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Orientador(es)
Resumo(s)
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.
Descrição
Palavras-chave
Adaptation Anxiety Anxiety trait Artificial Intelligence Entropy Logic programming Ãrtificial neural networks
Contexto Educativo
Citação
Costa 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_11
Editora
Springer