Child Care and Early Education Research Connections

Skip to main content

Learning analytics to predict student achievement in online learning during Covid-19 mitigation

This study aims to make predictions of online learning during the COVID-19 mitigation period by using Analytic Learning Techniques. Learning is done using Moodle as the learning management system. The primary statistical technique used in this study is cluster analysis, which groups students in three different characteristics based on the activity components. The results of the study indicate that the activity components that support social presence are the determining components in predicting learning success. Another consequence is that the three clusters formed can be identified as high, medium, and low groups in progress with the identifier of activity components. Chatting, Forum, Choice, and Assignment are the practical activity components in this finding. The result of this study is too early to state that the e-learning is successful during COVID-19 mitigation. More information is still needed for further analysis. (author abstract)
Resource Type:
Reports & Papers

- You May Also Like

These resources share similarities with the current selection. They are found by comparing the topic, author, and resource type of the currently selected resource to the rest of the library’s publications.

Professionalizing the child care workforce: Teachers’ and leaders’ views of Louisiana’s Early Childhood Ancillary Certificate

Reports & Papersview

ECE Credential Competency Project

Reports & Papersview

Maintaining professional standards in early childhood teacher preparation: Evaluating adaptations to fieldwork-based experiences during COVID-19

Reports & Papersview