Adaptive Instructional System for Complex Equipment Trainings in the Post-covid Era: Breaking the Ice of Time-Consuming Tasks

Abstract

Complex equipment trainings frequently rely on in-person trainings to describe instrument parts and personalize explanations based on training objectives, prior knowledge, and cognitive abilities of trainees. In this study, we assess the main challenges of adapting intelligent instructional system by training centers with limited human and technological resources. We found that the preparation of the training material is the most time-consuming task. During the COVID-19 pandemic, many training centers were forced to remotely conduct their trainings, thus generating a massive amount of digital training content. Here, we explore this unique opportunity to recycle this training material to design an adaptive instructional system (AIS) for bioimaging training. In this paper, we discuss the functional features of AIS that facilitate autonomous training for trainees and instructors: progress bar, notification system, built-in teleconferencing, and chatting tools. To address a high level of customization of in-person trainings, we designed AIS trainings as module-based instructions that can be easily tailored to accommodate the objectives and needs of the trainees. We also demonstrate that modular design of the training material database accelerates allocation and preparation of training content for similar types of equipment. We set up a framework for implementing a recommendation system that would accommodate the training material to the trainee’s experience. Our study shows that over the short or medium term, the potential of AIS solution for equipment trainings significantly outweighs the most time-consuming tasks like preparation of the training material.