Reducción de la dimensionalidad para el análisis e interpretación afectiva en la práctica educativa

  1. Diego Airado Rodríguez
  2. María Antonia Dávila Acedo
  3. Ana Belén Borrachero Cortés
Aldizkaria:
International Journal of Developmental and Educational Psychology: INFAD. Revista de Psicología

ISSN: 0214-9877

Argitalpen urtea: 2017

Zenbakien izenburua: La psicología hoy: retos, logros y perspectivas de futuro. Atención a la diversidad

Alea: 4

Zenbakia: 1

Orrialdeak: 97-102

Mota: Artikulua

DOI: 10.17060/IJODAEP.2017.N1.V4.1031 DIALNET GOOGLE SCHOLAR lock_openSarbide irekia editor

Beste argitalpen batzuk: International Journal of Developmental and Educational Psychology: INFAD. Revista de Psicología

Garapen Iraunkorreko Helburuak

Laburpena

In the personal development of the students both cognitive and affective factors have important influence. Therefore, it is very important to take into account the emotions of the students in the sciences teaching-learning process. This fact becomes even more relevant when the considered students are teachers in formation, since the emotions they feel toward science will crucially influence their educational practice with their future students. This communication is centered in the usefulness of principal component analysis (PCA) for dimensionality reduction to aid the analysis of emotions. It has been employed as case of study a survey on emotions of university students when addressing a physics problem from a theoretical (“on the paper”) and from a practical point of view (in the physics lab). The selected physics problem deals with the decomposition of forces in an inclined plane and the determination of the friction coefficient. The considered sample consisted on 118 students attending to the lab session and 75 students attending to the theoretical class session of problem solving. Emotions have been measured with the aid of a questionnaire including both, positive and negative emotions. Data analysis has been successfully performed by means of principal component analysis (PCA) and results demonstrate that students show more confidence and less insecurity when addressing the problem in the laboratory and from a more practical point of view.

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