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Pérez González, Juan Carlos

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0000-0003-4025-7516
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Pérez González
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Juan Carlos
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Autor: Robles, Gregorio ×

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Mostrando 1 - 2 de 2
  • Miniatura
    Publicación
    Extending the nomological network of computational thinking with non-cognitive factors
    (Elsevier, 2018-03) Román González, Marcos; Pérez González, Juan Carlos; Moreno León, Jesús; Robles, Gregorio
    Computational thinking (CT) is being consolidated as a key set of problem-solving skills that must be developed by the students to excel in our software-driven society. However, in psychological terms, CT is still a poorly defined construct, given that its nomological network has not been established yet. In a previous paper, we started to address this issue studying the correlations between CT and some fundamental cognitive variables, such as primary mental abilities and problem-solving ability. The current work deepens in the same direction as it aims to extend the nomological network of CT with non-cognitive factors, through the study of the correlations between CT, self-efficacy and the several dimensions from the ‘Big Five’ model of human personality: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. To do so, the Computational Thinking Test (CTt) and some additional self-efficacy items are administered on a sample of 1251 Spanish students from 5th to 10th grade (N ¼ 1251), and the Big Five Questionnaire-Children version (BFQ-C) is also taken by a subsample from the above (n ¼ 99). Results show statistically significant correlations between CT and self-efficacy perception relative to CT performance (rs ¼ 0.41), in which gender differences in favor of males are found (d ¼ 0.42). Moreover, results show statistically significant correlations between CT and: Openness to Experience (r ¼ 0.41), Extraversion (r ¼ 0.30), and Conscientiousness (r ¼ 0.27). These findings are consistent with the existing literature except for the unexpected correlation between CT and the Extraversion factor of personality, which is consequently discussed in detail. Overall, our findings corroborate the existence of a non-cognitive side of CT that should be taken into account by educational policies and interventions aimed at fostering CT. As a final contribution, the extended nomological network of CT integrating cognitive and non-cognitive variables is depicted.
  • Miniatura
    Publicación
    Can computational talent be detected? Predictive validity of the Computational Thinking Test
    (Elsevier, 2018-11) Román González, Marcos; Pérez González, Juan Carlos; Moreno-León, Jesús; Robles, Gregorio
    Computational thinking (CT) is arising as a set of problem-solving skills that must be acquired by the new generations of students to fully understand and participate in our computer-based world. However, from a psychometric approach, we are still at an early stage regarding the definition and assessment of CT as a psychological variable. One way to advance in this area is to investigate whether ‘computationally talented’ students (i.e., ‘computational top thinkers’) can be detected even before learning to code; and, if so, how to teach them properly to fully develop their high-computational ability. This paper presents several empirical concatenated studies about the predictive validity of the Computational Thinking Test (CTt), which is administered on a sample of 314 middle school Spanish students (n = 314). We report the predictive validity of the CTt, conducted at the beginning of the quarter, with respect to academic performance (Informatics, Mathematics, and Language) and learning analytics in a Code.org course collected at the end of the quarter. We also analyze the predictive validity of the CTt to early distinguish between ‘computational regular thinkers’ and ‘computational top thinkers’ (i.e., those who spontaneously accelerated from the ‘block-based’ programming environment of Code.org to the ‘text-based’ one of Khan Academy). Finally, we perform a case study over two of the students categorized as ‘computational top thinkers’, in which one of their coding products written in Processing JavaScript is described. Our results demonstrate that ‘computationally talented’ students can be detected in middle school, and that these subjects have the ability to accelerate in the Computer Science Education standards between 1 and 2 years compared to the regular learners. This could have major implications on the emerging computing curricula, which should take into account these individual differences in computational ability and ‘learning-how-to-code’ speed to ensure an appropriate progression for every student.