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Adaptation and Anxiety Assessment in Undergraduate Nursing Students

2020Book part Restricted access
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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.accessioned2021-01-04T16:00:41Z
dc.date.available2021-01-04T16:00:41Z
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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCosta A., Candeias A., Ribeiro C., Rodrigues H., Mesquita J., Caldas L., Araújo B., Araújo I., Vicente H., Ribeiro J. e Neves J. (2020) Adaptation and Anxiety Assessment in Undergraduate Nursing Students. In: Analide C., Novais P., Camacho D., Yin H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2020. IDEAL 2020. Lecture Notes in Computer Science, vol 12489. Springer, Cham. doi.org/10.1007/978-3-030-62362-3_11pt_PT
dc.identifier.doi10.1007/978-3-030-62362-3_11pt_PT
dc.identifier.isbn9783030623616
dc.identifier.urihttp://hdl.handle.net/10400.14/31538
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relationALGORITMI Research Center
dc.subjectAdaptationpt_PT
dc.subjectAnxietypt_PT
dc.subjectAnxiety traitpt_PT
dc.subjectArtificial Intelligencept_PT
dc.subjectEntropypt_PT
dc.subjectLogic programmingpt_PT
dc.subjectÃrtificial neural networkspt_PT
dc.titleAdaptation and Anxiety Assessment in Undergraduate Nursing Studentspt_PT
dc.typebook part
dspace.entity.typePublication
oaire.awardTitleALGORITMI Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT
oaire.citation.endPage123pt_PT
oaire.citation.startPage112pt_PT
oaire.citation.titleIntelligent Data Engineering and Automated Learning – IDEAL 2020pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSilva Candeias
person.familyNameAraujo
person.familyNameAraújo
person.familyNameVicente
person.familyNameRibeiro
person.familyNameBaère de Faria Campos Neves
person.givenNameAnalisa Lia
person.givenNameBeatriz
person.givenNameIsabel
person.givenNameHenrique
person.givenNameJorge
person.givenNameJosé Alberto
person.identifier.ciencia-id7219-4E30-AA4B
person.identifier.ciencia-id5412-F934-D095
person.identifier.ciencia-id6612-2135-B2D7
person.identifier.ciencia-id0A1F-D79E-6A3A
person.identifier.ciencia-id1310-2CF4-C108
person.identifier.ciencia-id4D1F-B189-47C2
person.identifier.orcid0000-0001-9620-163X
person.identifier.orcid0000-0003-0266-2449
person.identifier.orcid0000-0001-8456-7773
person.identifier.orcid0000-0003-1874-7340
person.identifier.ridF-9714-2015
person.identifier.ridJ-5948-2012
person.identifier.scopus-author-id57193525277
person.identifier.scopus-author-id55355515800
person.identifier.scopus-author-id57197202746
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typebookPartpt_PT
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