Bloom and Solo Taxonomies in planning teaching skills and competencies in machine learning

Authors

DOI:

https://doi.org/10.5902/2318133871873

Keywords:

Taxonomia de Bloom, Taxonomia SOLO, Planejamento de Ensino

Abstract

There is an effort to align an apparatus of theories, resources and methodologies to promote an effective teaching-learning process. However, this is not a trivial task, and may lead to misalignment between the expected, desired and results obtained. This study seeks to investigate the use of Bloom's and Solo's educational taxonomies to support the planning of offering the machine learning curricular unit in a bachelor's degree in Computer Science. The educational objectives to be achieved for this unit are structured within these taxonomies and the result is evaluated by professors of the discipline at the institution where the study is carried out. Although the taxonomies developed were positively evaluated, difficulties in their use were highlighted.

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References

BIGGS John B; COLLIS Kevin F. Evaluating the quality of learning: the solo taxonomy New York: Academic Press, 1982.

BULEGON, Ana Marli. Contribuições dos Objetos de Aprendizagem, no ensino de Física, para o desenvolvimento do Pensamento Crítico e da Aprendizagem Significativa. 2011. 156f. Tese (Doutorado de Informática na Educação) – Universidade Federal do Rio Grande do Sul, Porto Alegre, 2011.

CASTRO, Francisco Enrique Vicente; FISLER, Kathi. Designing a multi-faceted Solo taxonomy to track program design skills through an entire course. KOLI CALLING INTERNATIONAL CONFERENCE ON COMPUTING EDUCATION RESEARCH, 17, 2017. New York: Association for Computing Machinery, 2017, p. 10-19.

CHAMOLA, Vinay; HASSIJA, Vikas; GUPTA, Sakshi; GOYAL, Adit; GUIZANI, Mohsen; SIKDAR, Biplab. Disaster and Pandemic Management Using Machine Learning: A Survey. IEEE Internet of Things Journal, v. 8, n. 21, 2021, p. 16047-16071.

FACELLI, Lorena, Ana Carolina; GAMA, João; CARVALHO, André Carlos Ponce de Leon Ferreira. Inteligência artificial: uma abordagem de aprendizagem de máquina. Rio de Janeiro: LTC, 2011.

FERRAZ, Ana Paula do Carmo Marchet; BELHOTI, Renato Vair. Taxonomia de Bloom: revisão teórica e apresentação das adequações do instrumento para definição de objetivos instrucionais. Gestão & Produção, São Carlos, n. 2, v. 17, 2010, p. 421-431.

GARCIA, Léo Manoel Lopes da Silva; LARA, Daiany Francisca; ANTUNES, Franciano. Análise da retenção no ensino superior: um estudo de caso em um curso de Sistemas de Informação. Revista Faed - Unemat, Cáceres, v. 34, 2020, p. 151-38.

HATTIE, John; BROWN Gavin Thomas Lumsden. Cognitive processes in asTTle: the Solo taxonomy. asTTle Technical Report #43, University of Auckland/Ministry of Education. 2004.

HATTIE, John. Aprendizagem visível para professores: como maximizar o impacto da aprendizagem. Porto Alegre: Penso, 2017.

IMBULPITIYA, Asanthika; WHALLEY, Jacqueline; SENAPATHI, Mali. Examining the exams: bloom and database modelling and design. New York: Association for Computing Machinery, 2021, p. 21-29.

KRATHWOHL, David R.; ANDERSON, Lorin W. A taxonomy for learning, teching, and assessing: a revision of bloom's taxonomy of educational objectives. New York: Longman, 2001.

LADIAS, Anastasios; LADIAS, Demitrios; KARVOUNIDIS, Theodoros. Categorization of requests detecting in Scratch using the SOLO taxonomy. 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference, 2019, p. 1-7.

MALIK, Sohail Iqbal; COLDWELL-NEILSON, Jo. A model for teaching an introductory programming course using ADRI. Education and Information Technologies, New York, v. 22, n. 3, 2017, p. 1089-1120.

MALIK, Sohail Iqbal; TAWAFAK, Ragad M; SHAKIR, Mohanaad. Aligning and Assessing Teaching Approaches With Solo Taxonomy in a Computer Programming Course. International Journal of Information and Communication Technology Education (IJICTE) 17, n. 4, 2021, p. 1-15.

MOL, Solange Maria; MATOS, Daniel Abud Seabra. Uma análise sobre a taxonomia Solo: aplicações na avaliação educacional. Estudos em Avaliação Educacional, São Paulo, v. 30, n. 75, 2021, p. 722-747.

NIETO, Yuri; GACÍA-DÍAZ, Vicente; MONTENEGRO, Carlos; GONZÁLEZ, Claudio Camilo; CRESPO, Rubén González. Usage of Machine Learning for Strategic Decision Making at Higher Educational Institutions. IEEE Access, Manhattan/NY, v. 7, 2019, p. 75007-75017.

SANTOS, Marden Eufrasio dos; MENDONÇA, Andréa Pereira. Aplicação da robótica educacional no ensino das relações métricas do triângulo retângulo. Novas Tecnologias na Educação, Porto Alegre, v. 14, n. 2, 2016, p. 1-11.

SILVA, André Bessa. Big data, mineração de dados e aprendizagem de máquina: formas de extrair informação em grandes volumes de dados. Revista Dimensão Acadêmica, Castelo, v. 4, n. 2, 2019, p. 65-77.

SHUHIDAN, Shuhaidan; HAMILTON, Margaret; D'SOUZA, Daryl. A taxonomic study of novice programming summative assessment. In Proceedings of the Eleventh Australasian Conference on Computing Education - Volume 95 (ACE '09). Australian Computer Society, Inc., AUS, 2009, p. 147-156.

ZHANG, James; NASSER, Giacaman; WONG, Casey; e LUXTON-REILLY, Andrew. Automated classification of computing education questions using bloom’s taxonomy. New York: Association for Computing Machinery, 2021, p. 58-65.

ZORZO, Avelino F; NUNES, Daltro; MATOS, Ecivaldo; STEINMACHER, Igor; LEITE, Jair; ARAUJO, Renata; CORREIA, Ronaldo; MARTINS, Simone. Referenciais de formação para os cursos de graduação em Computação. Porto Alegre: Sociedade Brasileira de Computação, 2017.

Published

2023-01-05

How to Cite

Garcia, L. M. L. da S. ., Lara, D. F., & Gomes, R. S. (2023). Bloom and Solo Taxonomies in planning teaching skills and competencies in machine learning. Regae: Revista De Gestão E Avaliação Educacional, e71873, p. 1–22. https://doi.org/10.5902/2318133871873