Perspectives on Students' Online Learning During the COVID-19 Pandemic (Poster 3)

• In Event: AERA Virtual Poster Session 5
  In Poster Session: Understanding Virtual Cognitive Development and Digital Identity in Equitable Teaching and Learning Spaces

Abstract

The present study explored the variables contributing to student satisfaction with online teaching and learning effectiveness. Data were collected through an online survey. Python with Scikit-Learn was used for data analysis to implement regression functions and classify the potential data. The results of the study defined effective online teaching during the COVID-19 pandemic. In combination, eight criteria contributed to the definition: motivating students to accomplish, communicating effectively, meeting students' needs, providing access to a wide range of content, providing a well-organized course structure, providing numerous sources, providing explanatory feedback, and facilitating meaningful discussions. The results of the study are beneficial for the organization to understand what kind of factors contribute to student satisfaction concerning online transition during the COVID-19 pandemic.

Authors

• Burhan Ozfidan, Florida Gulf Coast University

• Lynn M. Burlbaw, Texas A&M University - College Station