Definition of a smart laboratory learning object compatible with online laboratory management systems

Abstract

The Virtual Learning Environment (VLE) or more specifically the Learning Management System (LMS) can report to an Online Laboratory Management System (OLMS) information about the student's progress in the class. Based on that information and teacher definition of parameters, the Smart Adapter module retrieves the laboratory activities and assessment content from the VLE and connects them with one or more online laboratory experiment stations to create the Smart Laboratory Learning Objects (SLLO). The SLLO components include class materials, lab activities, assessment information, student information, and information about access to the online laboratory experiments. These learning objects are managed by the OLMS. Additionally, the teacher can compose Smart Laboratory Learning Objects using a laboratory composer module in the OLMS. The Smart Laboratory Learning Objects (SLLO), has been defined based on the previous definition of the Laboratory-based Learning Object (LLO) and the one proposed in the Lab4CE. The proposed SLLO integrates the core components of the proposed architecture of the IEEE 1876-2019 Standard for Networked Smart Learning Objects for Online Laboratories. The proposed Smart Laboratory Learning Object (SLLO) is defined specifically for laboratory experiences. In this sense, different students will have access to different activities that, in some cases, can use the same laboratory experiments exhibiting different levels of complexity in their interactions and requiring different levels of knowledge for its operation. An example of this is a skilled student using a more challenging experiment and activities, while less skilled students will see a simpler version of the experiment with different activities that evaluate more basic concepts. This paper proposed the definition of the SLLO architecture that can be used as part of an online laboratory management system OLMS. An example of a SLLO implementation is presented to show the capabilities of this architecture.