The Implementation of Precision Education for Learning Analytics

Abstract

This study is based on a novel conceptual framework, precision education, and takes a blended Python programming course as an example to explore how to implement precision education that includes diagnosis, prediction, prevention and treatment. Precision education follows the principles of personalized services for precision medicine. Its purpose is to strengthen the learning risk prediction and early intervention mentioned in emerging learning analytics through big data, artificial intelligence and other emerging technologies, thereby improving teacher teaching quality and student learning efficiency. This study is based on the design of the e-book learning dashboard, so that teachers can quickly understand students' learning status, and improve the e-book through students' feedback on the dashboard to achieve precision diagnosis. Next, this study uses machine learning algorithms to predict students' learning performance, and thus determine whether students are at-risk to achieve precision prediction. Finally, through the correspondence between reading strategy and reading sequence, and then clearly distinguish the types of students by grouping, and use it as a treatment target for precision treatment and prevention. It is hoped that this empirical study can be used as a case study for implementing precision education.

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