16 September 2022 | 13:00 - 13:30 | English | Student Clustering Process and Teacher Learning Advisory Analysis of Problem Posing as Sentence Integration in Arithmetic Word Problem From Monsakun Digital Learning Media
In recent years, with the increase of online learning platform, obtaining learning behaviour data from students,are becoming easy. However, analyzing the data to extract meaningful information remains challenging due to the data volume and complexity. Here, we apply Self-organizing Maps (SOM) to visualize the learning characteristics of many elementary students over many online assignments in mathematics class. Our primary objective is to give intuitive understanding for the teachers regarding the studentsâ€™ performance that subsequently allows the teachers to generate meaningful advices. Here, SOM generates a two-dimensional map that preserved the topological order of high-dimensional learning characteristics data, in which students with similar learning characteristics are located close to each other, while students with significantly different characteristics are distanced from each other similarities in student learning.