ABSTRACT
This chapter focuses on the application of learning analytics to achieve assessment and improvement of the learning process and discusses how to achieve real-time monitoring, analysis, prediction, and feedback of the learning process through statistical analysis, sequence analysis, and machine learning based on the analysis of key learning behaviors and the development of learning engagement indicators. Based on the discussion of the concepts of learning engagement and behavioral engagement, this chapter shows and discusses how to assess substantive learning engagement, monitor learning status and progress, gain insight into learning paths and cognitive processes, predict learning performance, conduct automated assessments, and provide personalized assessment feedback based on students’ behavioral traces data of online learning based on four aspects: online learning engagement assessment, online learning process monitoring, learning prediction and alert, and personalized assessment and feedback, based on existing research examples and technical examples. The presentation shows and discusses how to assess substantive learning engagement, monitor learning status and progress, gain insight into learning paths and cognitive processes, predict learning performance, conduct automated evaluation, and provide personalized feedback based on students’ online learning traces data, thus promoting learning through assessment.
