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Convergent Classroom: From Nature to Digital to Cognition in Geometry Acquisition
Author(s) -
Alcides Bernardo Tello,
Cayto Didi Miraval Tarazona,
Elia Bernardo Tello,
Teófanes Huerta Mallqui
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1828/1/012137
Subject(s) - cognition , object (grammar) , computer science , mathematics education , test (biology) , geometry , psychology , artificial intelligence , mathematics , neuroscience , paleontology , biology
Artificial Intelligence can provide intelligent solutions for the educational system. This article uses an object detection algorithm to explore physical surroundings and extract geometric shapes from two- and three-dimensional objects in real time within or outside a classroom. Having the shapes, the geometry lesson begins. We named it “Convergent Classroom”. We have conducted a post-test only group design in which first-year pupils from secondary school participated in the sessions. Our main results show substantial statistical evidence to support pupils’ higher geometry acquisition engagement using computer vision algorithm, compared to those who did not use it. This nature-to-digital-to-cognition engagement can be further explored by neuroscience measurement to understand what happens in pupils’ brain when they connect geometrical shapes from their surroundings to geometric cognition. Furthermore, these observed significant differences call for teachers to implement the already known algorithms in future classrooms.

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