A tanuláselemzés fejlődése és nemzetközi alkalmazása az oktatásban

Abstract

Learning Analytics (LA) is a relatively young, interdisciplinary research field due to its technological foundations. It primarily focuses on understanding and optimizing learning within electronic learning envi­ronments and their relevance. According to the European Commission’s Hungarian "Education and Training 2020" working group, LA "holds significant potential for improving the quality of education and learn­ing". Learning analytics functions both as an academic field and a commercial market, which has rapidly evolved over the past decade. As a research and educational domain, it lies at the intersection of learning sciences (e.g., educational research, learning and assessment sciences, educational technology), analytics (e.g., statistics, visualization, com­puter science/data science, artificial intelligence), and human-centered design (e.g., usability, participatory design, socio-technical systems thinking).

Historically, the most common application of learning analytics has been predicting student academic success, specifically identifying stu­dents at risk of failing a course or dropping out of their studies. While these predictive capabilities provide a strong rationale for adopting learning analytics, research and empirical evidence from practice indi­cate that its applications extend beyond this scope, offering further po­tent and productive opportunities to support teaching and learning.