Using Learning Analytics to Improve Students’ Reading Skills: A case study in an American International School with EAL Students

Abstract

This paper shows how an American International School in Vietnam has been using data and Learning Analytics to learn about students learning from their assessment data and how to use these data to improve, among other areas, the reading skills of their mostly EAL student population. The source of data comes primarily from a Computer Adaptive Testing platform, commonly known as the MAP Growth test, which provides information about Math and Reading skills for each particular student. The data provided is transformed and presented to educational stakeholders through visualizations created in a specialized software in order to dig into the data and answer the pedagogical questions emerged from teachers and administrators. This process involves a new field know and Learning Analytics and Visual Data Mining in order to find new information not usually evident in school datasets. The results indicate that when teachers identify specific strengths and areas for improvement get into a reflective process that end up in actions plans for overall school and student learning improvement. In addition, learning analytics proves itself to be an effective way to understand what students learn and engage in actions to improve the conditions where learning happens.