Virtual Laboratory (VLAB): Design, Implementation, and Scalable Deployment
The Virtual Laboratory (VLAB) is a desktop-based graphical user interface (GUI) application developed to support the delivery of a first-year undergraduate chemistry laboratory course in a virtual mode. The platform was implemented using Python with the PyQt GUI toolkit, and was designed to closely emulate essential aspects of on-site laboratory experiments while ensuring reliability, scalability, and ease of use.
VLAB provides an interactive interface through which students can perform experiments virtually. Animations, guided walkthroughs, and virtual simulations are employed to achieve a high degree of similarity with physical laboratory equipment and experimental procedures. From a teaching and instructional standpoint, the software incorporates features such as secure user access, experiment-specific workflows, and a submission portal for systematic collection of experimental data.
For each experiment, experimental parameters are randomly assigned on a per-student basis using validated reference datasets. Student-submitted results are evaluated against individualized reference data, with predefined error bars used to automatically assess performance based on deviations within or beyond acceptable uncertainty limits. Data submission and evaluation are handled through web-enabled workflows, while the core experimental interface runs locally on the student’s computer.
The VLAB platform was successfully deployed for the 2021 admission batch, supporting over 1000 students, who conducted virtual experiments in three parallel slots with more than 300 students per slot. Beyond its role during online instruction, VLAB also serves as a supplementary learning and practice tool for laboratory preparation in the offline mode of study.
The development of VLAB was carried out over three semesters as part of two project-type courses and one first-degree thesis, and involved significant contributions from MSc students Utkarsh Kumar (2017B2A71008P), Abhishek Gaur (2017B2A21037P), and Akhilesh Parwal (2017B2AB1020P). The project provided the students with hands-on experience in scientific programming, GUI-based software development, and automated assessment workflows.
