New Perspectives in Science Education

Edition 13

Accepted Abstracts

Using Learning Analytics to Improve Digital Game-Based Learning

Larkin Cunningham, Cork Institute of Technology (Ireland)


Learning analytics provides the education researcher with the opportunity to collect and analyse a wide range of data related to learners and their contexts for the purpose of improving learner engagement and outcomes. While much of the focus of learning analytics has been on learning management systems, game-based learning offers the possibility of gathering rich data using the programmatic features of a game engine. Any interaction by a learner with the game-based environment can be tracked, with contextual data recorded. This paper presents a model for collecting game-based learning data that shows from a practical perspective what kind of data (such as events and timings) to collect and how it can be analysed with the express purpose of improving learning experiences and outcomes. A proof of concept is presented based on the game-based learning of graph theory. Graph theory is a branch of mathematics used in many scientific disciplines, for example to model molecules, atomic structures and the evolution of species. A virtual reality-based game introduces students to the fundamentals of graph theory, for example vertices and edges, and engages them in active learning as they connect vertices according to rules presented to them. Each action is recorded in a database for analysis, including a detailed log of student progress through an exercise, recording when vertices are correctly or incorrectly connected and the varying pace of progression through an exercise. The paper discusses how the educator can quickly analyse data to identify and correct common mistakes made by students, for example those based around a misinterpretation of the rules or a difficulty with the game’s mechanics. The paper also discusses how building learning analytics into a game early in its development can be useful as a means of formative evaluation as prototypes are iteratively improved through early and frequent stakeholder engagement.

Keywords: learning analytics, game based learning, virtual reality, active learning, graph theory;


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