Computational thinking and cognitive processes with elderly people: systematic review

Authors

DOI:

https://doi.org/10.33448/rsd-v10i11.20020

Keywords:

Thinking; Cognitive aging; Problem solving; Aged.

Abstract

Computational thinking involves cognitive processes that seek to understand which problem can be solved and to develop possible solutions efficiently and creatively. Elderly people may have cognitive impairment due to age-related factors. Computational thinking is a suitable proposal to be applied at this stage of life. In this study, a systematic literature review is presented, whose objective was to identify the areas of knowledge in which computational thinking, with a focus on cognitive processes, is being applied to the elderly. The search was carried out in May 2021, in electronic databases provided by CAPES (CAFe access): Scopus, Web of Science, Scielo, Sbie, Eric, IEEE Xplore, Ovid, Science Direct, SpringerLink, SAGE Journals and Wiley Online Library. The literature search resulted in a total of 165 studies, and after the exclusion criteria, 6 studies remained for the qualitative synthesis. The research method used was PRISMA - Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The results point to the presence of computational thinking in different areas. Its use had very positive aspects when it has its focus on elderly people. The main finding of the analyzed studies indicates that the use of computational thinking by elderly people has a relevant role for cognitive stimulation.

Author Biographies

Emerson Rogério de Oliveira Junior, Instituto Federal do Rio Grande do Sul

Graduate in Computer Science from the Pontifical Catholic University of Rio Grande do Sul - PUCRS (1988), Postgraduate in Telematics and Information Systems from the Federal University of Rio Grande do Sul - UFRGS (1990), Postgraduate in Informatics from COPPE Sistemas - UFRJ (1995 ) and Master's Degree in Computer Science from the Federal University of Rio Grande do Sul - UFRGS (1999). He has been studying for a Doctorate in Human Aging, at the University of Passo Fundo (UPF), in the field of Gerontechnology, since 2020. He is currently a professor at the Federal Institute of Education, Science and Technology of Rio Grande do Sul. Has experience in Computer Science, with an emphasis on basic software, acting on the following topics: operating systems, information technology in education, fault tolerance softwares, distributed objects, group communication systems, Java and Python programming languages.

 

Adriano Pasqualotti, Universidade de Passo Fundo

Doutorado em Informática na Educação, e mestrado em Computação (UFRGS), graduação em Matemática (UPF), realizou estágio de Pós-Doutorado em Sociedade, Comunicação e Cultura (Universidade de Lisboa – Portugal). Professor do Programa de Pós-Graduação em Envelhecimento Humano e pesquisador associado do Centro de Administração de Políticas Públicas, do Instituto de Ciências Sociais e Políticas da Universidade de Lisboa. Pesquisa nas áreas de gerontologia, ciência da computação e estatística, com ênfase em envelhecimento humano, educação de adultos, ambientes de interação e sentido no ciberespaço e sociedade, tecnologias de informação e comunicação e gameterapia, bem como em planejamento e avaliação educacional. É avaliador de instituição de educação superior do Sistema Nacional de Avaliação da Educação Superior, cadastrado do Banco de Avaliadores do Sinaes do Ministério da Educação

References

Angeli, C., & Giannakos M. N. (2020). Computational thinking education: Issues and challenges. Computers in Human Behavior, 105:106185 https://doi.org/10.1016/j.chb.2019.106185.

Azevedo, G. T. & Maltempi, M. (2020). Processo de Aprendizagem de Matemática à luz das Metodologias Ativas e do Pensamento Computacional. Ciência e Educação, 26: e20061.

Bireme. DeCS/MeSH. (2017). Descritores em Ciências da Saúde. https://decs.bvsalud.org/.

Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking - a guide for teachers.

IBGE – Instituto Brasileiro de Geografia e Estatística. (2018). Projeção da População 2018: número de habitantes do país deve parar de crescer em 2047. https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/21837-projecao-da-populacao-2018-numero-de-habitantes-do-pais-deve-parar-de-crescer-em-2047.

Isbell, C. L., Stein, L. A., Cutler, R., Forbes, J., Fraser, L., Impagliazzo, J., Proulx, V., Russ, S., Thomas, R. & Xu, Y. (2009). (re)defining computing curricula by (re)defining computing. ACM SIGCSE Bulletin, 41(4), 195–207.

Kale, U., Akcaoglu, M., Cullen, T. & Goh, D. (2018). Contextual Factors Influencing Access to Teaching Computational Thinking. Computers in the Schools, 35(2), 69-87.

Kitchenham, B. & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. Information and Software Technology, 51(1), 7-15.

Lee, C. & Wong, K. D. (2017). Developing community-based engagement in Smart Cities: A design-computational thinking approach. Proc. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 832-836.

Lee, E. & Park, S. (2020). Immersive Experience Model of the Elderly Welfare Centers Supporting Successful Aging. Frontiers in Psychology, 11: 8.

Lucena, D. A., Nunes, I. D., Rodrigues, R. S. & Souza, D. R. O. (2020). Adaptações em atividades de Pensamento Computacional para estimulação cognitiva em idosos. Anais XXXI Simpósio Brasileiro de Informática na Educação (SBIE 2020), 1533-1542.

Lupşe, O., Chirila, C. & Ciocârlie, H. (2011). Programming Concepts in the Silver Code Guide for Elders. Proc. IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI), 137-142.

Miranda, G. M. D., Mendes, A. C. G. & Silva, A. L. A. (2016). O envelhecimento populacional brasileiro: desafios e consequências sociais atuais e futuras. Revista Brasileira de Geriatria e Gerontologia, 19(3), 507-519.

Moher, D., Liberati, A., Tetzlaff, J. & Altmann, D. G. (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Medicine, 6(7): e1000097.

Piau, A., Campo, E., Rumeau, P. & Vellas, B. (2014). Aging society and gerontechnology: a solution for an independent living?. The Journal of Nutrition, Health & Aging, 18(1), 97-112.

Rouillard, M., Audiffren, M., Albinet, C., Bahri, M. A., Garraux, G. & Collette, F. (2017). Contribution of four lifelong factors of cognitive reserve on late cognition in normal aging and Parkinson's disease. Journal of Clinical and Experimental Neuropsychology. 39(2), 142-162.

Shute, V. J.; Sun, C. & Asbell-Clarke, J. (2017). Demystifying Computational Thinking. Educational Research Review, 22, 142-158.

Yang, H., Martin, P., Satterfield, D., Babbitt, R., Wong, J., Shelley, M. & Chang, C. (2011). A Novel Interdisciplinary Course in Gerontechnology for Disseminating Computational Thinking. Proc. 41th ASEE/IEEE Frontiers in Education Conference Political Science Presentations and Posters.

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.

World Health Organization. (‎2015)‎. World report on ageing and health. World Health Organization. https://apps.who.int/iris/handle/10665/186463.

Published

11/09/2021

How to Cite

OLIVEIRA JUNIOR, E. R. de; PASQUALOTTI, A. Computational thinking and cognitive processes with elderly people: systematic review. Research, Society and Development, [S. l.], v. 10, n. 11, p. e563101120020, 2021. DOI: 10.33448/rsd-v10i11.20020. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/20020. Acesso em: 24 jun. 2024.

Issue

Section

Education Sciences