Abstract
Remote laboratories in the educational context are made possible by the integration of the latest advances in telecommunication technology, software architectures and educational standards support. Remote laboratories are important in education because they provide access to equipment that some institutions cannot afford to purchase or maintain, reduce the need for dedicated physical space for equipment and personnel to staff laboratories. But more than just fill the absence of a real physical laboratory, remote laboratories can improve the users experience through the use of enhanced adaptive interfaces that, when complemented with the use of educational standards like Tin can API, can provide information important in the educational context, for example, the mastery level of the student and the complexity of the experiment. Based on that information, the remote laboratory could take actions related to the controls of the experiment, for example, disabling or enabling part of the experiment controls. Using smart adaptive interfaces, the experiments can gradually increase their complexity, taking into account variables that are clearly identified as part of the learning processes, such as: difficulty level of the topic, students' knowledge, and course level among others.
This paper proposes a model and set of diagrams that define the integration of adaptive interfaces in remote laboratories for educational purposes.