Supporting Learning Analytics in Educational Games in consideration of Qualifications-Based Learning

Abstract

Computer and video games have established themselves in society and are increasingly finding their way into learning with so-called Educational Games (EduGame). EduGames often provides a fundamental analysis of learners' learning results, but there is currently no existing approach to map the learning results automatically to digital standardized machine-readable Qualifications. In addition, different learning providers tend to use different approaches to describe Qualifications, often in the form of free text. Therefore, it is currently impossible to compare the reached Competencies and Qualifications (CQ) across different learning providers or only manually with high effort. In this paper, a prototypical implementation for automated mapping of learners' learning results in EduGames to standardized CQ will be introduced. The paper presents the conceptual work, the subsequent prototypical implementation with the chosen Analytics Environment, Game Engine, Learning Management System, and the evaluation results.