An assistive system for transferring domain knowledge to novice officers
Instructional strategies in many operative fields, including law enforcement, have reached a high level of complexity due to dynamically changing task environments and the introduction of different technologies to help the users in their operational work. In the last decades, a transition has been observed from dedicated trainers to the adoption of automated technologies to support the trainees. This paradigm shift makes conferring precise knowledge to novice users a challenging problem, which becomes especially relevant when the user is dealing with large and complex datasets from which to extract relevant information. In this context, the ANITA project aims at providing law enforcement agencies (LEAs) with a set of automated tools and systems to boost the investigative work in the fight against illicit trafficking activities. Within this project, one of the functionalities that have been developed is the capability to provide adequate solutions to facilitate the transfer of the acquired knowledge among users, and consequently improve the time necessary to train novel users. In particular, based on a review of state-of-the-art literature and direct feedback from LEAs, we have developed an assistive system to aid in the knowledge transfer from expert to novice officers. This system is grounded on the most relevant instructional principles derived from cognitive and learning theories. The end result is a system that can dynamically deliver suggestions based on both previous successful actions from other users and on the current performance and states of the user. To validate it, we have implemented a knowledge graph exploration task, in which users can receive suggestions from the system. Here, we propose this novel knowledge transfer system by presenting the corresponding literature review together with the conceptualization of the architecture of the assistive system and the implementation of a validation task. With this work, we aim at facilitating the transfer of domain knowledge, which could have a significant impact on the training and education of law enforcement officials in and for the Digital Age.
