Please use this identifier to cite or link to this item:

Title: Adaptation and Anxiety Assessment in Undergraduate Nursing Students
Authors: Costa, Ana
Candeias, Analisa
Ribeiro, Célia
Rodrigues, Herlander
Mesquita, Jorge
Caldas, Luís
Araújo, Beatriz
Araújo, Isabel
Vicente, Henrique
Ribeiro, Jorge
Neves, José
Keywords: Adaptation
Anxiety Trait
Artificial Intelligence
Logic Programming
Artificial Neural Networks
Issue Date: 2020
Publisher: Springer
Citation: Costa, 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.
Abstract: The 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.
ISSN: 0302-9743 (paper)
1611-3349 (electronic)
Type: article
Appears in Collections:QUI - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

Files in This Item:

File Description SizeFormat
2020_IDEAL_2020_RD.pdf784.79 kBAdobe PDFView/Open
FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpaceOrkut
Formato BibTex mendeley Endnote Logotipo do DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Dspace Dspace
DSpace Software, version 1.6.2 Copyright © 2002-2008 MIT and Hewlett-Packard - Feedback
UEvora B-On Curriculum DeGois