Design de Sistema de Recomendação Educacional: abordagens com Mágico de Oz
Resumo
A educação é um domínio plural, e as tecnologias a serem inseridas neste contexto, devem considerar, principalmente, as percepções de estudantes e professores. Neste caso, Sistemas de Recomendação podem passar por processos de design antes de direcionar esforços para utilizar Aprendizado de Máquina. Para isso, esse estudo teve como objetivo verificar o impacto na frequência de interações ao incorporar recomendações em um contexto educacional de Rede Social Educativa. Através de técnicas de Mágicos de Oz (WoZ), durante períodos do ano letivo de 2022, foi possível verificar que o processo de design resultou na antecipação de situações que inserem estudantes da Educação Básica no espaço de interações mais significativamente incentivadas por abordagens de recomendação.
Palavras-chave:
Sistemas de Recomendação, Rede Social Educativa, Mágicos de Oz, Interações, Educação Básica
Referências
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Andrade, T., Almeida, C., Barbosa, J., & Rigo, S. (2021). Metodologias Ativas integradas a um Sistema de Recomendação e Mineração de Dados Educacionais para a mitigação de evasão em EaD. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 824-835). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218385
Champiri, Z. D., Mujtaba, G., Salim, S. S., & Chong, C. Y. (2019, January). User experience and recommender systems. In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-5). IEEE. https://doi.org/10.1109/ICOMET.2019.8673410
Chaiyo, Y., & Nokham, R. (2017, March). The effect of Kahoot, Quizizz and Google Forms on the student's perception in the classrooms response system. In 2017 International Conference on Digital Arts, Media and Technology (ICDAMT) (pp. 178-182). IEEE. https://doi.org/10.1109/ICDAMT.2017.7904957
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two Decades of Artificial Intelligence in Education: Contributors, Collaborations, Research Topics, Challenges, and Future Directions. Educational Technology & Society, 25(1), 28–47. https://www.jstor.org/stable/48647028
Browne, J. T. (2019, May). Wizard of oz prototyping for machine learning experiences. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-6). https://doi.org/10.1145/3290607.3312877
Escolà-Gascón, Á., & Gallifa, J. (2022). How to measure soft skills in the educational context: psychometric properties of the SKILLS-in-ONE questionnaire. Studies in Educational Evaluation, 74, 101155. https://doi.org/10.1016/j.stueduc.2022.101155
Ferreira, H. N. M., Brant-Ribeiro, T., Araújo, R. D., Dorça, F. A., & Cattelan, R. G. (2016). An automatic and dynamic student modeling approach for adaptive and intelligent educational systems using ontologies and bayesian networks. In 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 738-745). IEEE. https://doi.org/10.1109/ICTAI.2016.0116
Jansen, A., & Colombo, S. (2022, April). Wizard of Errors: Introducing and Evaluating Machine Learning Errors in Wizard of Oz Studies. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (pp. 1-7). https://doi.org/10.1145/3491101.3519684
Jokhan, A., Chand, A. A., Singh, V., & Mamun, K. A. (2022). Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance. Sustainability, 14(4), 2377. https://doi.org/10.3390/su14042377
Hernandez-Bocanegra, D. C., & Ziegler, J. (2021, July). Conversational review-based explanations for recommender systems: Exploring users’ query behavior. In CUI 2021-3rd Conference on Conversational User Interfaces (pp. 1-11). https://doi.org/10.1145/3469595.3469596
Howard, S. K., Swist, T., Gasevic, D., Bartimote, K., Knight, S., Gulson, K., ... & Selwyn, N. (2022). Educational data journeys: Where are we going, what are we taking and making for AI?. Computers and Education: Artificial Intelligence, 3, 100073. https://doi.org/10.1016/j.caeai.2022.100073
Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American statistical Association, 47(260), 583-621. https://doi.org/10.1080/01621459.1952.10483441
Ladosha, O. M. (2022). Dynamics of Student Performance in a Foreign Language from the Perspective of the Transition to Distance Learning (statistical analysis). In 2022 VI International Conference on Information Technologies in Engineering Education (Inforino) (pp. 1-5). IEEE. https://doi.org/10.1109/Inforino53888.2022.9782984
Pereira, A., Gomes, A., Primo, T., Silva, R., Rodrigues, R., Campos Filho, A., Lima, R., & Melo Júnior, R. (2021). Identificação e caracterização de níveis de interação no ensino remoto de emergência na Educação Básica. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 145-156). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218498
Rahayu, N. W., Ferdiana, R., & Kusumawardani, S. S. (2022). A systematic review of ontology use in E-Learning recommender system. Computers and Education: Artificial Intelligence, 100047. https://doi.org/10.1016/j.caeai.2022.100047
Silva, F. L., da Silva, K. K. A., Slodkowski, B. K., & Cazella, S. C. (2022). A Aplicação de Sistemas de Recomendação no Contexto Educacional: uma Revisão Sistemática da Literatura. Revista Iberoamericana de Tecnología en Educación y Educación en Tecnología, (32), e1-e1. https://doi.org/10.24215/18509959.32.e1
Silva, V., Ferreira, H., Torres, A., & Rodrigues, F. (2021). Math Suggestion: Uma Ferramenta de Recomendação de Objetos de Aprendizagem Fundamentada nos Princípios das Avaliações de Autoeficácia e Análise de Desempenho. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 237-248). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218677
Viswanathan, S., Guillot, F., Chang, M., Grasso, A. M., & Renders, J. M. (2022, June). Addressing Hiccups in Conversations with Recommender Systems. In Designing Interactive Systems Conference (pp. 1243-1259). https://doi.org/10.1145/3532106.3533491
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2022). Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI. International Journal of Human–Computer Interaction, 1-25. https://doi.org/10.1080/10447318.2022.2041900
Amaral, G., Ramos, D., Ramos, I., & Oliveira, E. (2021). Um Sistema de Recomendação de Estratégias de Aprendizagem Baseado no Perfil de Motivação do Aluno: SisREA. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 718-727). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218743
Andrade, T., Almeida, C., Barbosa, J., & Rigo, S. (2021). Metodologias Ativas integradas a um Sistema de Recomendação e Mineração de Dados Educacionais para a mitigação de evasão em EaD. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 824-835). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218385
Champiri, Z. D., Mujtaba, G., Salim, S. S., & Chong, C. Y. (2019, January). User experience and recommender systems. In 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-5). IEEE. https://doi.org/10.1109/ICOMET.2019.8673410
Chaiyo, Y., & Nokham, R. (2017, March). The effect of Kahoot, Quizizz and Google Forms on the student's perception in the classrooms response system. In 2017 International Conference on Digital Arts, Media and Technology (ICDAMT) (pp. 178-182). IEEE. https://doi.org/10.1109/ICDAMT.2017.7904957
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two Decades of Artificial Intelligence in Education: Contributors, Collaborations, Research Topics, Challenges, and Future Directions. Educational Technology & Society, 25(1), 28–47. https://www.jstor.org/stable/48647028
Browne, J. T. (2019, May). Wizard of oz prototyping for machine learning experiences. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-6). https://doi.org/10.1145/3290607.3312877
Escolà-Gascón, Á., & Gallifa, J. (2022). How to measure soft skills in the educational context: psychometric properties of the SKILLS-in-ONE questionnaire. Studies in Educational Evaluation, 74, 101155. https://doi.org/10.1016/j.stueduc.2022.101155
Ferreira, H. N. M., Brant-Ribeiro, T., Araújo, R. D., Dorça, F. A., & Cattelan, R. G. (2016). An automatic and dynamic student modeling approach for adaptive and intelligent educational systems using ontologies and bayesian networks. In 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 738-745). IEEE. https://doi.org/10.1109/ICTAI.2016.0116
Jansen, A., & Colombo, S. (2022, April). Wizard of Errors: Introducing and Evaluating Machine Learning Errors in Wizard of Oz Studies. In CHI Conference on Human Factors in Computing Systems Extended Abstracts (pp. 1-7). https://doi.org/10.1145/3491101.3519684
Jokhan, A., Chand, A. A., Singh, V., & Mamun, K. A. (2022). Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance. Sustainability, 14(4), 2377. https://doi.org/10.3390/su14042377
Hernandez-Bocanegra, D. C., & Ziegler, J. (2021, July). Conversational review-based explanations for recommender systems: Exploring users’ query behavior. In CUI 2021-3rd Conference on Conversational User Interfaces (pp. 1-11). https://doi.org/10.1145/3469595.3469596
Howard, S. K., Swist, T., Gasevic, D., Bartimote, K., Knight, S., Gulson, K., ... & Selwyn, N. (2022). Educational data journeys: Where are we going, what are we taking and making for AI?. Computers and Education: Artificial Intelligence, 3, 100073. https://doi.org/10.1016/j.caeai.2022.100073
Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American statistical Association, 47(260), 583-621. https://doi.org/10.1080/01621459.1952.10483441
Ladosha, O. M. (2022). Dynamics of Student Performance in a Foreign Language from the Perspective of the Transition to Distance Learning (statistical analysis). In 2022 VI International Conference on Information Technologies in Engineering Education (Inforino) (pp. 1-5). IEEE. https://doi.org/10.1109/Inforino53888.2022.9782984
Pereira, A., Gomes, A., Primo, T., Silva, R., Rodrigues, R., Campos Filho, A., Lima, R., & Melo Júnior, R. (2021). Identificação e caracterização de níveis de interação no ensino remoto de emergência na Educação Básica. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 145-156). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218498
Rahayu, N. W., Ferdiana, R., & Kusumawardani, S. S. (2022). A systematic review of ontology use in E-Learning recommender system. Computers and Education: Artificial Intelligence, 100047. https://doi.org/10.1016/j.caeai.2022.100047
Silva, F. L., da Silva, K. K. A., Slodkowski, B. K., & Cazella, S. C. (2022). A Aplicação de Sistemas de Recomendação no Contexto Educacional: uma Revisão Sistemática da Literatura. Revista Iberoamericana de Tecnología en Educación y Educación en Tecnología, (32), e1-e1. https://doi.org/10.24215/18509959.32.e1
Silva, V., Ferreira, H., Torres, A., & Rodrigues, F. (2021). Math Suggestion: Uma Ferramenta de Recomendação de Objetos de Aprendizagem Fundamentada nos Princípios das Avaliações de Autoeficácia e Análise de Desempenho. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, (pp. 237-248). Porto Alegre: SBC. https://doi.org/10.5753/sbie.2021.218677
Viswanathan, S., Guillot, F., Chang, M., Grasso, A. M., & Renders, J. M. (2022, June). Addressing Hiccups in Conversations with Recommender Systems. In Designing Interactive Systems Conference (pp. 1243-1259). https://doi.org/10.1145/3532106.3533491
Xu, W., Dainoff, M. J., Ge, L., & Gao, Z. (2022). Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI. International Journal of Human–Computer Interaction, 1-25. https://doi.org/10.1080/10447318.2022.2041900
Publicado
16/11/2022
Como Citar
PEREIRA, Aluisio José; GOMES, Alex Sandro; PRIMO, Tiago Thompsen.
Design de Sistema de Recomendação Educacional: abordagens com Mágico de Oz. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 1184-1195.
DOI: https://doi.org/10.5753/sbie.2022.225760.
