Intelligent Collaborative Assessment for Cyberspace eLearning Environments

As the demand for more effective and efficient eLearning assessment systems continues to rise, there is a growing need for innovative approaches. This paper introduces the Intelligent Collaborative Assessment Framework (ICAF), which is a novel ontology-based framework that integrates Artificial Intelligence (AI) and collaborative tools to enhance assessment activities in cyberspace eLearning environments. Our research approach involved developing a specific ontology to capture essential concepts related to collaborative eLearning assessment, guiding the creation of the ICAF. The architecture of the ICAF consists of interconnected components that work in synergy to support assessment activities in cyberspace eLearning environments. One of its key features is the integration of collaborative learning techniques, which fosters a more engaging and effective learning experience. Additionally, the framework incorporates learning analytics and machine learning algorithms to analyze group learning patterns and deliver precise and valuable feedback. By presenting the viability and potential benefits of the ICAF, we demonstrate how the ICAF has the potential to significantly enhance assessment practices and facilitate collaborative learning in cyberspace eLearning environments.