Framework for Activity Development in Remote Laboratories IEEE 1876–2019 Standard Based

Recent publications show that there is a positive impact of remote laboratories in engineering education, based on the perception of students and teachers, and based on student grades in some cases. The IEEE 1876–2019 standard outlines requirements for remote laboratories to qualify as networked intelligent learning objects. However, there is an absence in the literature of pedagogical guidelines aimed at defining activities within remote laboratories that align with the IEEE 1876–2019 standard and utilize learning analytics techniques to enhance student performance. This work proposes a framework that supports the remote laboratory activity development aligned with IEEE 1876–2019 standard, while following Kolb's expe-riential learning cycle. Through a case study conducted in a digital systems laboratory, we demonstrate the application of this framework. Our proposed framework not only aims to enhance student performance through the utilization of learning analytics techniques but also offers adaptability for application in virtual laboratory settings. A pedagogical challenge lies in crafting activities and assessments that help skills development. Hence, the framework can be improved if aspects like attention, memory, cognitive load, and emotion are considered.