5 resultados para low SES students

em Universidad de Alicante


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We examined the psychometric properties of the School Attitude Assessment Survey–Revised in a Spanish population (n = 1,398). Confirmatory factor analysis procedures supported the instrument’s five-factor structure. The results of discriminant analysis demonstrated the predictive power of the School Attitude Assessment Survey–Revised scales as regards academic performance. Implications for education and assessment are discussed.

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This paper analyzes the learning experiences and opinions from a group of undergraduate students in a course about Robotics. The contents of this course were taught as a set of seminars. In each seminar, the student learned interdisciplinary knowledge of computer science, control engineering, electronics and other fields related to Robotics. The aim of this course is that the students are able to design and implement their own and custom robotic solution for a series of tests planned by the teachers. These tests measure the behavior and mechatronic features of the students' robots. Finally, the students' robots are confronted with some competitions. In this paper, the low-cost robotic architecture used by the students, the contents of the course, the tests to compare the solutions of students and the opinion of them are amply discussed.

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The objective of this study is to identify possible combinations of multiple goals that lead to different goal orientation profiles and to determine whether there are significant group differences in self-concept dimensions. The Achievement Goals Tendencies Questionnaire (AGTQ) and the Self-Description Questionnaire-II (SDQ-II) were administered to a sample of 2,022 students of Compulsory Secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four profiles of motivational goals: a group of students with a generalized high motivation profile, a group of students with generalized low motivation profile, a group of students with a predominance of learning goals and achievement goals, and a last group of students with a predominance of achievement goals and social reinforcement goals. Results reveal statistically significant differences among the profiles obtained regarding self-concept dimensions.

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Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational profiles and to determine whether there are significant differences between the groups obtained regarding causal attributions of success and failure (ability, effort, or external causes) in Mathematics and Language and Literature, and in overall academic performance. The Goal Achievement Tendencies Questionnaire (AGTQ) and the Sydney Attribution Scale (SAS) were administered to a sample of 2022 students of compulsory secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four motivational profiles: a group of students with a high generalized motivation profile, a group of students with low generalized motivation profile, a group of students with predominance of learning goals and achievement goals, and a final group of students with predominance of social reinforcement goals. Results revealed statistically significant differences between the profiles obtained in academic self-attributions.

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In the last few years, one of the lines of research of great interest in the field of emotional intelligence (EI) has been the analysis of the role of emotions in the educational context and, in particular, their influence on learning strategies. The aims of this study are to identify the existence of different EI profiles and to determine possible statistically significant differences in learning strategies between the obtained profiles. The study involved 1253 Chilean school students from 14 to 18 years (M = 15.10, SD = 1.30), who completed the Trait Meta-Mood Scale-24 (TMMS-24) and the Inventory of Learning and Study Strategies—High School version (LASSI-HS). Cluster analysis identified four EI profiles: a group of adolescents with a high EI profile, a group with predominance of low emotional attention and high repair skills, a group with high scores on attention and low scores on clarity and repair, and a final group of adolescents with low EI. Also, students in groups with high overall scores in EI and low attention and high repair emotional obtained higher scores on the different learning strategies; however, the effect size analysis showed that these differences had no empirical relevance.