A Math Educacional Computer Game Using Procedural Content Generation

Rodrigues, Luiz; Bonidia, Robson Parmezan; Brancher, Jacques Duílio

doi:10.5753/cbie.sbie.2017.756

Cited by 14 publications

(14 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One major research challenge of PCG for math education is generating math problems at various difficulty levels. Rodrigues et al introduced MentalMath [13], which is an adventure game that requires the players to solve math problems as a final challenge after winning a shooting game at each level. The authors employed a parametric-based method to generate text arithmetic problems based on templates.…”

Section: Related Workmentioning

confidence: 99%

Procedural generation of problems for elementary math education

Smeets²,

Bidarra³

2021

IJSG

View full text Add to dashboard Cite

Mathematics education plays an essential role in children’s development, and there are many online applications aimed at supporting this process. However, manually creating math problems with a variety of textual and visual content is very time-consuming and expensive. This article presents a generic approach for procedural generation of mathematical problems, including their corresponding textual representations. The content generation process consists of two phases: abstract math problem generation and text generation. For the generation of abstract math problems, we propose a generic template-based method that operates across a variety of difficulty-levels and domains, including arithmetic, comparison, ordering, mathematical relationships, measurement, and geometry. Subsequently, we propose a multi-language adaptive textual content generation pipeline to realize the generated abstract math problems into semantically coherent text questions in natural language. A workflow time gain evaluation shows that the system yields an average time saving of 56%. Further, human expert evaluation of this approach indicates that the content it generates is sensible and solvable for primary school students.

show abstract

Section: Related Workmentioning

confidence: 99%

Procedural generation of problems for elementary math education

Smeets²,

Bidarra³

2021

IJSG

View full text Add to dashboard Cite

show abstract

“…PCG have has applied in EG approaching a varied set of subjects, such as math [Rodrigues et al 2017, Smith et al 2012, Butler et al 2015, Lara et al 2018, computing [Horn et al 2016, Dong and Barnes 2017, Valls-Vargas et al 2017, Dezani et al 2017, resource management [Aslam et al 2017, Luo et al 2017, Grappiolo et al 2011, evolution [Soule et al 2017], therapy [Duval et al 2017], and reading [Hooshyar et al 2018]. In those studies, PCG was mostly used to generate levels or its components (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The exceptions are the cases where the algorithms were analyzed [Soule et al 2017, Smith et al 2012, Valls-Vargas et al 2017, Dong and Barnes 2017 or no user evaluation was performed [Dezani et al 2017]. In contrast, works reporting user-based studies mainly evaluated users' behavior [Butler et al 2015], affective states' changes [Lara et al 2018], learning gains [Hooshyar et al 2018, Rodrigues et al 2017, Horn et al 2016, in-game performance [Aslam et al 2017], opinions [Duval et al 2017], and the proposed approach's performance [Luo et al 2017, Grappiolo et al 2011].…”

Section: Literature Reviewmentioning

confidence: 99%

Playing an Educational Game Featuring Procedural Content Generation: Which Attributes Impact Players’ Curiosity?

Rodrigues

Brancher

2019

RENOTE

Self Cite

View full text Add to dashboard Cite

Understanding which and how attributes impact player experience can contribute to designing more tailored tools, providing concerns on how to improve these. However, there is a gap in the understanding of what impacts learners’ experience when interacting with Educational Games (EG) featuring Procedural Content generation (PCG) as these have been scantly used together. This article presents an empirical study on which attributes impact both math’s and game’s curiosity of players when interacting with an EG that uses PCG. The results show the attributes that led to higher or lower curiosity, as well aswhich of them are associated with it. Hence, advancing the understanding of what drives players’ curiosity, contributing to the design of EG that feature PCG.

show abstract

“…In this case, the generated scenario is the environment itself rather than any of the tasks or events taking place within it. Finally, Rodrigues, Bonidia, and Brancher () have developed a math educational computer game using PCG with aim to improve motivation in users to practice math by solving problems. Results of their experiments, similar to previous related works, showed that the proposed game could successfully arouse students' interest.…”

Section: Related Workmentioning

confidence: 99%

A data‐driven procedural‐content‐generation approach for educational games

Hooshyar

Yousefi

Wang

et al. 2018

Computer Assisted Learning

View full text Add to dashboard Cite

Although game-based learning has been increasingly promoted in education, there is a need to adapt game content to individual needs for personalized learning. Procedural content generation (PCG) offers a solution for difficulty in developing game contents automatically by algorithmic means as it can generate individually customizable game contents applicable to various objectives. In this paper, we advanced a data-driven PCG approach benefiting from a genetic algorithm and support vector machines to automatically generate educational-game contents tailored to individuals' abilities. In contrast to other content generation approaches, the proposed method is not dependent on designer's intuition in applying game contents to fit a player's abilities.We assessed this data-driven PCG approach at length and showed its effectiveness by conducting an empirical study of children who played an educational languagelearning game to cultivate early English-reading skills. To affirm the efficacy of our proposed method, we evaluated the data-driven approach against a heuristic-based approach. Our results clearly demonstrated two things. First, users realized greater performance gains from playing contents tailored to their abilities compared with playing uncustomized game contents. Second, this data-driven approach was more effective in generating contents closely matching a specific player-performance target than the heuristic-based approach. KEYWORDS data-driven approach, early English-reading skills, educational game, procedural contents generation 1 | INTRODUCTION Adaptive learning is an educational method for personalized learning. Personalized learning refers to learning and instructional approaches that are driven by needs and interests of individual learners. It represents a shift from teacher-centred learning towards student-centred learning. It is built upon constructivist learning theory that emphasizes the critical role of student in learning by constructing personally relevant meaning. Personalized learning cannot be realized in traditional classrooms in a large scale. Instead, computers or information and communication technologies play an important role in this regard by the following: (a) adapting learning objectives, content, and progress according to individual learning needs, abilities, prior knowledge, and preferences; (b) recording individual activities for analysis; and (c) providing personalized feedback after assessing individual performance.

show abstract

A Math Educacional Computer Game Using Procedural Content Generation

Cited by 14 publications

References 15 publications

Procedural generation of problems for elementary math education

Procedural generation of problems for elementary math education

Playing an Educational Game Featuring Procedural Content Generation: Which Attributes Impact Players’ Curiosity?

A data‐driven procedural‐content‐generation approach for educational games

Contact Info

Product

Resources

About