Co-designing instruction in virtual learning environments using AI

Abstract

The literature was explored to determine how artificial intelligence (AI) systems and algorithms are currently being used in the co-design of learning within virtual learning environments. Through the analysis of literature, the study aims to retrieve multiple methods of AI assistance to ease or uplift the educator’s role in online learning design. The study determined a variety of themes that determine methods of AI use in online instruction, such as prediction, providing feedback, adaptive learning, and providing visualization of student data on learning management systems (LMS). The study also determined the importance of a repository of various student data input in AI algorithms, and the collaboration of educators and experts in the process of using AI systems. The key implications suggest the importance of bridging feedback immediacy and formative approaches to improving student performance in online environments. Furthermore, the study also determines the changing roles of stakeholders in the education process. Finally, it also suggests the potential to create a multifaceted AI system and an effective LMS that supports such features.