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786 results on '"Bittencourt, Ig"'

7. Knowledge Tracing Unplugged: From Data Collection to Model Deployment

Author

Rodrigues, Luiz, Avila-Santos, Anderson P., Silva, Thomaz E., da Penha, Rodolfo S., Neto, Carlos, Challco, Geiser, dos Santos, Ermesson L., Souza, Everton, Guerino, Guilherme, Vieira, Thales, Marinho, Marcelo, Macario, Valmir, Bittencourt, Ig Ibert, Dermeval, Diego, Isotani, Seiji, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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8. Anticipating Student Abandonment and Failure: Predictive Models in High School Settings

Author

Queiroga, Emanuel Marques, Santana, Daniel, da Silva, Marcelo, de Aguiar, Martim, dos Santos, Vinicius, Mello, Rafael Ferreira, Bittencourt, Ig Ibert, Cechinel, Cristian, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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9. Breaking the Cycle: AI Boosting Communication Skills of Low-Income Students in Brazil

Author

de Gama, Renata Miranda, Chalco, Geiser, Santos, Jário, Reis, Marcelo, Sobrinho, Álvaro, Isotani, Seiji, Bittencourt, Ig Ibert, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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10. Contextual Features for Automatic Essay Scoring in Portuguese

Author

Galhardi, Lucas, Herculano, Maria Fernanda, Rodrigues, Luiz, Miranda, Péricles, Oliveira, Hilário, Cordeiro, Thiago, Bittencourt, Ig Ibert, Isotani, Seiji, Mello, Rafael Ferreira, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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11. Exploring NLP and Embedding for Automatic Essay Scoring in the Portuguese

Author

Carvalho, Ruan, Lins, Lucas Fernandes, Rodrigues, Luiz, Miranda, Péricles, Oliveira, Hilário, Cordeiro, Thiago, Bittencourt, Ig Ibert, Isotani, Seiji, Mello, Rafael Ferreira, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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12. Bringing AIED, Public Policy and GDPR to Promote Educational Opportunities in Brazil

Author

Portela, Carlos, Rocha, Jorge, Palomino, Paula, Lisbôa, Rodrigo, Cordeiro, Thiago, Silva, Alan, Bittencourt, Ig, Dermeval, Diego, Marques, Leonardo, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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13. Unhappiness and Demotivation Among Students in Gamified Tutoring Systems: Toward Understanding the Gender Gap

Author

Benevides, Kamila, Santos, Jário, Chalco, Geiser, Reis, Marcelo, Sobrinho, Álvaro, Marques, Leonardo, Dermeval, Diego, Mello, Rafael, Silva, Alan, Isotani, Seiji, Bittencourt, Ig Ibert, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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14. An Optimization Approach for Elementary School Handwritten Mathematical Expression Recognition

Author

Chevtchenko, Sergio F., Carvalho, Ruan, Rodrigues, Luiz, Souza, Everton, Rosa, Daniel, Cordeiro, Filipe, Pereira, Cicero, Vieira, Thales, Marinho, Marcelo, Dermeval, Diego, Bittencourt, Ig Ibert, Isotani, Seiji, Macario, Valmir, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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15. Handwritten Equation Detection in Disconnected, Low-Cost Mobile Devices

Author

Souza, Everton, Santos, Ermesson L. dos, Rodrigues, Luiz, Rosa, Daniel, Cordeiro, Filipe, Pereira, Cicero, Chevtchenko, Sergio, Carvalho, Ruan, Vieira, Thales, Marinho, Marcelo, Dermeval, Diego, Bittencourt, Ig Ibert, Isotani, Seiji, Macario, Valmir, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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16. Exploring the Impact of Gender Stereotypes on Motivation, Flow State, and Learning Performance in a Gamified Tutoring System

Author

Silva, Kelly, Santos, Jário, Chalco, Geiser, Reis, Marcelo, Marques, Leonardo, Silva, Alan, Sobrinho, Álvaro, Dermeval, Diego, Mello, Rafael, Bittencourt, Ig Ibert, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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19. Does Gender Stereotype Threat Affects the Levels of Aggressiveness, Learning and Flow in Gamified Learning Environments?: An Experimental Study

Author

Santos, Jário, Andrade, Ester, Benevides, Kamila, Silva, Kelly, Nascimento, João, Bittencourt, Ig, Pereira, Marcos, Fernandes, Sheyla, and Isotani, Seiji

Abstract

Studies in the literature reported several positive benefits provided by the use of technology in online education, especially in the gamified tutoring system. However, despite the benefits of intelligent tutoring systems, recent studies indicate the presence of a gender gap not considered in the construction of the attributes present in the gamified tutoring system. To investigate this impact by observing users' behavioral changes in gamified online educational environments, the present study aims to investigate the effects of the stereotype threats using a quantitative experiment with a Factorial Design in three gamified environments (stereotypical male version, stereotypical female version and control environment). Was conducted an experiment with 150 individuals (high school and undergraduate students) without considering age, ethnicity, or social class. The results show that the participants allocated to the male learning environment present an increase in aggressiveness level. Furthermore, the results also show the stereotypical male and female learning environments increased the participants' performance level. Another finding was that the threatening condition provided a significant increase in the participants' flow level among males subjected to a threatening condition, which did not manifest in the case of females. In addition, this study also observed the effect of the stereotype threat on men and women in the threatening condition by division in the 34-year age group, resulting in a significant increase in the level of flow among men. This study showed previous results show that the gamified environment influences psychological variables as aggressiveness, intellectual performance, and flow level, they raise questions about the direction of these changes and the impact they may have on users' usability and performance in these systems.

Published
2023
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21. Ethics of AI in Education: Towards a Community-Wide Framework

Author

Holmes, Wayne, Porayska-Pomsta, Kaska, Holstein, Ken, Sutherland, Emma, Baker, Toby, Shum, Simon Buckingham, Santos, Olga C., Rodrigo, Mercedes T., Cukurova, Mutlu, Bittencourt, Ig Ibert, and Koedinger, Kenneth R.

Abstract

While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between "doing ethical things" and "doing things ethically," to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far from trivial. As a first step towards addressing this critical gap, we invited 60 of the AIED community's leading researchers to respond to a survey of questions about ethics and the application of AI in educational contexts. In this paper, we first introduce issues around the ethics of AI in education. Next, we summarise the contributions of the 17 respondents, and discuss the complex issues that they raised. Specific outcomes include the recognition that most AIED researchers are not trained to tackle the emerging ethical questions. A well-designed framework for engaging with ethics of AIED that combined a multidisciplinary approach and a set of robust guidelines seems vital in this context.

Published
2022
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22. Planning Gamification Strategies Based on User Characteristics and DM: A Gender-Based Case Study

Author

Toda, Armando M., Oliveira, Wilk, Shi, Lei, Bittencourt, Ig Ibert, Isotani, Seiji, and Cristea, Alexandra

Abstract

Gamification frameworks can aid in gamification planning for education. Most frameworks, however, do not provide ways to select, relate or recommend how to use game elements, to gamify a certain educational task. Instead, most provide a "one-size-fits-all" approach covering all learners, without considering different user characteristics, such as gender. Therefore, this work aims to adopt a data-driven approach to provide a set of game element recommendations, based on user preferences, that could be used by teachers and instructors to gamify learning activities. We analysed data from a novel survey of 733 people (male=569 and female=164), collecting information about user preferences regarding game elements. Our results suggest that the most important rules were based on four (out of nineteen) types of game elements: Objectives, Levels, Progress and Choice. From the perspective of user gender, for the female sample, the most interesting rule associated Objectives with Progress, Badges and Information (confidence=0.97), whilst the most interesting rule for the male sample associated also Objectives with Progress, Renovation and Choice (confidence=0.94). These rules and our descriptive analysis provides recommendations on how game elements can be used in educational scenarios. [For the full proceedings, see ED599096.]

Published
2019

23. Analysing gamification elements in educational environments using an existing Gamification taxonomy

Author

Toda, Armando M., Klock, Ana C. T., Oliveira, Wilk, Palomino, Paula T., Rodrigues, Luiz, Shi, Lei, Bittencourt, Ig, Gasparini, Isabela, Isotani, Seiji, and Cristea, Alexandra I.

Subjects
Computer Science - Human-Computer Interaction
Abstract

Gamification has been widely employed in the educational domain over the past eight years when the term became a trend. However, the literature states that gamification still lacks formal definitions to support the design and analysis of gamified strategies. This paper analysed the game elements employed in gamified learning environments through a previously proposed and evaluated taxonomy while detailing and expanding this taxonomy. In the current paper, we describe our taxonomy in-depth as well as expand it. Our new structured results demonstrate an extension of the proposed taxonomy which results from this process, is divided into five dimensions, related to the learner and the learning environment. Our main contribution is the detailed taxonomy that can be used to design and evaluate gamification design in learning environments., Comment: Smart Learn. Environ. 6, 16 (2019)

Published
2020
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24. Artificial Intelligence and Educational Policy: Bridging Research and Practice

Author

Isotani, Seiji, Bittencourt, Ig Ibert, Walker, Erin, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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25. Gamiflow: Towards a Flow Theory-Based Gamification Framework for Learning Scenarios

Author

Chalco Challco, Geiser, Bittencourt, Ig Ibert, Reis, Marcelo, Santos, Jario, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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26. The Good and Bad of Stereotype Threats: Understanding Its Effects on Negative Thinking and Learning Performance in Gamified Tutoring

Author

Fernanda Silva Barbosa, Jessica, Chalco Challco, Geiser, Rafael Do Nascimento Martins, Francys, Felix de Sousa, Breno, Bittencourt, Ig Ibert, Reis, Marcelo, Santos, Jário, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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27. A Case Study on AIED Unplugged Applied to Public Policy for Learning Recovery Post-pandemic in Brazil

Author

Portela, Carlos, Lisbôa, Rodrigo, Yasojima, Koiti, Cordeiro, Thiago, Silva, Alan, Dermeval, Diego, Marques, Leonardo, Santos, Jário, Mello, Rafael, Macário, Valmir, Bittencourt, Ig Ibert, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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28. Even Boosting Stereotypes Increase the Gender Gap in Gamified Tutoring Systems: An Analysis of Self-efficacy, Flow and Learning

Author

Takeshita, Maria, Challco, Geiser Chalco, Reis, Marcelo, Santos, Jário, Isotani, Seiji, Bittencourt, Ig Ibert, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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29. AIED Unplugged: Leapfrogging the Digital Divide to Reach the Underserved

Author

Isotani, Seiji, Bittencourt, Ig Ibert, Challco, Geiser C., Dermeval, Diego, Mello, Rafael F., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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30. Question Classification with Constrained Resources: A Study with Coding Exercises

Author

Rodrigues, Luiz, Pereira, Filipe, Santos, Jario, Oliveira, Elaine, Gasparini, Isabela, Mello, Rafael, Marques, Leonardo, Dermeval, Diego, Bittencourt, Ig Ibert, Isotani, Seiji, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Wang, Ning, editor, Rebolledo-Mendez, Genaro, editor, Dimitrova, Vania, editor, Matsuda, Noboru, editor, and Santos, Olga C., editor

Published
2023
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31. Blended learning and media centers: A bibliometric analysis

Author

Challco, Geiser Chalco, Silva, Wesley Vieira da, Setton Gonçalves, Bruno, Almeida Levino, Natallya de, Bittencourt, Ibsen Mateus, Kaczam, Fabíola, Oliveira, Elaine Harada Teixeira de, Martins, Flavio Pinheiro, Lima Filho, Walter Araujo de, Araújo, Ronaldo Ferreira de, Bittencourt, Ig Ibert, and Paiva, Ranilson Oscar Araújo

Published
2024
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33. What to Do and What to Avoid on the Use of Gamified Intelligent Tutor System for Low-Income Students

Author

Joaquim, Sivaldo, Bittencourt, Ig Ibert, de Amorim Silva, Rafael, Espinheira, Patrícia Leone, and Reis, Marcelo

Abstract

Educational indicators have revealed that a significant portion of Brazilian Basic Education students have a less than satisfactory skill level in reading and solving Mathematics problems. Despite several proven benefits, adaptive learning technologies are scarcely used with low-income students in public schools' due unavailable resources and lack of technological infrastructure. Nonetheless, there is a great expectation that the access to new technologies will assist and improve teaching practices and contribute to enhance learning performance. This study aimed to identify good and bad pedagogical practices from teaching and learning processes using a gamified Intelligent Tutor System (ITS) in Elementary Education. In order to achieve this goal, a case study was conducted with a qualitative research approach based on observations made in classrooms in a 9 months period and the application of Framework Analysis as a data analysis technique involving 6 teachers and 112 students aged between 9 and 21 years old from public schools in Brazil. Results presented provide evidence of significant improvement in the domain of Portuguese Language and Mathematical skills. The highlights of the paper are the seven good practices and six bad pedagogical practices with the use of gamified ITS. Additionally, while gamified ITS are important to improve learning and promote more engagement, this study also sheds light on the importance of using gamified ITS aligned with the school curriculum and a clear intervention proposal instead of voluntary use.

Published
2022
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34. Brain-Imaging Techniques in Educational Technologies: A Systematic Literature Review

Author

Tenório, Kamilla, Pereira, Emanuel, Remigio, Sterfanno, Costa, Derecky, Oliveira, Wilk, Dermeval, Diego, da Silva, Alan Pedro, Bittencourt, Ig Ibert, and Marques, Leonardo Brandão

Abstract

Recent studies are increasingly using brain-imaging techniques in the technology-enhanced learning (TEL) context to understand students' cognitive processes during technology-assisted learning, with the ultimate goal to improve students' outcomes in these environments. Given the importance of the promising impact of brain-imaging techniques in the technology-enhanced learning context, it is of utmost importance to analyze and investigate studies published in the intersection of these research areas. However, despite the growing interest in this promising research field, there is a lack of systematic literature review investigating how brain-imaging techniques have been applied in technology-enhanced learning environments. Therefore, this article presents a systematic literature review (SLR) using a well-accepted guideline to perform a rigorous study of the current literature to investigate, analyze, and understand how brain-imaging techniques have been applied in technology-enhanced learning contexts. This SLR considered studies published in nine academic databases that resulted in a total of 3910 studies that, after the selection process, were reduced to 37 studies (published during 2001-2019) for the final analysis. The studies' content analysis was used to classify the studies according to their objectives, brain-imaging techniques and devices used, educational levels, study domains, and studies outcomes. The main results indicate that (i) most studies aim to use brain-imaging methods to measure/detect students' psychological processes while using educational technology to provide a personalized experience, (ii) the most used brain-imaging technique in the studies is electroencephalogram, and (iii) the most investigated study domain was Mathematics and Biology. Moreover, this article highlights some gaps found in the state-of-the-art and provides insights that can be used for future research.

Published
2022
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35. Sequence Labeling Algorithms for Punctuation Restoration in Brazilian Portuguese Texts

Author

Lima, Tiago B. De, Miranda, Pericles, Mello, Rafael Ferreira, Wenceslau, Moesio, Bittencourt, Ig Ibert, Cordeiro, Thiago Damasceno, José, Jário, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xavier-Junior, João Carlos, editor, and Rios, Ricardo Araújo, editor

Published
2022
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36. Authoring Inner Loops of Intelligent Tutoring Systems Using Collective Intelligence

Author

Tenório, Thyago, Isotani, Seiji, Bittencourt, Ig Ibert, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rodrigo, Maria Mercedes, editor, Matsuda, Noburu, editor, Cristea, Alexandra I., editor, and Dimitrova, Vania, editor

Published
2022
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38. The State-of-the-Art on Collective Intelligence in Online Educational Technologies

Author

Tenorio, Thyago, Isotani, Seiji, Bittencourt, Ig Ibert, and Lu, Yu

Abstract

The application of the collective intelligence (CI) concept has yielded significant results in many knowledge areas and it has substantial potential to yield results in the educational context. In view of distance education and online educational technologies, the use of CI has enormous potential to improve collaboration, social learning, and problem solving. However, there is still not a clear understanding of how CI has been used in combination with online educational technologies, due to a lack of secondary studies in this context. Thus, in this article, we conducted a systematic literature review with the objectives of determining how CI has been used in online learning environments and identifying the benefits and/or the difficulties that are encountered in the process of its use. We have analyzed 354 studies and only 30 have met our inclusion criteria. The main contributions to online learning of these 30 studies were categorized and discussed. Our results have shown that CI enables the exploration. of the potential of collaboration and collaborative learning in social environments to create more diverse educational contents and to improve educational aspects using group intelligence. Moreover, approximately 74% of the studies presented positive evidence of learning benefits. However, approximately 40% of the studies also presented positive evidence of implementation difficulties. These and other results presented in this article demonstrate that more research is necessary to explore the potential of CI in online learning technologies.

Published
2021
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40. Does gender-stereotyped gamification increase negative thinking? Results from an experimental study with logic tutoring systems.

Author

Silva Barbosa, Jessica Fernanda, Chalco Challco, Geiser, and Bittencourt, Ig Ibert

Subjects
GENDER stereotypes, EDUCATIONAL games, TUTORS & tutoring, STEM education, EDUCATIONAL technology
Abstract

Gender-stereotypical design, such as the predominance of blue colors in interfaces, leaderboards with only men at the top, and male avatars, may have negative effects on women in gamified tutoring systems, especially in courses with a majority of male participation, such as courses of Science, Technology, Engineering, and Mathematics (STEM). We conducted a quasi-experimental study with 133 Brazilian high school students in order to determine the impact of gender stereotypes on the flow state of students, their negative thinking, and their learning performance. These participants were divided into a control group (non-stereotyped) and two intervention groups (male and female stereotypes). Girls' flow state and academic performance were negatively impacted by male stereotypes, as indicated by p.adj values of 0.031 and 0.046, respectively. Contrary to popular belief, participants' negative thoughts were more prevalent in a neutral (non-stereotyped) context than in one with a stereotype threat condition with p.adj value of 0.039. These findings suggest that gender stereotypes should be investigated further, as there are instances in which, contrary to expectations, their effects can be positive. Therefore, the primary contribution of the study is to provide funding for future research into the causes of the observed effects of gender stereotypes on negative thinking. These findings are also applicable to specialists in the design and development of gamified systems, as they support guidelines and the need to develop mechanisms for adapting game elements and the interface of these systems. [ABSTRACT FROM AUTHOR]

Published
2024
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41. A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System

Author

Pian, Yang, Lu, Yu, Huang, Yuqi, Bittencourt, Ig Ibert, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bittencourt, Ig Ibert, editor, Cukurova, Mutlu, editor, Muldner, Kasia, editor, Luckin, Rose, editor, and Millán, Eva, editor

Published
2020
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42. Can Ontologies Support the Gamification of Scripted Collaborative Learning Sessions?

Author

Challco, Geiser Chalco, Bittencourt, Ig Ibert, Isotani, Seiji, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bittencourt, Ig Ibert, editor, Cukurova, Mutlu, editor, Muldner, Kasia, editor, Luckin, Rose, editor, and Millán, Eva, editor

Published
2020
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43. Helping Teachers Help Their Students: A Human-AI Hybrid Approach

Author

Paiva, Ranilson, Bittencourt, Ig Ibert, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bittencourt, Ig Ibert, editor, Cukurova, Mutlu, editor, Muldner, Kasia, editor, Luckin, Rose, editor, and Millán, Eva, editor

Published
2020
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45. FOCA: A Methodology for Ontology Evaluation

Author

Bandeira, Judson, Bittencourt, Ig Ibert, Espinheira, Patricia, and Isotani, Seiji

Subjects
Computer Science - Artificial Intelligence
Abstract

Modeling an ontology is a hard and time-consuming task. Although methodologies are useful for ontologists to create good ontologies, they do not help with the task of evaluating the quality of the ontology to be reused. For these reasons, it is imperative to evaluate the quality of the ontology after constructing it or before reusing it. Few studies usually present only a set of criteria and questions, but no guidelines to evaluate the ontology. The effort to evaluate an ontology is very high as there is a huge dependence on the evaluator's expertise to understand the criteria and questions in depth. Moreover, the evaluation is still very subjective. This study presents a novel methodology for ontology evaluation, taking into account three fundamental principles: i) it is based on the Goal, Question, Metric approach for empirical evaluation; ii) the goals of the methodologies are based on the roles of knowledge representations combined with specific evaluation criteria; iii) each ontology is evaluated according to the type of ontology. The methodology was empirically evaluated using different ontologists and ontologies of the same domain. The main contributions of this study are: i) defining a step-by-step approach to evaluate the quality of an ontology; ii) proposing an evaluation based on the roles of knowledge representations; iii) the explicit difference of the evaluation according to the type of the ontology iii) a questionnaire to evaluate the ontologies; iv) a statistical model that automatically calculates the quality of the ontologies.

Published
2016

46. Conclusions

Author

Oliveira, Wilk, Bittencourt, Ig Ibert, Oliveira, Wilk, and Bittencourt, Ig Ibert

Published
2019
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50. Introduction

Author

Oliveira, Wilk, Bittencourt, Ig Ibert, Oliveira, Wilk, and Bittencourt, Ig Ibert

Published
2019
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