Systematizing game learning analytics for serious games

Abstract

-Applying games in education provides multiple benefits clearly visible in entertainment games: their engaging, goal-oriented nature encourages students to improve while they play. Educational games, also known as Serious Games (SGs) are video games designed with a main purpose other than pure entertainment; their main purpose may be to teach, to change an attitude or behavior, or to create awareness of a certain issue. As educators and game developers, the validity and effectiveness of these games towards their defined educational purposes needs to be both measurable and measured. Fortunately, the highly interactive nature of games makes the application of Learning Analytics (LA) perfect to capture students' interaction data with the purpose of better understanding or improving the learning process. However, there is a lack of widely adopted standards to communicate information between games and their tracking modules. Game Learning Analytics (GLA) combines the educational goals of LA with technologies that are commonplace in Game Analytics (GA), and also suffers from a lack of standards adoption that would facilitate its use across different SGs. In this paper, we describe two key steps towards the systematization of GLA: 1), the use of a newly-proposed standard tracking model to exchange information between the SG and the analytics platform, allowing reusable tracker components to be developed for each game engine or development platform; and 2), the use of standardized analysis and visualization assets to provide general but useful information for any SG that sends its data in the aforementioned format. These analysis and visualizations can be further customized and adapted for particular games when needed. We examine the use of this complete standard model in the GLA system currently under development for use in two EU H2020 SG projects.

Using game authoring platforms to develop screen-based simulated functional assessments in persons with executive dysfunction following traumatic brain injury

“…This is in the line of what is being called evidence-based medicine. Recent development as new specifications for user interaction data tracking such as Experience API (xAPI) [131] and the availability of new cloud infrastructure to collect all the data generated in serious games will greatly simplify the data collection tasks and will allow to create simulations that deal with more complex tasks [132]. [38].…”

Improving Serious Games Analyzing Learning Analytics Data: Lessons Learned

“…Fig. 2 describes some of the visualizations included in the teacher dashboard used in the latest experiments to provide real-time feedback in classroom settings [15]. The dashboard uses xAPI-SG concepts such as completables (e.g.…”

Full Lifecycle Architecture for Serious Games: Integrating Game Learning Analytics and a Game Authoring Tool

“…We propose a complete and scalable analytics architecture, based on standards, that encompasses the whole process from game development to the analysis and visualization of results; a design guided game development where the interaction tracker sends players' interactions to the analytics platform composed of collector, In this architecture, SGs send traces in a standard-based format to a server that analyzes the data and transforms it into useful information. This analyzed information is then displayed in dashboards for different stakeholders: teachers or instructors in charge of players, the players themselves, game developers or designers and researchers [12].…”

“…A complete architecture to manage GLA requires handling several interlocking parts: data tracking, data analysis and results visualization. We proposed the following standard-based architecture, a combination of modules that work together to analyze and visualize information collected from SGs [12]. Fig.…”