PRAIA Education - Research Center for Really Applied Artificial Intelligence: education in the 4th industrial revolution

• Grant number: 22/00688-1
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• Start date: August 01, 2024
• End date: July 31, 2029
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Agreement: MCTI/MC
• Principal Investigator: Geber Lisboa Ramalho
• Grantee: Geber Lisboa Ramalho
• Host Institution: Centro de Informática (CIn). Universidade Federal de Pernambuco (UFPE). Ministério da Educação (Brasil). Recife , SP, Brazil
• City: Recife
• Pesquisadores principais: Celson Pantoja Lima ; Eduardo Santana de Almeida ; Elaine Harada Teixeira de Oliveira ; Evandro de Barros Costa ; Guido Lemos de Souza Filho ; Jorge Tarcisio da Rocha Falcão ; Leandro Balby Marinho ; Maria Auxiliadora Soares Padilha ; Rafael Ferreira Leite de Mello ; Silvio Romero de Lemos Meira ; Thiago Barros Murari
• Associated researchers: Alberto César Cavalcanti França ; Alberto Nogueira de Castro Junior ; Alex Sandro Gomes ; Alexandre Magno Andrade Maciel ; Alisson Vasconcelos de Brito ; Ana Carolina Brandão Salgado ; Anarosa Alves Franco Brandão ; André Luís de Medeiros Santos ; Andre Menezes Marques das Neves ; Augusto Cezar Alves Sampaio ; Bruno José Torres Fernandes ; Carina Frota Alves ; Carlos Eduardo Santos Pires ; Charles Andrye Galvao Madeira ; Claudia Lage Rebello da Motta ; Cláudio Elízio Calazans Campelo ; Clauirton de Albuquerque Siebra ; Cristiano Coelho de Araujo ; Danielle Rousy Dias Ricarte ; David Braga Fernandes de Oliveira ; Delamar José Volpato Dutra ; Edna Gusmão de Góes Brennand ; Edna Natividade da Silva Barros ; Edson Barbosa Lisboa ; Eduardo Camilo Inacio ; Esteban Walter Gonzalez Clua ; Fabio Queda Bueno da Silva ; Felipe Santana Furtado Soares ; Fernando José Ribeiro Sales ; Fernando Silvio Cavalcante Pimentel ; Filipe Carlos de Albuquerque Calegario ; Frederico Araújo Durão ; Gabriel Alves de Albuquerque Júnior ; Germano Crispim Vasconcelos ; Giordano Ribeiro Eulalio Cabral ; Guilherme Alvaro Rodrigues Maia Esmeraldo ; Isabela Gasparini ; Ivan do Carmo Machado ; Izabel Augusta Hazin Pires ; Jaime Simão Sichman ; José Carlos Silva Cavalcanti ; Joseana Macêdo Fechine Régis de Araújo ; Julio Cabero Almenara ; Kiev Santos da Gama ; Leandro Dias da Silva ; Leandro Silva Galvao de Carvalho ; Leonardo Augusto Gómez Castillo ; Lucas Silva Figueiredo ; Luciano de Andrade Barbosa ; Luciano Rogério de Lemos Meira ; Lucidio dos Anjos Formiga Cabral ; Marcelo Alves de Barros ; Maria Amalia Arruda Camara ; Natasha Correia Queiroz Lino ; Pablo Azevedo Sampaio ; Patricia Cabral de Azevedo Restelli Tedesco ; Patrick Henrique da Silva Brito ; Paulo Henrique Monteiro Borba ; Paulo Jorge Leitao Adeodato ; Ricardo Araújo Rios ; Ricardo Bastos Cavalcante Prudencio ; Roberta Macêdo Marques Gouveia ; Rodrigo Lins Rodrigues ; Sergio Castelo Branco Soares ; Simone Cristiane dos Santos Lima ; Taciana Pontual da Rocha Falcão ; Tatiane Nogueira Rios ; Thais Helena Chaves de Castro ; Thales Miranda de Almeida Vieira ; Vaninha Vieira dos Santos ; Veronica Teichrieb ; Vinicius Cardoso Garcia

Abstract

The PRAIA's research program is centered in Artificial Intelligence in Education (AIEd). The center targets the gap in the educational system created by the fourth industrial revolution, which is gradually destroying jobs and creating new ones. We started by identifying with our industrial partner SENAI, the major Brazilian player in education for the industrial sector, four key education challenges to guide our research work: large-scale quality education (how to provide quality education covering a large number of people and a large variety of courses and vocations?); fast-adapting job market-oriented education (How to timely adapt and/or anticipate the demands of the dynamic 4.0 job market?); competence-oriented learning (How effectively and systematically cover not only hard skills but also include soft skills and attitudes?); and novel education models (How to introduce AI not to reinforce almost obsolete models, but as a support for rethinking roles, structures, and education methods?). The state of the art in AIEd presents several works focusing on different objectives and approaches. Considering its three main stakeholders the main goals AIEd are (i) to support students to achieve better results in terms of educational gain, (ii) to provide teachers with tools and methods to improve the effectiveness of their actions; (c) to provide managers with valuable insights to support the institutions' operational and strategic decisions. Different AI approaches (machine learning, intelligent agents, natural language processing, etc.) have been studied and applied to systems, such as intelligent tutoring systems, recommendation systems, and adaptive environments. Despite the advances, there are still several open research subjects that should be addressed, particularly from the standpoint of the aforementioned challenges. Therefore, PRAIA will pursue new AI methods and techniques to develop technology-enhancing learning applications. More specifically, the center will produce original contributions to the state of the art of AI in Education related to the following research lines: - Scalable educational systems, focusing on methods that can be (i) generalizable for different domains and (ii) support classes with a massive number of students;- Systems for recommending and fasting creating educational resources inline with the skills required by the job market, which encompasses technical challenges related to the retrieval of information related to the skill forecast in the labor world and the creation or recommendation of educational resources to support instructors and educational managers to maintain the offered courses constantly updated and relevant;- Artificial intelligence models to support the learning of skills and attitudes, not only content. It includes the analysis of IoT devices and the application of multimodal machine learning approaches for both online and face-to-face environments. This also implies in suggesting to teachers different pedagogical approaches for a given lesson and student profile;- Propose new educational models where AI could enrich collaborative immersive environments (metaverse labs) where the students could interact with intelligent agents aiming the assistance and assessment of students during the simulation programs. This also includes rethinking about how to assess students during and after the course, based not only on cognitive, but also behavioral and affective learning aspects; - Provide new insights and practices on ethical AIEd. The literature reports many ethical issues, but there is much to be done to bring them into the concrete daily research and innovation; (AU)