Development and Results of an Instrument to Search for Competences and Abilities in Information Technology
- 1 Digital Metropole Institute, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 2 Psychology Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 3 Psychology Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 4 Psychology Department, Federal University of Pernambuco (UFPE), Recife, Brazil
- 5 Psychology Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 6 Psychology Department, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 7 Statistics and Mathematics Department, Rural Federal University of Pernambuco (UFRPE), Recife, Brazil
- 8 Digital Metropole Institute, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 9 Digital Metropole Institute, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- 10 Digital Metropole Institute, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
Abstract
This article presents an analysis of the selection process of students from both private and public high schools in the state of Rio Grande do Norte (Northeast of Brazil), in order to form the first group of the Information Technology technical course of the Metrópole Digital project at the Federal University of Rio Grande do Norte (UFRN). The selection instrument consists of a written exam built on the basis of a set of matrices that depict relevant competences and abilities expected from the students. Data concerning the profile of distribution of performance per exam question are presented, together with empirical evidences of the effectiveness of the proposed competence matrices in the selection process. The correlation very fied among the matrices compounding the instrument and scores in courses, and the instrument as a wholeand scores in courses is moderate to strong (r S = 0.6 and r S = 0.7; p < 0,05). The association between the criterion variables (Average of Performance in the Basic Moduleof courses) and the explicative variables (Total score in the selection instrument (QTot) and each of the five compounding matrices) is moderate (r S =0.51, p = 0.001), and the matrices and QTot are jointly responsible for 25% of the variance of the performance in the basic module. The regression coefficient for matrix 1 is 1.38 (CI of 95% = 1.07-1.68); for matrix 2 it was 0.65 (CI of 95% = 036-0.95); for matrix 3, 1.2 (CI of 95% = 0.92 - 1,55); matrix 4 0,76 (CI of 95% = 0.45-1.06); matrix 5 1.08 (CI of 95% = 0.78-1.39). The effects of student-descriptive independent variables on performance in the exam are also presented and discussed, and predictive relationships between performance in the exam and performance in the disciplines of the course are verified. Data collected allow concluding that the instrument of selection proposed fits well the aim of forming a group of students to undertake a technical course in the area of information technology.
- Borba, M. C., & Villareal, M. E. (2005). Humans-with-Media and the Reorganization of Mathematical Thinking. Springer, USA.
- Comperve, & do Vestibular, C. P. (2010). Perfil sócio-econômico dos candidatos ao concurso Metrópole Digital segundo reprovação/aprovação. COMPERVE-UFRN, Natal (RN).
- Da Rocha Falcão, J. T. (2009). Na vida dez, na escola dez: Breve discussão crítica acerca de pressupostos psicológicos e seus desdobramentos sobre a avaliação em matemática escolar. Vértices, 10, 117-139.
- Hazin, I. (2011). Projeto Metrópole Digital—UFRN: Elementos básicos de caracterização de uma proposta de seleção de candidatos e oferta de capacitação básica pioneira em TI para estudantes do ensino médio norte-riograndense. Procedings from:Seminário de avaliação do Curso Técnico do Instituto Metrópole Digital. Natal, 21 September 2011.
- ISTE (2007). Profiles for Students in TI. http://www.iste.org/standards/nets-for-students/nets-student-standards-2007
- Kaptelinin, V., & Nardi, B. (2012). Affordances in HCI: Toward a Mediated Action Perspective. In Proceedings of the Conference on Human Factors in Computing Systems—CHI’12 (967-976). Austin, TA: ACM Press.
- Keay-Bright, W. E. (2008). Tangible Technologies as Interactive Play Spaces for Children with Learning Difficulties: The Reactive Colours Project. The International Journal of Technology, Knowledge and Society, 4, 111-120.
- Mooi, E., & Sarstedt, M. (2011). Chapter 9: Cluster Analysis. In E. Mooi, & M. Sarstedt (Eds.), A Concise Guide to Market Research (pp. 273-324). Berlin: Springer-Verlag.
- Papert, S. (1980). Mindstorms: Children, Computers and Powerful Ideas. New York: Basic Books.
- Passey, D., Rogers, C. G., Machell, J., & McHugh, G. (2004). The Motivational Effect of ICT on Pupils (RR523). London: Department for Educationand Skills—DfES.
- Perrenoud, P. (2000). Dez Novas Competências para Ensinar. Porto Alegre: Artmed Editora.
- Primi, R., Dos Santos, A., Vendramini, C., Taxa, F., Muller, F., Lukjanenko, M., & Sampaio, I. (2001). Competências e Habilidades Cognitivas: Diferentes Definições dos Mesmos Construtos. Psicologia: Teoria e Pesquisa, 17, 151-159. http://dx.doi.org/10.1590/s0102-37722001000200007
- Primi, R. (2003). Inteligência: Avanços nos modelos teóricos e nos instrumentos de medida. Avaliação Psicológica, 1, 67-77.