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What to do and what to avoid on the use of gamified intelligent tutor system for low-income students

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Abstract

Educational indicators have revealed that a significant portion of Brazilian Basic Education students have a less than satisfactory skill level in reading and solving Mathematics problems. Despite several proven benefits, adaptive learning technologies are scarcely used with low-income students in public schools’ due unavailable resources and lack of technological infrastructure. Nonetheless, there is a great expectation that the access to new technologies will assist and improve teaching practices and contribute to enhance learning performance. This study aimed to identify good and bad pedagogical practices from teaching and learning processes using a gamified Intelligent Tutor System (ITS) in Elementary Education. In order to achieve this goal, a case study was conducted with a qualitative research approach based on observations made in classrooms in a 9 months period and the application of Framework Analysis as a data analysis technique involving 6 teachers and 112 students aged between 9 and 21 years old from public schools in Brazil. Results presented provide evidence of significant improvement in the domain of Portuguese Language and Mathematical skills. The highlights of the paper are the seven good practices and six bad pedagogical practices with the use of gamified ITS. Additionally, while gamified ITS are important to improve learning and promote more engagement, this study also sheds light on the importance of using gamified ITS aligned with the school curriculum and a clear intervention proposal instead of voluntary use.

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Authors and Affiliations

  1. Federal University of Alagoas, Maceió, Alagoas, Brazil

    Sivaldo Joaquim, Ig Ibert Bittencourt, Rafael de Amorim Silva & Marcelo Reis

  2. Federal University of Pernambuco, Recife, Pernambuco, Brazil

    Patrícia Leone Espinheira

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  1. Sivaldo Joaquim
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Joaquim, S., Bittencourt, I.I., de Amorim Silva, R. et al. What to do and what to avoid on the use of gamified intelligent tutor system for low-income students. Educ Inf Technol 27, 2677–2694 (2022). https://doi.org/10.1007/s10639-021-10728-4

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