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Title: Lab Classes in Chemistry Learning - An Artificial Intelligence View
Authors: Figueiredo, Margarida
Esteves, M. Lurdes
Neves, José
Vicente, Henrique
Editors: de la Puerta, José Gaviria
Ferreira, Iván García
Bringas, Pablo Garcia
Klett, Fanny
Abraham, Ajith
de Carvalho, André C.P.L.F.
Herrero, Álvaro
Baruque, Bruno
Quintián, Héctor
Corchado, Emilio
Keywords: Artificial Intelligence
Chemistry Learning
Decision Trees
Lab Classes
Lab Work
Issue Date: 30-Jun-2014
Publisher: Springer International Publishing
Citation: Figueiredo, M., Esteves, M.L., Neves, J. & Vicente, H., Lab Classes in Chemistry Learning – An Artificial Intelligence View. In J.G. Puerta, I.G. Ferreira, P.G. Bringas, F. Klett, A. Abraham, A.C. Carvalho, Á. Herrero, B. Baruque, H. Quintián & E. Corchado Eds., International Joint Conference SOCO’14 – CISIS’14 – ICEUTE’14, Advances in Intelligent Systems and Computing, Vol. 299, pp. 565–575, Springer International Publishing, Cham, Switzerland, 2014.
Abstract: The teaching methodology used in lab classes in Chemistry Learning was studied for a cohort of 702 students in the 10th grade of Portuguese Secondary Schools. The k-Means Clustering Method, with k values ranging between 2 (two) and 4 (four), was used in order to segment the data. Decision Trees were used for the development of explanatory models of the segmentation. The results obtained showed that the majority of the answerers considered that experimentation is central on Chemistry learning. The results also showed that the significance of research in Chemistry learning is strongly dependent on the students’ involvement in lab work.
ISBN: 978-3-319-07994-3
ISSN: 2194-5357
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros
CQE - Publicações - Capítulos de Livros

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