About

Effecetive social interaction is a critical human skill. To train social skills, there has been a rapid growth in narrative-based simulations that allow learners to role-play social interactions with virtual characters, and, in the process, ideally learn social skills necessary to deal with socially complex situations in real-life.

Although interactive narrative systems represent a major advancement in training, their designs often do not provide learners with exibility to replay scenarios with suffcient variety in choices to support learning and achievement of proffciency. Attempts to create more generative experiences face various challenges. First, the combinatorial explosion of alternative narrative paths poses an overwhelming challenge to create content for all the paths, especially if there are long narrative arcs. Second, current narrative systems are often brittle and constrained in terms of their generativity and exibility to adapt to the interaction.

Additionally, training systems are often designed around exercising specific skills in specific situations. However, it is also important for social skill training to teach skills more broadly. Fundamental to effective human social interaction is the human skill to have and use beliefs about the mental processes and states of others, commonly called Theory of Mind (ToM). ToM skills are predictive of social cooperation and collective intelligence as well as being implicated in a range of other social interaction constructs, e.g., cognitive empathy and shared mental models.Although children develop ToM at an early age, adults often fail to employ it. On the other hand, people engaging in ToM across multiple situations, including actors, have improved ToM skills.

Our goal is to develop generative social training narrative systems that support replay as well as embed ToM training. Achieving this requires: (1) a new generative model for conceptualizing narrative/role-play experiences, (2) new methods to facilitate extensive content creation for those experiences and (3) an approach that embeds ToM training in the experience to support better learning outcomes.

Approach

Project Overview

Fig.1 The AA Social Skill Training System

Our approach begins with a paradigm shift that re-conceptualizes social skill simulation as rehearsing and improvising roles instead of performing a role. We have adapted Stanislavsky's Active Analysis (AA) rehearsal technique as the design basis for social simulation training. AA was developed to help theater actors rehearse a script or text. The overall script is divided into key events (i.e., short scenes) that actors rehearse and improvise under a director's guidance. AA has two attributes especially relevant to social skills training. First, AA is designed to foster an actor's conceptualization of the beliefs, motivations and behavior of their own as well as other actors, and thus is developed to engender ToM reasoning. Second, by adopting AA to simulation based social skills training, the emphasis shifts to developing short scenes that allow variability and re-playability. Decomposition into short rehearsal scenes helps: (a) break the combinatorial explosion that exacerbates content creation for long narrative arcs, (b) support users replaying scenes, possibly in different roles with different virtual actors, and (c) users to directly experience in subsequent scenes the larger social consequences of behaviors.

AA provides a basis for experience design that uses ToM constructs and enables crowd sourcing to generate content for rich, coherent interactive experiences. Several researchers have proposed crowd sourcing techniques for narrative creation. The work presented here differs in that we focus on an iterative crowd sourcing method designed to create content for crafting a space of rich social interactions in which players explore a wide range of social gambits, from ethical persuasion and personal appeals to even deception; the content is created through the crowd using carefully designed tasks and interfaces that use AA and ToM as theoretical foundation.

Result

We collected 108 stories using the same AA interface. The average length of a story was 6 lines. The stories collected show an impressive range in complexity, richness and variety in characters' actions.

  • Deception :
    Anne dresses up as a postwoman.
    Charlie replies that Bob is not home.
    Anne informs Charlie that Bob must sign to acknowledge delivery.
    Charlie informs Anne that this is simply not possible.
    Anne begins to cry and says her job is on the line.
    Charlie finally relents and let her in.
  • Distraction :
    Anne sets fire to a nearby bin.
    Charlie looks at the fire.
    Charlie goes towards the fire and calls the police.
    Anne runs towards the door.
    Anne enters the place.
  • Threatens :
    Anne tells Charlie she is the best reporter in the country.
    Charlie ignores Anne.
    Anne shows Charlie her badge.
    Charlie tells Anne to leave.
    Anne threatens to write a story about Charlie.
    Charlie tells Anne to do it.
  • Others :
    Anne flirts with Charlie.
    Charlie tries to ignore Anne.
    Anne compliments Charlie a lot.
    Charlie begins to flirt with Anne.
    Anne tells Charlie that she just needs a few teeny minutes with Bob.
    Charlie becomes worried and tells her to leave

Publication

Acknowledgment

Funding for this research was provided by the National Science Foundation Cyber-Human Systems under Grant No. 1526275.