features by the teachers, who also considered the incorporation of these systems into learning activities to be potentially very useful. In addition, in the context of our experimental conditions, our work provides useful insights into the way to appropriately integrate this type of intelligent information access systems into learning activities, revealing key themes to consider when developing such approaches.
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http://dx.doi.org/10.1016/j.ijmedinf.2017.12.016 | DOI Listing |
ACS Sens
December 2024
College of Integrated Circuits, Taiyuan University of Technology, Taiyuan 030024, China.
By analyzing facial features to perform expression recognition and health monitoring, facial perception plays a pivotal role in noninvasive, real-time disease diagnosis and prevention. Current perception routes are limited by structural complexity and the necessity of a power supply, making timely and accurate monitoring difficult. Herein, a self-powered poly(vinyl alcohol)-gellan gum-glycerol thermogalvanic gel patch enabling facial perception is developed for monitoring emotions and atypical pathological states.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon, Republic of Korea.
The increasing utilization of deep learning models in drug repositioning has proven to be highly efficient and effective. In this study, we employed an integrated deep-learning model followed by traditional drug screening approach to screen a library of FDA-approved drugs, aiming to identify novel inhibitors targeting the TNF-α converting enzyme (TACE). TACE, also known as ADAM17, plays a crucial role in the inflammatory response by converting pro-TNF-α to its active soluble form and cleaving other inflammatory mediators, making it a promising target for therapeutic intervention in diseases such as rheumatoid arthritis.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Life Sciences, Centre for Clinical and Cognitive Neuroscience, Brunel University London, Kingston Lane, Uxbridge, Middlesex, United Kingdom.
Multitasking (MT)-performing more than one task at a time-has become ubiquitous in everyday life. Understanding of how MT is learned could enable optimizing learning regimes for tasks and occupations that necessitate frequent MT. Previous research has distinguished between MT learning regimes in which all tasks are learned in parallel, single-task (ST) learning regimes in which all tasks are learned individually, and mixed learning regimes (Mix) in which MT and ST regimes are mixed.
View Article and Find Full Text PDFPLoS Comput Biol
December 2024
Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Canada.
Treatment for major depressive disorder (depression) often has partial efficacy and a large portion of patients are treatment resistant. Recent studies implicate reduced somatostatin (SST) interneuron inhibition in depression, and new pharmacology boosting this inhibition via positive allosteric modulators of α5-GABAA receptors (α5-PAM) offers a promising effective treatment. However, testing the effect of α5-PAM on human brain activity is limited, meriting the use of detailed simulations.
View Article and Find Full Text PDFJ Comput Neurosci
December 2024
Department of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, 19104, PA, USA.
Traveling waves of neuronal spiking activity are commonly observed across the brain, but their intrinsic function is still a matter of investigation. Experiments suggest that they may be valuable in the consolidation of memory or learning, indicating that consideration of traveling waves in the presence of plasticity might be important. A possible outcome of this consideration is that the synaptic pathways, necessary for the propagation of these waves, will be modified by the waves themselves.
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