A computational system to support learning self-regulation to measure knowledge acquisition by students of Computer Science-related courses
Resumo
The evaluation of knowledge acquisition is a constant challenge in the educational field, mainly for learners in higher education – in this paper, students of Computer Sciences-related courses are the main target. In this context, self-regulation and metacognition emerge as tools that might help improve this process, allowing students to monitor their learning process. The objective of this project is to evaluate the applicability of a computational system based on self-regulation for the verification of knowledge acquisition in higher education, in the area of technology. Thereby, we aim to contribute to learners’ learning process and facilitate teachers in keeping up with this evolution. In order to do this, a literary review was conducted, followed by the development of the computational system. The results of the tests conducted with educators indicated a consensus in regard to the viability of the application of the system, highlighting that the proposal contributes to a more humane evaluation and that it helps in the identification of the learners’ needs. In future works, it’s viable to take into consideration points found throughout the research, focusing on the betterment of the system with the aim of applying it effectively in educational environments.
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Zheng, L., Li, X., Zhang, X., and Sun, W. (2019). The effects of group metacognitive scaffolding on group metacognitive behaviors, group performance, and cognitive load in computer-supported collaborative learning. The Internet and Higher Education, 42:13–24.
Bloom, B., S., Hastings, J., T., and Madaus, G., F. (1983). Manual de Avaliação Formativa e Somativa do Aprendizado Escolar.
Bransford, J. D., Brown, A. L., and Cocking, R. R. (2003). How people learn: Brain, mind, experience, and school.
Clark, K. (2018). Learning theories: Cognitivism. Radiologic technology, 90:176–179.
Dewaele, J.-M. and Li, C. (2021). Teacher enthusiasm and students’ social-behavioral learning engagement: The mediating role of student enjoyment and boredom in chinese efl classes. Language Teaching Research.
Dias Canedo, E., Santos, G. A., and de Freitas, S. A. A. (2017). Analysis of the teaching-learning methodology adopted in the introduction to computer science classes. In 2017 IEEE Frontiers in Education Conference (FIE), page 1–8. IEEE Press.
Dimensions (2023). Technical report, [link]. Acessado em: 12/2023.
Dobrigkeit, F. and de Paula, D. (2019). Design thinking in practice: Understanding manifestations of design thinking in software engineering. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019, page 1059–1069, New York, NY, USA. Association for Computing Machinery.
d.school Stanford (2010). An introduction to design thinking - process guide. Technical report.
Hartikainen, S., Rintala, H., Pylväs, L., and Nokelainen, P. (2019). The concept of active learning and the measurement of learning outcomes: A review of research in engineering higher education. Education Sciences, 9(4).
Hartwig, A., Silveira, M., Fronza, L., Mattos, M., and Kohler, L. (2019). Metodologias ativas para o ensino da computação: uma revisão sistemática e um estudo prático. Anais do Workshop de Informática na Escola, 25(1):1139–1143.
Hulland, J. and Houston, M. B. (2020). Why systematic review papers and meta-analyses matter: An introduction to the special issue on generalizations in marketing. Journal of the Academy of Marketing Science, 48:351–359.
Johnson, L. F., Smith, R., Smythe, J. T., and Varon, R. (2009). Challenge-based learning: An approach for our time.
Lai, C.-L., Hwang, G.-J., and Tu, Y.-H. (2018). The effects of computer-supported self-regulation in science inquiry on learning outcomes, learning processes, and self-efficacy. Educational Technology Research and Development, 66:863–892.
Paiva, J. C., Leal, J. P., and Figueira, A. (2022). Automated assessment in computer science education: A state-of-the-art review. ACM Trans. Comput. Educ., 22(3).
Pimentel, E. (2006). Um modelo para Avaliação e Acompanhamento Contínuo do Nível de Aquisição de Conhecimentos do Aprendiz. PhD thesis, Instituto Tecnológico de Aeronáutica.
Pintrich, P. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology - J EDUC PSYCHOL, 95:667–686.
Prather, J., Pettit, R., Becker, B. A., Denny, P., Loksa, D., Peters, A., Albrecht, Z., and Masci, K. (2019). First things first: Providing metacognitive scaffolding for interpreting problem prompts. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, SIGCSE ’19, page 531–537, New York, NY, USA. As- sociation for Computing Machinery.
Preece, J., Rogers, Y., and Sharp, H. (2023). Interaction Design: Beyond Human-Computer Interaction. John Wiley & Sons, Inc., EUA.
Pressman, R. S. and Maxim, B. R. (2021). Engenharia de Software: Uma Abordagem Profissional. AMGH, 9ed edition.
Ramos, V. A. B. (2019). A motivação e o sucesso escolar. Technical report. Psicologia.pt - O Portal dos Psicólogos.
Saadati, Z., Zeki, C. P., and Barenji, R. V. (2021). On the development of blockchain-based learning management system as a metacognitive tool to support self-regulation learning in online higher education. Interactive Learning Environments, 0(0):1–24.
Sahli, A., Pei, E., Manohar, A., and Evans, R. (2022). Knowledge visualization: A design centered framework. Procedia CIRP, 109:629–634. 32nd CIRP Design Conference (CIRP Design 2022) - Design in a changing world.
Santos, K. S. d. P. (2021). Processo de avaliação de interfaces para dispositivos móveis: uma proposta. Master’s thesis, Universidade Presbiteriana Mackenzie.
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104:333–339.
Ulbricht, K. (1982). Summative evaluation of a course of study in computer science. Higher Education, 11.
Veiga, A. V. L. d. (2017). A participação dos alunos na regulação dos processos de aprendizagem. Master’s thesis, Instituto Politécnico de Lisboa. Acessado em: 10/10/2022.
Wang, L., Ang, L. H., and Abdul Halim, H. (2020). A systematic literature review of narrative analysis in recent translation studies. 28:1–16.
Zheng, L., Li, X., Zhang, X., and Sun, W. (2019). The effects of group metacognitive scaffolding on group metacognitive behaviors, group performance, and cognitive load in computer-supported collaborative learning. The Internet and Higher Education, 42:13–24.
Publicado
04/11/2024
Como Citar
LEITE, Paula Torales; SILVEIRA, Ismar Frango.
A computational system to support learning self-regulation to measure knowledge acquisition by students of Computer Science-related courses. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 35. , 2024, Rio de Janeiro/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 101-114.
DOI: https://doi.org/10.5753/sbie.2024.242147.
