Lab Classes in Chemistry Learning - An Artificial Intelligence View

• Autor(es): Figueiredo, Margarida ; Esteves, M. Lurdes ; Neves, José ; Vicente, Henrique
• Data: 2014
• Identificador Persistente: http://hdl.handle.net/10174/11351
• Origem: Repositório Científico da Universidade de Évora
• Assunto(s): Artificial Intelligence; Chemistry Learning; Decision Trees; k-Means; Lab Classes; Lab Work
• Tipo de Documento: Parte ou capítulo de livro
• Idioma: Inglês
• Editor(es): 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

Descrição

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.