Modelo conceitual para ambientes virtuais de ensino e aprendizagem com integração de técnicas de inteligência artificial

Abstract

The advancement of Virtual Learning Environments (VLEs) and the growing adoption of Artificial Intelligence (AI) techniques in education highlight challenges related to personalization, monitoring, and pedagogical support. Although the use of AI in these environments is expanding, there is a lack of conceptual models that systematically guide its pedagogical integration. This dissertation aimed to develop a conceptual model for VLEs with the incorporation of AI techniques, oriented toward supporting educational processes. Structured in a multipaper format, the research was conducted in three methodological stages: a systematic literature review, model development based on the Design Science Research approach, and qualitative validation with experts using the ValiQuali method. The resulting model is organized into four dimensions: personalization, engagement, monitoring, and performance analysis, each comprising processes and functionalities that support pedagogical mediation through AI. As a practical outcome, the research led to the development of the InteliEduca web platform, which provides an interactive representation of the proposed conceptual model. The application aims to enhance accessibility, understanding, and applicability of the model in real-world contexts, serving as a potential resource for teacher training, research, and educational innovation. The findings contribute theoretically, methodologically, and practically by proposing a structured framework for integrating AI into education, with potential for implementation in platforms such as AWS, Azure, and Google Cloud. Furthermore, the study points to future directions for research, including the practical construction of AI models associated with the proposed dimensions and their implementation in real educational environments.