z-logo
open-access-imgOpen Access
Assistente conversacional para resolução de Problemas Trigonométricos em Linguagem Natural
Author(s) -
Neiva Larisane Kuyven,
Vinícius João de Barros Vanzin,
Carlos André Antunes,
Alexandra Cemin,
João Luis Tavares da Silva,
Liane Margarida Rockenbach Tarouco
Publication year - 2020
Publication title -
revista brasileira de informática na educação
Language(s) - English
Resource type - Journals
eISSN - 2317-6121
pISSN - 1414-5685
DOI - 10.5753/rbie.2020.28.0.208
Subject(s) - humanities , philosophy
Intelligent Tutoring Systems (ITS) are an interdisciplinary area aiming to investigate how to model instructional content based on pedagogical decisions and students’ interactions. Those decisions use student modeling, basedrules domain knowledge and teaching strategies. Most ITS advocate that the feedback of exercises and activities planned by the system define the knowledge students’ level. Therefore, limiting the student’s interactive possibility through the conversational interface. A more “wizard” approach integrates Chatbots into the ITS, using artificial intelligence techniques to manage interactions. This article intends to provide a greater degree of freedom for the Kuyven et al. RBIE V.28 – 2020 209 student through natural language inputs of problems out of the activity set of the ITS. This work presents a Recurrent Neural Network (RNR) model, which translates trigonometric problems, entered by students, into equation models as part of a larger ITS Trigonometry project. The experiments conducted showed that the proposed model correctly classified a large part of the problems posed by students, providing answers to the proposed problems in a step-bystep resolution format of a Computer Algebra System (CAS).

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom