The self-expectations as gender differentiating factor by University students

  1. Núñez Angulo, Beatriz 1
  2. Santamaría Conde, Rosa Mª 1
  1. 1 Universidad de Burgos
    info

    Universidad de Burgos

    Burgos, España

    ROR https://ror.org/049da5t36

Revista:
JETT

ISSN: 1989-9572

Año de publicación: 2014

Volumen: 5

Número: 3

Páginas: 17

Tipo: Artículo

Otras publicaciones en: JETT

Resumen

The object of the investigation is to establish the profile of the students who are studying in the EHEA in relation to the expectations of their evaluation, emphasizing the dimension self-concept and self-expectative, both future and current. The self-expectation shows higher positive percentages in the highest categories, questioning ourselves whether there may be differences depending on the gender.At the methodological level, the questionnaire ¨University Expectations¨ [EXPUNI] has been constructed with 40 items, including 13 items of demographic and identification purposes, 26 items adjusted to a Likert scale and the 40 item of free response for comments and suggestions. Additionally, the reliability has been tested, obtaining a Cronbrach alpha of 0.827 and for the validity a factor analysis and expert judgment has been performed. A study from the University of Burgos conducted with 592 students, 109 men [18.4 %] and 483 women [81.6 %] of 1st and 2nd year of the following grades: Education, Social Education, Master of Elementary Education and Early Childhood Education. The results of the questionnaire allowed us to estimate that there are differences according to different variables, including gender, in connection with future and current self expectation, inasmuch as each of the items in this dimension has been considered, which are linked to studying hard, having a better performance than friends, receiving congratulations from friends and family and studying depending of the teacher.By way of conclusion, it is important to continue with the measurement of the expectations in all courses, in order to corroborate data obtained so far and make inferences to the University population.

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