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Finding the Truth: Interview and Interrogation Training Simulations
 

Finding the Truth: Interview and Interrogation Training Simulations

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Presentation given at the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC)2011 under the Hidden in Plain Sight:

Presentation given at the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC)2011 under the Hidden in Plain Sight:
Training Perceptual Skills session.

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  • In regard to interrogation, agencies today rely upon a variety of investigative techniques and tools to assist criminal investigators in identifying those persons attempting to deceive them. Skilled investigators develop deception indicators during repeated interrogations. The skills required to identify these deception indictors range from verbal communication to non-verbal cues to assist investigators in their discovery of the truth, the ultimate goal of any criminal investigation. This process is time consuming and can only be accomplished through hands-on interrogation technique application with known suspects of crimes committed. Government agencies are beginning to develop tactics, techniques, and procedures (TTPs) to assist them in identifying deception indicators, especially for suspects of serious crimes against persons.
  • A key implication of this audience upon system design was that the majority of learners would be considered Millennial learners (1982-2002) who grew up with electronic media from television to Ataris. Many studies have shown that for Millennial learners the predominant training question to answer is “how do we do it” (Coomes and DeBard, 2004). Learners in this group need to achieve, have a relatively short attention span, are used to multitasking, prefer to have a structure enforced and to tend to have high regard for objective testing. Instructional design considerations for both systems were selected in order to support the following Millennial needs as described by Svinicki (1999): 1. Provide reinforcement for activities you wish to encourage such as praise and positive feedback. 2. Emphasize internal reinforcement and motivation. 3. Set challenging yet attainable goals for learning, and provide feedback on progress.
  • Images from PPT clip art. Borg, J. (2009). Body Language: 7 Easy Lessons to Master the Silent Language. Upper Saddle River, New Jersey: Pearson Education Press.
  • Let’s address the six characteristics of game and simulation design as described by Appelman and Wilson in their 2005 book: challenges, models, control, manipulation, authenticity, and consequences . Appelman, R., & Wilson, J. (2005). Games and simulations for training: From group activities to reality. In J. Pershing (Ed.), Handbook of human performance technology. San Francisco: Pfeiffer.
  • To be read verbatim, with the exception of Proxemics and Attention to Child’s needs which will require a bit of extra explanation. -Proxemics is the study of the cultural, behavioral, and sociological aspects of spatial distances between individuals. - Attention to child’s needs in the interview system is very important and tests the learner’s “Emotional Intelligence.”
  • Proof-of-concept simulation dealing with interview of child abuse victims Applicable to both military and civilian applications. Avatars should provide motion and appearance to project indicators of abuse. Learners should be provided feedback on interviews after completion.
  • Overview As the learner, you take on the role of investigator investigating a report of sexual abuse of a child at the hands of an adult caretaker while her parents were deployed at a military base in Belgium. The alleged victim, Ms. Cynthia Baker, is the subject of your interview. As investigator, it is your mission to ask Cynthia the most appropriate line of questioning in order to gain evidence for a conviction of the caretaker while taking care to maintain rapport with her through three (3) acts. Failure to do so will lead to termination of the interview and the inability to gather needed evidence for a conviction. Physical profile Cynthia has been designed based upon a child who was a victim of a real child abuse case. We were provided with transcripts and videos of an investigator interview with the child which served as a guide for Cynthia's physical characteristics and as a basis for the story of the simulation. Cynthia possesses the typical characteristics of a 6 year old female. Steps were taken to change some aspects of Cynthia’s appearance in order to provide a character that would be interpreted as a member of any culture. These steps were taken to ensure that learners would not execute the training under any pretense, bias or assumptions based upon cultural differences.
  • Playroom environment The interview room environment was designed around a composite of real-world child interview rooms. The room contains a careful balance of seating arrangements, one-way glass observation point and opportunities for the child to play, if desired. This arrangement allows for several seating possibilities for the learner relative to Cynthia’s location and to provide an environment that is inviting for children. For much of the simulation the learner is seated near Cynthia, with some exceptions.
  • Challenge: Communicate emotional state using body language To address the goals of the simulation we had to find a way to recreate the movement and emotional state of Cynthia as would be depicted in real-life. We also wanted to be able to reuse and combine the animations. And so, we started with a long list of animations that would support the simulation story line and then reduced them to a short list that was representative of the kinds of animations that would support the instructional objectives of the simulation. Body animations designed across two layers The list was narrowed to 20 animations that would run across two layers. One layer would provide an idle or base animation and the other would provide the capability to blend in an emotive animation. This arrangement allowed for many combinations of emotional state while minimizing the animation task.
  • Challenge: Attempt to accurately portray facial expression We had a challenge in portraying the facial expression for a couple reasons. We typically model adults in our simulations, and so modeling a child was bit different. We also wanted to have access to a system that would allow us to show the range of and detail of emotion that Cynthia possessed while meeting the realism expectations for those expressions when presented to learner/investigators. Facial animations designed across four layers We had decided at that time to create an animation system in which would provide rich expression. The system plays out over four layers including an idle or base layer, blink layer, lip-sync layer and an emotive layer. By blending animations across the four layers our model was capable of many emotional states that could be called upon when needed in our scripts without having to produce highly customized animations. In short, it allowed a great deal of reuse and realism in the model with less modeling . Facial Action Coding System We also decided to continue to use the work of Dr. Paul Ekman’s Facial Action Coding System (FACS) in creating the facial expressions. FACS is a taxonomy of human facial expression. In particular, we ensured that the animations would match with Ekman’s FAC Action Unit (AU) combinations. When combined, these units represent in varying degrees the emotional state of the expression maker. Therefore, we built our modular, multi-layer approach using AU combinations that show anger, fear, happiness, et al.
  • First question deals with seating arrangements relative to Cynthia When the learner enters the interview room they are provided with an opportunity to demonstrate their Proxemics competency. Proxemics deal with cultural, behavioral, and sociological aspects of spatial distances between individuals. In this case, the way that the learner physically positions their avatar relative to Cynthia will determine her initial reaction towards your presence. The learner has three options including sitting in the adult chair across from and above Cynthia, sitting on the couch across the room or sitting in the child’s chair slightly back and aside of her. By sitting in the child’s chair slightly back and aside of Cynthia, she has the best reaction towards you. The seated across-above position projects dominance over by the child by a stranger and the couch seating arrangement places the Jamie too far from the child to begin building rapport. Experimented with the Xbox 360 Kinect controller to provide Proxemics We had success in experimenting with the Xbox 360 Kinect controller to provide Proxemics support. We used two kits including the OpenNI or Open Natural Interaction framework and the Omek gesture recognition technology and were successfully able to make them work using our simulation platform. However, due to the scope of the prototype we were not able to formally integrate the controller as a formal game mechanic.
  • Paying close attention to Cynthia’s needs is critical to completing the simulation. Talking at the child’s level First, use of age-appropriate dialogue is critical. If Cynthia cannot understand the questions that the investigator is asking then the investigator will not be able to obtain the evidence needed to level charges against the suspect. Decision points and voice acting for the simulation was designed to provide different levels of dialogue. Sitting at the child’s level Child subjects can easily have their attention diverted or may want to disconnect from the interview by playing. A situation is presented where Cynthia has retreated under a table. In this case the right thing to do is to let the Cynthia play and ask permission to join her on the floor at her level to continue your interview. Paying attention to the child’s special needs Cynthia enjoys coloring and spends a great deal of time doing so during the simulation. It is comforting and familiar to her and is a tool that can be used by the investigator to gather evidence by asking Cynthia to draw pictures that help activate her memories of the time in question. In addition, when Cynthia is very upset she will ask for her mother who is in the waiting room. If she is denied access to her mother then she will decompensate and the simulation will terminate.
  • To be read verbatim with the exception of micro expressions and lifecycle note which require more explanation. Micro expression A micro expression is a brief, involuntary facial expression (1/25 – 1/15 of a second) shown on the face of humans according to emotions experienced (Ekman, 2001). We will talk more about this later. Lifecycle impacts/Building on the back of the interrogation system The integration effort for both the interview and interrogation system took 3 months. The interrogation system integration effort began a month after the interview system integration effort had begun. Therefore, we were able to leverage many assets and lessons learned from the interview system effort that allowed us to produce better quality visuals, greater volume of animations and more functionality in the same amount of time. I will discuss these throughout.
  • Proof-of-concept simulation dealing with interrogation of sexual assault suspects. Develop scenarios that can be manipulated to provide interrogation exercises.
  • Overview As the learner, you take on the role of investigator investigating a report of sexual assault PFC Melissa Green during a promotion party in her barracks. The subject of the interview is Sgt. Mike Hagan. Mike is a young, first time offender who requires different handling by investigators then that of a seasoned criminal which plays into the decisions that the interviewer makes during the course of the investigation. The simulation is broken into three (3) acts. The first act is used to “norm” or develop a baseline of the suspect’s behavior and to build rapport. The baseline behavior is then used as a gauge to determine if Mike’s responses later in the interrogation are typical or atypical relative to the baseline. Miroexpressions are also presented in the first act. We will discuss these more later. Acts 2 and 3 deal with confronting Mike with the crime and obtaining a confession. Physical profile *Same as interrogation system, but we were able to create a more detailed model as many of the animation tasks to communicate body language had been completed with the Cynthia character. The demographic for Mike was determined through training materials provided to us. These materials also served as the basis for the story of the simulation.
  • Interrogation room environment The interrogation room environment has been designed to place as little obstruction between the interrogator and suspect as possible. This setup allows the investigator to control Proxemics. If the suspect needs to be consoled then it is easy for the interrogator to rollup in his chair to provide comfort or to move close by to show the suspect that there is no where left to hide. Another aspect of the environment is that there be no items close by that may be used as a weapon against the interrogator.
  • Challenge: Communicate emotional state using body language *Same as interview system but, we were able to leverage the animations made for Cynthia for Mike in order to have a greater range of emotion. To address the goals of the simulation we had to find a way to recreate the movement and emotional state of Mike as would be depicted in real-life. We also wanted to be able to reuse and combine the animations. And so, we started with a long list of animations that would support the simulation story line and then reduced them to a short list that was representative of the kinds of animations that would support the instructional objectives of the simulation. Body animations designed across two layers (Same as interview system) The list was narrowed to 35 animations that would run across two layers. One layer would provide an idle or base animation and the other would provide the capability to blend in an emotive animation. This arrangement allowed for many combinations of emotional state while minimizing the animation task.
  • Challenge: Attempt to accurately portray facial expression *Same as interview system but, we were able to leverage the animations made for Cynthia for Mike in order to have a greater range of emotion. The challenge of accurate portrayal of facial expression was the same as the interrogation system. However, I want you to take notice of the word “voluntary” as there is a difference between voluntary facial expression and involuntary expressions or micro-expressions. Facial animations designed across four layers *Same as interview system We had decided at that time to create an animation system in which would provide rich expression. The system plays out over four layers including an idle or base layer, blink layer, lip-sync layer and an emotive layer. By blending animations across the four layers our model was capable of many emotional states that could be called upon when needed in our scripts without having to produce highly customized animations. In short, it allowed a great deal of reuse and realism in the model with less modeling . Facial Action Coding System *Same as interview system We also decided to continue to use the work of Dr. Paul Ekman’s Facial Action Coding System (FACS) in creating the facial expressions. FACS is a taxonomy of human facial expression. In particular, we ensured that the animations would match with Ekman’s FAC Action Unit (AU) combinations. When combined, these units represent in varying degrees the emotional state of the expression maker. Therefore, we built our modular, multi-layer approach using AU combinations that show anger, fear, happiness, et al.
  • Challenge: Can the architecture handle extremely fast animation transitions? Micro expressions were a key challenge. A micro expression is a brief, involuntary facial expression (1/25 – 1/15 of a second) shown on the face of humans according to emotions experienced (Ekman, 2001). Because they are involuntary they can betray the subject’s façade, showing their true emotions. These expressions occur so quickly that we needed to ensure that a) the software was capable of producing an animation that plays within .25 seconds and that b) the system requirements be sufficient such that no frames were skipped thus missing the ME frame. We were successful in the end of accurately portraying the MEs. Our development pipeline was updated to play animations that lasted a fraction of a section and the client systems that the tools were to be deployed to were sufficient to not drop the ME animation frames.
  • Challenge: How to integrate a micro expression mini-game into the simulation? We needed to find a way to allow the learner to detect MEs. We had reviewed a video-based tool developed for this purpose. The tool showed a close up of a face which would then flash an ME. The learner would then attempt to identify which expression had occurred. However, our simulation would be a) seamlessly integrating MEs as part of a fluid interrogation process and b) would need to be integrated in such a way that the detection interaction would be highly usable and not distract from the overall interrogation. Not a dexterity test and the ME detection button We discussed using a free-scrolling zoom capability to allow the learner to explore and zoom as needed, but then thought that this total control may end up causing problems for users who were not dexterous with their control. The solution was to zoom in automatically when a ME may occur and allow the user to press a detection button if they believed that they had observed one. This approach removed usability obstacles and seamlessly integrated ME observance. Time frame and false positives The time between when the button is shown and when it disappears marks the time frame between which an ME may occur. False positive opportunities were created as well.
  • When an interviewer questions a suspect their willingness to answer truthfully may be affected by the suspect’s disposition towards the interviewer and may do so over a period of time. Similarly, suspects with different personalities may respond differently to the same questions asked in the same manner by the same person. These are interesting deltas that can significantly affect the outcome of an interview. As a game mechanic, these deltas provide significant replay and difficultly level game mechanics. In short, the avatar’s personality can be changed to account for different learner approaches to questioning. For example, we could set the subject to “Angry.” While angry he would not answer your questions with civility and may request a lawyer unless the learner is able to recover rapport. The chart shown on the screen shows how a first-time offender’s disposition may differ from that of a seasoned criminal. In this case questioning a first time offender in a civil manner would gain the learner better responses where as doing the same with a seasoned criminal may get you no where. We had success in integrating this game mechanic into the first act, however ran out of time to implement it throughout the rest of the simulation and therefore backed the whole subsystem out. However, we believe that it holds great promise for future implementation.
  • Overview of event sequences As in real life, the choices we make today help to shape many possible future outcomes tomorrow. The simulation employs an event sequence capable of simulating outcomes that mirror real-life events and outcomes. Our event sequencing engine has been designed to support linear, branching, recursive and any-order sequences. These are similar in concept to SCORM sequencing, but are not directly compatible at this point. The MPHNP simulation in particular takes advantage of the Linear and Any Order models. Linear Linear sequencing is the sequencing of events from start to end with no opportunity for deviation. Engineers and Program Managers may recognize this as the “waterfall” model. This is typically reserved for simple sequence complexity or low budget simulation. Branching Branching sequencing allows opportunity for deviation from the sequence trunk. These are useful for placing learners within different branches of events based upon the decisions they have made in the simulation giving the learners “control” of outcomes. Developers must be careful with branching as the event sequences get wider they also become more complex, longer and, therefore, expensive. Recursive Recursive sequencing can be thought of as reverse-branching to previously experienced events. This is useful for when the learner requires multiple repetitions of a task for practice or remediation. Exercise developers must be careful to ensure that there is some exit condition or risk having a never ending loop of the same set of events. Any Order Any order sequencing allows the user to experience a number of events from a discreet group in any order. After completing the group of events the learner is allowed to move on. In the MPHNP simulation this kind of sequencing is useful for letting learners explore aspects of the host nation police station in the order of their preference. Flow As previously mentioned, Flow helps to organize our consciousness for the task at hand. How do you know when you are experiencing flow? It varies, but many cite the rapid passing of time, forgetting of one’s self and the ability to intensely focus at the task at hand (Csikszentmihalyi, 1990). Athletes call it “The Zone.” It is important to engagement and retention. As game designers, we want to keep the leaner in an “optimal flow state”. Ideally, that state would run directly up the middle of the “Flow Channel” perfectly balanced between anxiety and boredom to move quickly to mastery. However, in real-life and in games learners typically come up against a challenge the first time with little skill and so the challenge can cause high anxiety at first. As we gain skill, anxiety is reduced as we are now able to overcome challenge. However, linger to long at the same challenge with the same skills and soon the learner will become bored and so new challenges must be introduced. Therefore, in reality the path through the flow channel looks more like a snake representing the rise and fall of challenge and skills (Schell, 2008). This keeps learners on the engaged and “on the edge of competency”.(Gee, 2008) Our event sequences allow us to support flow by throttling difficulty and acquisition of skill. Students quickly moving through branches that are easy for them may be branched to more difficult branches and vice-vice versa.
  • Our simulation is designed to train just-in-time analysis and decision making skills. Just-in-time Analysis and decision making Analysis is conducted based upon synthesis of information from environment, characters, communication and intelligence gathering. Analyzed information is then used to make decisions that immediately and significantly effect the outcome of the simulation story. Decision point user interface Three colored “event sequence paths” run through the simulations including a green path, yellow path and a red path. Each path began as a separate script or story with its own, unique subject animations, subject voiceover, events and outcomes. The green path is designed to move the learner through the optimum scenario in which the interviewer will have made all the right decisions in regard to interviewing the child subject. The yellow path is designed to move the learner into some tangles and will meet with some resistance from the subject. The red path is designed to be a halting path of strong resistance, even hostility towards the learner, from the subject. Choices take place primarily through dialogue with the subjects and through observation of their body language. In the image above the learner is given the choice of 2 to 3 weighted dialog options to choose from in a visual list. These choices advance the learner along the colored paths. The response option order is randomized each time the simulation is executed to deter cheating.
  • Overview of scoring Each decision in the simulation is weighted or given a color code representing a good, fair or bad choice, but can be any number of colors and weights. These choices are dictated by the educational requirements of the simulation. Three types of scoring are used including quantitative, qualitative and combined. The interview system uses both qualitative and quantitative scoring and the interrogation uses qualitative scoring only. Quantitative Using quantitative scoring the learners make choices that are individually scored and then averaged across objectives. Then, all of the objective scores are compiled into a final score for an after action review. This method enables a bridge to standardized test assessment methods and for storage into an LMS. (Not yet implemented in latest rewrite) Qualitative Using quantitative scoring the learners make choices and associated qualitative feedback is stored across objectives. Then, the qualitative information is compiled into an after action review. This method is useful for those who simply want practice and feedback and or for exercise developers who do not require or possess standardized test assessment thresholds . Combination Both quantitative and qualitative scoring occurs for a comprehensive assessment.
  • Challenge: how to simulate a meaningful confession/disclosure The investigator will have to proceed through the rapport building phase into the confession stage in the end of the simulation in order to achieve the confession. Along the way the learner will have to have made a majority of green and or yellow path decisions. There are several decisions in both simulations that will end the simulation immediately due to their severity. Others are provided so that learners may attempt to recover rapport and continue the simulation.
  • Challenge: How to provide the learner with an effective record of kinesics exhibited? Running log of all kinesics, dialogue, choices, decisions and mentor feedback All stage direction, body language, facial expression, decisions, responses and mentor feedback are provided to the learner through a Notebook game mechanic. The book can be toggled open and close as necessary and is constantly updated with the latest feedback from the system. Designed for learner reflection, performance review and memory/analysis aid This comprehensive level of detail is provided to users as just-in-time feedback regarding their performance and for review as there is much expression through body language and facial expression that may be missed for analysis and review.
  • After Action Review The review offers an opportunity for deep reflection of performance through a detailed walkthrough. The learner SEES the decision they made with a referential in-game image for activation they SEE remediating and reinforcing feedback on their performance and they SEE how it all relates to underlying objectives . Summary Panel The summary panel provides a list of objectives and the learner’s score against those objectives and a rollup of all scores into a cumulative score. Details Panel The details panel provides shows a referential screen shot, decision response, related objective and mentor feedback for each decision made in the simulation.
  • To be read verbatim.
  • To be read verbatim.
  • Questions? Thank you for your time?

Finding the Truth: Interview and Interrogation Training Simulations Finding the Truth: Interview and Interrogation Training Simulations Presentation Transcript

  • Finding the Truth: Interview and Interrogation Training Simulations Janet Mulkern Concurrent Technologies Corporation Ronald Punako, Jr. Concurrent Technologies Corporation
    • Welcome!
    • Instructional Systems Design
      • Intended Audience
      • Design Considerations
      • Commonalities of Instructional Design
    • Simulation – Visual and Interaction
      • Interview System
      • Interrogation System
    Topics
  • Our Purpose
    • Interview a Child Interrogate a Suspect
    • Creating interview and interrogation
    • Immersive Learning Simulations (ILS)
  • Intended Audience
    • The interview training system was designed as capstone experience.
    • The interrogation training system was designed for Special Agents with little or no interviewing or interrogating suspects of major crimes.
    • The audiences include mostly male individuals between 18-40 years of age.
  • Design Considerations
    • Predominant Millennial learners (1982-2002):
      • Predominant training question to answer is: “How do we do it?” (Coomes and DeBard, 2004)
      • The “Net Generation.”
    • Instructional strategies support the learner’s needs as described by Svinicki (1999):
      • Provide reinforcement for activities you wish to encourage such as praise and positive feedback.
      • Emphasize internal reinforcement and motivation.
      • Set challenging yet attainable goals for learning, and provide feedback on progress.
  • Kinesics
    • “ The study of nonlinguistic bodily movements”
      • Communication is 93% body language and paralinguistic cues (including pitch, volume and tone)
      • Words only provide 7% of the communication. (Borg, 2009)
  • Commonalities of Instructional Design
    • Challenges:
      • Recognition of behavioral indicators of abuse
      • Recognition of Kinesic indicators of truth or deception.
    • Models:
      • Scenarios were modeled after a session by an experienced investigator and expert instructor.
      • Correct answers are based on real-life experiences and consequences.
  • Commonalities of Instructional Design (Continued)
    • Controls:
      • System’s graphical user interfaces (GUIs) were designed to include a number of controls.
      • In the interrogation training system an additional control was added where the learner can acquire points to increase the motivation to “win” by obtaining the most points.
    • Manipulation:
      • The learner controls the interview and interrogation by asking the right question, reading the non-verbal indicators correctly and then asking the next question correctly.
      • Depending on how poorly the learner asks the question, the consequences become more severe.
  • Commonalities of Instructional Design (Continued)
    • Authenticity:
      • Written from case material
      • Reviewed by the internal SMEs and the client for authenticity of content and interaction.
    • Consequences:
      • If the learner does not pay attention to and adapt their line of questioning to the suspects non-verbal signs, the subject avatar is designed to shut down the interview and ask for a lawyer.
      • To the learner, the course consequences are passing or failing.
  • Interview System
    • Goals
    • Subject
    • Environment
    • Simulation of Body Language
    • Simulation of Facial Expression
    • Proxemics
    • Attention to Child’s Needs
  • Interview ILS Goals
    • Develop a proof-of-concept simulation to train investigators to conduct interviews of child abuse victims.
    • Develop a training scenario to benefit interagency organizations for both military and civilian applications.
    • Provide a virtual interactive training module avatar system, with all necessary motion and appearance to project the behavioral indicators of abuse.
    • Enable investigators to practice interviewing child abuse victims and to receive feedback after the training has reached completion.
  • Subject: Cynthia Baker
    • Physical profile
    • 6 years old
    • Petite
    • Brown hair
    • Brown eyes
  • Environment: Child’s Interview Room
    • Playroom environment
    • Sofa, adult chairs, child chairs
    • Toys
    • Posters
    • One way glass
  • Simulation of Body Language Shrugging off Coloring Casual dialogue Closing off/hiding
    • Challenge: Communicate
    • emotional state using body
    • language
    • Designed 20 animations to communicate emotional state
    • Body animations designed to be blended across 2 layers including idle and emotive
  • Simulation of Facial Expression Happy
    • Challenge: Attempt to accurately portray facial expression
    • Designed for sadness, fear, anger, indignant, disgust, happiness, confusion and shame across 4 layers including: blink, idle, lip-sync and emotive
    • Selected expressions modeled after Facial Action Coding System action unit combinations.
    Angry
  • Proxemics
    • First question deals with seating arrangements relative to Cynthia
    • Experimented with the Xbox 360 Kinect controller to provide proxemics
  • Attention to Cynthia’s Needs
    • Challenge: Simulating the
    • special needs of a child
    • interviewee
    • Talking at the child’s level
    • Sitting at the child’s level
    • Paying attention to the child's special needs (requests for mother, playing and coloring)
    Playing under the table
  • Interrogation System
    • Subject
    • Environment
    • Simulation of Body Language
    • Simulation of Voluntary Facial Expression
    • Simulation of Micro Expression
    • Detection of Micro Expression
    • Continuation of Disposition/Personality
  • Interrogation ILS Goals
    • Develop a proof-of-concept simulation to train investigators to conduct interrogation of criminals suspected of sexual assault.
    • Develop scenarios that can be manipulated to provide challenging interrogation exercises that are real and relevant to the current threat of perpetrators of serious crimes against persons.
  • Subject: Sergeant Mike Hagan
    • Physical profile
    • 30 years old
    • 71 inches
    • 156 lbs
    • Brown hair
    • Brown eyes
    • Criminal record
    • First time offender
  • Environment: Interrogation Room
    • Minimalist design
    • One table
    • Security Camera
    • Two chairs
  • Simulation of Body Language Shrugging off Stop pressuring me Defensive rebuke Closing off/hiding
    • Challenge: Communicate
    • emotional state using body
    • language
    • Designed 35 animations to communicate emotional state
    • Body animations designed to be blended across 2 layers including idle and emotive
  • Simulation of Voluntary Facial Expression Happy Angry Worried Disgusted
    • Challenge: Attempt to accurately
    • portray facial expression with a
    • high-fidelity model.
    • Designed for sadness, fear, anger, contempt, disgust, happiness and surprise across 4 layers including: blink, idle, lip-sync and emotive
    • Selected expressions modeled after Facial Action Coding System action unit combinations.
  • Simulation of Micro Expressions
    • Challenge: Can the architecture
    • handle extremely fast animation
    • transitions and blending?
    • Designed for sadness, fear, anger, contempt, disgust, happiness and surprise
    • Achieved required 1/25 second micro expression duration.
    Worried micro expression
  • Detection of Micro Expressions
    • Challenge: How to integrate a
    • micro expression mini-game into
    • the simulation?
    • A possible micro expression occurs while a detect button is shown
    • Not a test of dexterity
    • False-positives possible .
    Worried micro expression
  • Continuation of Disposition/Personality Disposition Modifiers (First time offender) Red = +1 Yellow = +0 Green = -1 Disposition Modifiers (Repeat offender) Red = -1 Yellow = +0 Green = +1 Disposition Threshold Disposition Visual Output 5+ Angry/ Uncooperative 2-4 Upset 0-1 Idle/ Cooperative
  • Common Design Elements: Decision Sequencing
    • Linear - sequencing of events with no opportunity for deviation from sequence trunk.
    • Branching - sequencing of events that allows deviation from the sequence trunk.
    • Recursive – revisit previous events.
    • Any order – events presented in a discreet group in any order.
  • Common Design Elements: Decision Making
    • Select a response which would help assess the child’s episodic memory level.
    • A. You were telling me about your Christmas. (Green = Best)
    • I’ll bet Christmas day was fun, right? (Yellow = Average)
    • Specifically, where were you and what did you do Christmas day. (Red = Poor)
  • Common Design Elements: Performance Scoring Learner makes a choice Score is averaged by objective and recoded Final score is averaged across objective scores   Objective 1: 50% Objective 2: 100% …   Final: 75%
    • 1. Choice A
    • Choice B
    • Choice C
    Learner makes a choice Feedback is recorded by objective. Feedback is provided to learner   Objective 1: Good Job! …   Good Job! You chose choice A. Choice A was best because…
    • 1. Choice A
    • Choice B
    • Choice C
    Quantitative Qualitative
  • Common Design Elements: Confession or Disclosure
    • Challenge: How to
    • simulate a meaningful
    • confession/disclosure?
    • Culminating point in final act
    • Reached through majority green and yellow path decisions
    • Must avoid terminal red path decisions
  • Common Design Elements: Notebook
    • Challenge: How to provide the learner with an effective record of kinesics exhibited?
    • Running log of all kinesics, dialogue, choices, decisions and mentor feedback
    • Designed for learner reflection, performance review and memory/analysis aid
  • Common Design Elements: After Action Review
    • Summary Panel
    • Rollup of objectives
    • Scored or un-scored against objective thresholds
    • Details Panel
    • For each decision displays screen shot, decision response, related objective and mentor feedback
  • Technical and Integration Details
    • Work with internal and client SME to develop a script that details what content (objectives, voice over, feedback, remediation, interactivity, others) to integrate
    • Staff works to produce content
    • Custom development pipeline built on the Unity Game Development Tool supports integration of content
    • Simulations currently deployed to Web, PC, Mac, iPad
  • Next Steps
    • System to be evaluated for a Certificate of Networthiness
    • Pursuing evaluation by learners at Fort Leonard Wood, MO
    • Advanced feature integration
      • Full implementation of continuation of disposition/personality
      • Implementation of motion capture for Proxemics
      • Photo-realistic body language and facial expression
      • Improve development pipeline
    • Evaluate potential for application in broader industry.
  • Questions
    • Questions ?