Adaptation and Anxiety Assessment in Undergraduate Nursing Students

dc.contributor.authorCosta, Ana
dc.contributor.authorCandeias, Analisa
dc.contributor.authorRibeiro, Célia
dc.contributor.authorRodrigues, Herlander
dc.contributor.authorMesquita, Jorge
dc.contributor.authorCaldas, Luís
dc.contributor.authorAraújo, Beatriz
dc.contributor.authorAraújo, Isabel
dc.contributor.authorVicente, Henrique
dc.contributor.authorRibeiro, Jorge
dc.contributor.authorNeves, José
dc.date.accessioned2020-11-03T14:59:28Z
dc.date.available2020-11-03T14:59:28Z
dc.date.issued2020
dc.description.abstractThe experiences and feelings in a first phase of transition from undergraduate to graduate courses may lead to some kind of anxiety, depression, malaise or loneliness that are not easily overwhelmed, no doubt the educational character of each one comes into play, since the involvement of each student in academic practice depends on his/her openness to the world. In this study it will be analyzed and evaluated the relationships between academic experiences and the correspondent anxiety levels. Indeed, it is important not only a diagnose and evaluation of the students’ needs for pedagogical and educational reorientation, but also an identification of what knowledge and attitudes subsist at different stages of their academic experience. The system envisaged stands for a Hybrid Artificial Intelligence Agency that integrates the phases of data gathering, processing and results’ analysis. It intends to uncover the students’ states of Adaptation, Anxiety and Anxiety Trait in terms of an evaluation of their entropic states, according to the 2nd Law of Thermodynamics, i.e., that energy cannot be created or destroyed; the total quantity of energy in the universe stays the same. The logic procedures are based on a Logic Programming approach to Knowledge Representation and Reasoning complemented with an Artificial Neural Network approach to computing.por
dc.identifier.authoremaila45330@gmail.com
dc.identifier.authoremailacandeias@ese.uminho.pt
dc.identifier.authoremailcelia.ribeiro1984@gmail.com
dc.identifier.authoremailtwinscorpion@gmail.com
dc.identifier.authoremailtwinscorpion@gmail.com
dc.identifier.authoremailluiscaldas@gmail.com
dc.identifier.authoremailbea9araujo@gmail.com
dc.identifier.authoremailisabel.araujo@ipsn.cespu.pt
dc.identifier.authoremailhvicente@uevora.pt
dc.identifier.authoremailjribeiro@estg.ipvc.pt
dc.identifier.authoremailjneves@di.uminho.pt
dc.identifier.citationCosta, A., Candeias, A., Ribeiro, C., Rodrigues, H., Mesquita, J., Caldas, L., Araújo, B., Araújo, I., Vicente, H., Ribeiro, J. & Neves, J., Adaptation and Anxiety Assessment in Undergraduate Nursing Students. Lecture Notes in Computer Science, 12489: 112–123, 2020.por
dc.identifier.doi10.1007/978-3-030-62362-3_11por
dc.identifier.issn0302-9743 (paper)
dc.identifier.issn1611-3349 (electronic)
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-62362-3_11
dc.identifier.urihttp://hdl.handle.net/10174/28306
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSpringerpor
dc.rightsopenAccesspor
dc.subjectAdaptationpor
dc.subjectAnxietypor
dc.subjectAnxiety Traitpor
dc.subjectArtificial Intelligencepor
dc.subjectEntropypor
dc.subjectLogic Programmingpor
dc.subjectArtificial Neural Networkspor
dc.titleAdaptation and Anxiety Assessment in Undergraduate Nursing Studentspor
dc.typearticlepor

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