Applications of data science to game learning analytics data: A systematic literature review

Alonso‐Fernández, Cristina; Calvo-Morata, Antonio; Freire, Manuel; Martínez‐Ortiz, Iván; Fernández‐Manjón, Baltasar

doi:10.1016/j.compedu.2019.103612

Cited by 103 publications

(69 citation statements)

References 82 publications

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“…Finally, authors in [35] conducted a systematic literature review, analyzing 87 papers that reported evidence of the outcomes of the analysis of game analytics data and/or learning analytics data collected from serious games. Authors concluded that the application of data science can increase the still-limited application of serious games in education.…”

Section: B Learning Analytics and Metricsmentioning

confidence: 99%

Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

et al. 2021

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Technology has become an integral part of our everyday life, and its use in educational environments keeps growing. Additionally, video games are one of the most popular mediums across cultures and ages. There is ample evidence that supports the benefits of using games for learning and assessment, and educators are mainly supportive of using games in classrooms. However, we do not usually find educational games within the classroom activities. One of the main problems is that teachers report difficulties to actually know how their students are using the game so that they can analyze properly the effect of the activity and the interaction of students. To support teachers, educational games should incorporate learning analytics to transform data generated by students when playing useful information in a friendly and understandable way. For this work, we build upon Shadowspect, a 3D geometry puzzle game that has been used by teachers in a group of schools in the US. We use learning analytics techniques to generate a set of metrics implemented in a live dashboard that aims to facilitate that teachers can understand students' interaction with Shadowspect. We depict the multidisciplinary design process that we have followed to generate the metrics and the dashboard with great detail. Finally, we also provide uses cases that exemplify how teachers can use the dashboard to understand the global progress of their class and each of their students at an individual level, in order to intervene, adapt their classes and provide personalize feedback when appropriate.

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Section: B Learning Analytics and Metricsmentioning

confidence: 99%

Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

et al. 2021

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“…The latest literature review is provided by Alonso-Fernández et al [8]. They systematically summarize the research progress of applying data science and technology to serious game analytics to support decision making.…”

Section: Foundationmentioning

confidence: 99%

“…The reason why we exclude the research on serious games as the previous literature review on this area already exists [8]. As shown in Fig.…”

Section: • Exclusion Criteriamentioning

confidence: 99%

Comprehensive review and classification of game analytics

Backlund

Engström

2020

SOCA

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As a business model, the essence of games is to provide a service to satisfy the player experience. From a business perspective, development in the game industry has led to the application of Business Intelligence (BI) becoming more and more extensive. However, related research lacks systematic examination and precise classification. This paper provides a comprehensive literature review of BI used in the game industry, focusing primarily on game analytics. This research mainly studies and discusses five aspects. First, we explore game analytics aspects in the available literature based on the traditional game value chain. Second, we find out the main purposes of using analytics in the game industry. Third, we present the problems or challenges in the game area, which can be addressed by using game analytics. Fourth, we also list different algorithms that have been used in game analytics for prediction. Finally, we summarize the research areas that have already been covered in literature but need further development. Based on the categories established after the mapping and the review findings, we also discuss the limitations of game analytics and propose potential research points for future research.

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“…Regarding the analysis to be performed on the collected data, the sample size restricts the application of artificial intelligence techniques as they require a high amount of data. However, comparing our work with the applications of data science to game and learning analytics data in general contexts [20], we consider that the sample size reached for participants with intellectual disabilities is highly representative. The number of students with ID in each classroom is substantially lower compared with other ordinary educational environments.…”

Section: Related Workmentioning

confidence: 99%

Game Analytics Evidence-Based Evaluation of a Learning Game for Intellectual Disabled Users

et al. 2019

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Learning games are becoming popular among teachers as educational tools. However, despite all the game development quality processes (e.g., beta testing), there is no total assurance about the game design appropriateness to the students' cognitive skills until the games are used in the classroom. Furthermore, games designed specifically for Intellectual Disabled (ID) users are even harder to evaluate because of the communication issues that this type of players have. ID users' feedback about their learning experience is complex to obtain and not always fully reliable. To address this problem, we use an evidence-based approach for evaluating the game design of Downtown, A Subway Adventure, a game created to improve independent living in users with ID. In this paper we exemplify the whole process of applying Game Analytics techniques to gather actual users' gameplay interaction data in real settings for evaluating the design. Following this process, researchers were able to validate different game aspects (e.g., mechanics) and could also identify game flaws that may be difficult to detect using formative evaluation or other observational-based methods. Results showed that the proposed evidence-based approach using Game Analytics information is an effective way to evaluate both the game design and the implementation, especially in situations where other types of evaluations that require users' involvement are limited.

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Applications of data science to game learning analytics data: A systematic literature review

Cited by 103 publications

References 82 publications

Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

Comprehensive review and classification of game analytics

Game Analytics Evidence-Based Evaluation of a Learning Game for Intellectual Disabled Users

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