Simulations and Virtual Reality experiences
Simulations and Virtual Reality experiences are very effective training tools for any application since real learning requires some failure: faithfully simulating work-specific tasks or social interactions gives learners the opportunity to train in a safe environment and fail without fear.
Virtual Reality, in particular, may change sales productivity and technical knowledge dramatically. VR allows students and employees to learn new skills in a safe environment, immersed in computer-generated worlds where they can undergo a real case scenario in an artificial environment controlled by Artificial Intelligence.
DTales has already experimented with immersive training through a 360° 4K Computer Graphics video for VR headsets, such as Oculus Go and Pico Neo, and prototyped a VR Soft Skills Simulator leveraging A.I. and machine learning.
The VR Soft Skills Simulator tests the user’s ability to relate to a 3D animated avatar powered by artificial intelligence (AI) and surrounded by a realistic virtual environment.
In the sim’s basic version, the AI is based on a predefined decision tree interacting with the learner’s dialogue choices. In the advanced version, the AI is based on a machine learning algorithm recognising the learner’s intent through natural language (via Language Understanding and Microsoft Bot Framework).
This is a valuable training tool to assess and/or develop such soft skills as communication, problem solving, decision making, handling objections or selling ceremony. Last but not least, it can help you train and improve observational skills and context analysis relating to potential customers/clients and thus the ability to collect useful information in the storymaking process for selling.
▪ Immersive simulation on VR headsets
▪ Train in a virtual environment and learn how to tackle real problems
▪ Extensive customisation options: the simulator can be adapted to different training goals and relationship contexts (sale, negotiation, customer support, conflict resolution…)
▪ Basic AI (decision tree) or advanced AI (machine learning and natural language recognition)
▪ LMS/LRS integration via APIs to track and analyse the simulation results