Augmenting Teachers with Data Science Powers: Joining Human and Artificial Intelligence to Assist Students

  • Ranilson Paiva Universidade Federal de Alagoas (UFAL)
  • Júlio Cesar de Holanda Universidade Federal de Alagoas (UFAL)
  • Myron David Universidade Federal de Alagoas (UFAL)
  • João Pedro Universidade Federal de Alagoas (UFAL)

Resumo


Technology has the potential to influence the processes and outcomes of teaching and learning. Researchers notice a high demand for online education, but these environments generate educational data in high quantity, diversity, and velocity, which requires the use of technology. However, putting too much emphasis on artificial intelligence is not bringing the expected results. It is time to position teachers as the principal decision-makers in the "classroom" and use AI as an assistant. Our proposal is a tool (called T-Partner) to help online teachers: (1) search for relevant patterns in the educational data; (2) create visualizations to present the results in a more teacher-friendly way; (3) recommend study plans, based on students' needs. For that, we applied data science techniques on these data and processed the results, making it easier for teachers to understand them. We evaluated the tool, asking participants to use it to complete some tasks that simulate a teacher analyzing data to make pedagogical decisions. We evaluated time, correctness, number of doubts, and the participants' perceptions. The results show that most participants were able to complete the tasks in an appropriate amount of time and considered the T-Partner useful and easy to use in an online learning context.

Palavras-chave: Augmented Intelligence, Data Science, Online Education

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Publicado
11/11/2019
PAIVA, Ranilson; DE HOLANDA, Júlio Cesar; DAVID, Myron; PEDRO, João. Augmenting Teachers with Data Science Powers: Joining Human and Artificial Intelligence to Assist Students. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 30. , 2019, Brasília/DF. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 1721-1730. DOI: https://doi.org/10.5753/cbie.sbie.2019.1721.