Feedback Techniques in Computer-Based Simulation Training: A Survey

TL;DR

This survey reviews the current state of feedback techniques in computer-based simulation training, emphasizing types, presentation, and extraction methods to guide future development of effective feedback systems.

Contribution

It provides a comprehensive overview of feedback provision in CBST, highlighting gaps and proposing directions for future research and system design.

Findings

Feedback is crucial for skill improvement and decision making.

Current CBST systems lack standardized feedback extraction methods.

Effective feedback should mimic experienced tutor advice.

Abstract

Computer-based simulation training (CBST) is gaining popularity in a vast range of applications such as surgery, rehabilitation therapy, military applications, and driver/pilot training, as it offers a low-cost, easily-accessible and effective training environment. Typically, CBST systems comprise of two essential components: 1) a simulation environment that provides an immersive and interactive learning experience, and 2) a feedback intervention system that supports knowledge/skill acquisition and decision making. The simulation environment is created using technologies such as virtual or augmented reality, and this is an area which has gained much interest in recent years. The provision of automated feedback in CBST however, has not been investigated as much, and thus, is the focus of this paper. Feedback is an essential component in learning, and should be provided to the trainee during the training process in order to improve skills, to correct mistakes, and most importantly, to inspire reasoning and critical thinking. In CBST, feedback should be provided in a useful and timely manner, ideally in a way that mimics the advice of an experienced tutor. Here, we explore the provision of feedback in CBST from three perspectives: 1) types of feedback to be provided, 2) presentation modalities of feedback, and 3) methods for feedback extraction/learning. This review is aimed at providing insight into how feedback is extracted, organized, and delivered in current applications, to be used as a guide to the development of future feedback intervention systems in CBST applications.