Convergent classroom: From nature to digital to cognition in geometry acquisition

Alcides Bernardo Tello, Cayto Didi Miraval Tarazona, Elia Bernardo Tello, Teófanes Huerta Mallqui

Research output: Contribution to journalConference articlepeer-review

Abstract

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.

Original languageEnglish
Article number012137
JournalJournal of Physics: Conference Series
Volume1828
Issue number1
DOIs
StatePublished - 4 Mar 2021
Event2020 International Symposium on Automation, Information and Computing, ISAIC 2020 - Beijing, Virtual, China
Duration: 2 Dec 20204 Dec 2020

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