Comparative analysis of learning analytics tools to improve learning used in different learning platforms

Abstract

The aim of the paper is to present Go-Lab and Moodle learning platforms as tools suitable for applying Learning Analytics to improve learning. Moodle is one of the most popular open source learning platforms used both in schools and Universities, and Go-Lab is learning platform for Inquiry-Based Science Education in schools developed in Go-Lab project funded by EU 7FP programme and continued to be developed in new Next-Lab project funded by Horizon 2020. Learning Analytics aims to collect and analyse user activities to make learning and learning environments more effective and efficient. Go-Lab Learning Analytics services provide means to track user activities and analyse this tracked data. This provides the foundation for guidance mechanisms for students through scaffolding, as well as intelligent decision support for teachers and lab owners. More specifically, Learning Analytics services provide support for recommendations, intelligent feedback for students, and analytical reports that help to design better Inquiry-Based Learning scenarios and spaces. The add-on services consist of the bartering platform and the lab booking system to support Go-Lab Portal in different aspects. The bartering platform offers teachers peer assistance through a tutor social platform for expertise sharing related to online labs and inquiry learning spaces. Teachers are motivated to help other teachers and share their skills and knowledge about online labs on the bartering platform. On the other hand, there are the number of reports, blocks and other plugins for Moodle that provide Learning Analytics in this platform such as logs, activity, statistics etc. which are useful for students, teachers, administrators and decision-makers. A number of systems can be integrated with Moodle to provide Learning Analytics information. The paper is organised as follows: (1) systematic review on research topic, (2) analysis of Learning Analytics / educational data mining tools used in both platforms, (3) comparative analysis of possibilities provided by Learning Analytics tools in both platforms to improve learning, and (4) discussion and conclusion. The work presented in this paper is partially supported by the European Commission under Horizon 2020 research and innovation programme – as part of the Next-Lab project (Grant Agreement Number No 731685).