Effects of Using World Indicators for Online ESD Learning

Abstract

As a pedagogical method to improve student recognition of Education for Sustainable Development (ESD) through scientific data reading, this study looked at the effects of learning in online academic discussions using data from global indicators. Students’ scholarly messages were coded and introduced into qualitative content analysis, sequential analysis, and social network analysis, which are emphasized, respectively, to investigate code co-occurrence, code sequence, and code distribution. In all, 307 messages appeared from 119 university students in the online community. The ESD competencies and collective intelligence (CI) are used as indicators for analyses. Qualitative content analysis, particularly addressing those sentences, proved that CI enhanced communication among students where they shared individual norms and values. Sequential analysis elucidated characteristics of discussion thread characteristics with CI, which induced further discussion with foresight views and questions. Social network analyses indicated students connected and showed the connection structure was meshed. Key student bridging messages were extracted. Whereas ESD competencies appeared effectively, the expansion of the current online environment must be regarded as including competency in participatory learning. After summarizing the effects of the online learning method in the Moodle forum environment, the method was proved to empower students to represent core competencies of ESD and to lead data-driven concept transformation.