Adaptation and anxiety assessment in undergraduate nursing students

Ana Costa; Analisa Candeias; Célia Ribeiro; Herlander Rodrigues; Jorge Mesquita; Luís Caldas; Beatriz Araújo; Isabel Araújo; Henrique Vicente; Jorge Ribeiro; José Neves

doi:10.1007/978-3-030-62362-3_11

Adaptation and anxiety assessment in undergraduate nursing students

Ana Costa, Analisa Candeias, Célia Ribeiro, Herlander Rodrigues, Jorge Mesquita, Luís Caldas, Beatriz Araújo, Isabel Araújo, Henrique Vicente, Jorge Ribeiro, José Neves^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings
Editors	César Analide, Paulo Novais, David Camacho, Hujun Yin
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	112-123
Number of pages	12
ISBN (Print)	9783030623616
DOIs	https://doi.org/10.1007/978-3-030-62362-3_11
Publication status	Published - 2020
Event	21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 - Guimaraes, Portugal Duration: 4 Nov 2020 → 6 Nov 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12489 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020
Country/Territory	Portugal
City	Guimaraes
Period	4/11/20 → 6/11/20

Keywords

Adaptation
Anxiety
Anxiety trait
Artificial Intelligence
Artificial neural networks
Entropy
Logic Programming

Access to Document

10.1007/978-3-030-62362-3_11

Cite this

Costa, A., Candeias, A., Ribeiro, C., Rodrigues, H., Mesquita, J., Caldas, L., Araújo, B., Araújo, I., Vicente, H., Ribeiro, J., & Neves, J. (2020). Adaptation and anxiety assessment in undergraduate nursing students. In C. Analide, P. Novais, D. Camacho, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings (pp. 112-123). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12489 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62362-3_11

Costa, Ana ; Candeias, Analisa ; Ribeiro, Célia et al. / Adaptation and anxiety assessment in undergraduate nursing students. Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings. editor / César Analide ; Paulo Novais ; David Camacho ; Hujun Yin. Springer Science and Business Media Deutschland GmbH, 2020. pp. 112-123 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{9f52afd7afc24c9bb5af8692be5b7aa8,

title = "Adaptation and anxiety assessment in undergraduate nursing students",

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{\textquoteright} 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{\textquoteright} analysis. It intends to uncover the students{\textquoteright} 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.",

keywords = "Adaptation, Anxiety, Anxiety trait, Artificial Intelligence, Artificial neural networks, Entropy, Logic Programming",

author = "Ana Costa and Analisa Candeias and C{\'e}lia Ribeiro and Herlander Rodrigues and Jorge Mesquita and Lu{\'i}s Caldas and Beatriz Ara{\'u}jo and Isabel Ara{\'u}jo and Henrique Vicente and Jorge Ribeiro and Jos{\'e} Neves",

note = "Funding Information: Acknowledgments. This work has been supported by FCT – Funda{\c c}{\~a}o para a Ci{\^e}ncia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Funding Information: This work has been supported by FCT ? Funda??o para a Ci?ncia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 ; Conference date: 04-11-2020 Through 06-11-2020",

year = "2020",

doi = "10.1007/978-3-030-62362-3_11",

language = "English",

isbn = "9783030623616",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "112--123",

editor = "C{\'e}sar Analide and Paulo Novais and David Camacho and Hujun Yin",

booktitle = "Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings",

address = "Germany",

}

Costa, A, Candeias, A, Ribeiro, C, Rodrigues, H, Mesquita, J, Caldas, L, Araújo, B, Araújo, I, Vicente, H, Ribeiro, J & Neves, J 2020, Adaptation and anxiety assessment in undergraduate nursing students. in C Analide, P Novais, D Camacho & H Yin (eds), Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12489 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 112-123, 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, Guimaraes, Portugal, 4/11/20. https://doi.org/10.1007/978-3-030-62362-3_11

Adaptation and anxiety assessment in undergraduate nursing students. / Costa, Ana; Candeias, Analisa; Ribeiro, Célia et al.
Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings. ed. / César Analide; Paulo Novais; David Camacho; Hujun Yin. Springer Science and Business Media Deutschland GmbH, 2020. p. 112-123 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12489 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptation and anxiety assessment in undergraduate nursing students

AU - Costa, Ana

AU - Candeias, Analisa

AU - Ribeiro, Célia

AU - Rodrigues, Herlander

AU - Mesquita, Jorge

AU - Caldas, Luís

AU - Araújo, Beatriz

AU - Araújo, Isabel

AU - Vicente, Henrique

AU - Ribeiro, Jorge

AU - Neves, José

N1 - Funding Information: Acknowledgments. This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Funding Information: This work has been supported by FCT ? Funda??o para a Ci?ncia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Publisher Copyright: © 2020, Springer Nature Switzerland AG.

PY - 2020

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N2 - 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.

AB - 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.

KW - Adaptation

KW - Anxiety

KW - Anxiety trait

KW - Artificial Intelligence

KW - Artificial neural networks

KW - Entropy

KW - Logic Programming

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DO - 10.1007/978-3-030-62362-3_11

M3 - Conference contribution

AN - SCOPUS:85097395839

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings

A2 - Analide, César

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A2 - Camacho, David

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Costa A, Candeias A, Ribeiro C, Rodrigues H, Mesquita J, Caldas L et al. Adaptation and anxiety assessment in undergraduate nursing students. In Analide C, Novais P, Camacho D, Yin H, editors, Intelligent Data Engineering and Automated Learning – IDEAL 2020 - 21st International Conference, 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 112-123. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-62362-3_11

Adaptation and anxiety assessment in undergraduate nursing students

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

CIIS: Center for Interdisciplinary Research in Health

Cite this

Adaptation and anxiety assessment in undergraduate nursing students

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

CIIS: Center for Interdisciplinary Research in Health

Cite this