Embed Size (px)
Citation preview
An Interactive Virtual Training (IVT) Simulation for Early CareerTeachers to Practice in 3D Classrooms with Student Avatars
A. Delamarrea,b/C. Bucheb/M. Polceanub/S. Lunna/G. Ruiza/S. Bolivara/E. Shernoffc/C. LisettiaaVirtual Interactive Social Agents Laboratory, FIU, USA
bLAB-STICC, ENIB, FrancecGraduate School of Applied and Professional Psychology, Rutgers University, USA
[email protected]; [email protected]; [email protected]; [email protected];[email protected]; [email protected]; [email protected]; [email protected]
Abstract
Interactive Virtual Training (IVT) is a web-based in-teractive simulation system created to help early ca-reer teachers working in high-poverty schools learn ef-fective classroom management skills. IVT simulatesdisruptive students’ behavior (aggressive, off-task, non-compliant), as defined in vignettes developed by peda-gogical experts on our team. These simulations enableearly career teachers to hone their classroom manage-ment skills before they start teaching in real classrooms.In the simulation, users will interact with thirty (30)realistic diverse virtual three-dimensional (3D) "prac-tice" students, which are situated in two (2) realisticvirtual 3D classrooms. We describe IVT: (1) require-ments and process mechanisms, (2) the IVT simula-tion of the vignettes depicting students’ behaviors, (3)3D virtual classrooms and characters, (4) website mainfunctionalities, and (5) contributions and challenges.
IntroductionLearning how to prevent and manage behavioral prob-lems is critical to improving student achievement, par-ticularly for struggling learners. This includes stu-dents growing up in high poverty communities, inaddition to students at risk for emotional and be-havioral disabilities (Oliver and Reschly 2010). Ef-fective prevention and management of disruptive be-haviors has been empirically linked to student suc-cess through its impact on effective instruction andmaximizing of learning opportunities (Creemers 1994;Crone and Teddlie 1995).
Early career teachers (ECT) with less than 3 to 5years of experience report that disruptive behaviors arestressful, given they have received limited training inthis area (Shernoff et al. 2011; 2016). Predictably, dis-ruptive behaviors are identified as one of the strongestdrivers of turnover (Ingersoll and Smith 2003; Shernoffet al. 2016). ECTs are often left to practice and improvethese skills in the classroom without support, and solelythrough a trial-and-error approach. Given the negativeimpact that disruptive behaviors can have on classroomclimate and interpersonal relationships, helping ECTs
Copyright c© 2015, Association for the Advancement of Ar-tificial Intelligence (www.aaai.org). All rights reserved.
improve these skills can have a significant impact onclassroom interactions and the facilitation of studentlearning.
Progress in three-dimensional (3D) computer graph-ics, visual displays, and auditory stimuli have made itpossible to develop virtual environments inhabited byrealistic human-like characters (Magnentat-Thalmanand Thalmann 2005). 3D virtual characters (alsoknown as virtual agents, virtual humans, or avatars)can simulate human behaviors and affective expressionsby adapting and responding to the behavior of their hu-man counterparts (Calvo et al. 2015). The effectivenessof serious games for professional training has alreadybeen shown in applications such as training safe drivers(Herviou and Maisel 2006). Presently some trainingsystems do simulate students in schools (Popovici etal. 2004) as well as teachers with the STAR Simula-tor (Dieker et al. 2007). However these studies do nottackle the ECT issues that we address and has somelimitations that we do satisfy.
Interactive Virtual Training (IVT) aims to acceler-ate ECTs’ skill acquisition by tackling ECTs’ main is-sues: ECTs are unprepared for the realities of teaching(Grossman and McDonald 2008), ECTs have few op-portunities to practice while receiving feedback abouttheir mistakes expertly tailored to them (Denton andHasbrouck 2009), and ECTs have few opportunities forreflecting about their skills and how to resolve prob-lems (Reigeluth and Carr-Chellman 2009). IVT is afour year development and innovation grant funded bythe US Department of Education.
IVT is an educational system in which ECTs can im-prove their classroom management skills by practicingin a realistic 3D virtual classroom. In IVT, ECTs areprovided with a large number of possible options in re-sponse to the actions of disruptive student avatars (e.g.praise or ignore student) which they can select. Theirchoice, dynamically determines the avatars’ next behav-ior: the classroom climate can, as a result, get worse orimprove based on the ECTs’ choice.
In this article, we describe (1) IVT requirementsand classroom vignettes developed in collaboration withproject education experts, (2) the IVT simulator archi-tecture controlling the interactive vignettes of students
Figure 1: Overview of the IVT system
behaviors and ECTs’ possible choices, (3) the creationof IVT 3D virtual classrooms with its avatars, (4) IVTwebsite main functionalities and visual prototype, and(5) contributions and challenges.
IVT Specifications and PhasesThe strength and novelty of IVT is that it addressessome of the limitations of existing virtual trainingmodel for teachers (Dieker et al. 2007). First, IVT pro-vides ECTs with learning experiences in which they areencouraged to practice, reflect, and problem solve byenabling ECTs to replay simulations of their IVT ses-sion, and to learn from their mistakes. Second, withits online access and low-technology requirements, IVTfacilitates ECTs practice and receiving automaticallygenerated explicit feedback about their skills which canbe advantageous in the resource-limited environmentsof high poverty schools. Third, IVT classrooms arepopulated with a realistic number of avatars, who be-have autonomously (rather than being controlled by ahuman) with, not only disruptive behaviors, but alsocompliant ones.
SpecificationsIVT is built on four main components:• Vignettes: Vignettes are descriptions of possible
classroom scenarios designed to reflect the real lifesituations that teachers experience, created by ourteam of pedagogical experts.
• Classrooms: To ensure the immersion of ECTsin our two IVT classrooms (one 1st grade, one 6th
grade), our 3D graphics focus on physical arrange-ment, quality, and realism.
• Characters: Each classroom is populated with 15avatars. Characters were designed to not only reflectappropriate ages (1stgraders and 6thgraders) but alsoto portray the racial and ethnic demographics typicalin high poverty schools.
• Website: ECTs will access the system using the IVTwebsite where they can play and replay simulations,enter comments and reflections, and view simulationresults.
PhasesIn order to achieve our objectives, IVT training is di-vided into two phases:
• Phase 1 IVT Practice: During the practice phase,skills of the ECT, like monitoring and redirecting ofdisruptive behaviors are trained and tested. ECTsare invited to practice with a trial-and-error ap-proach. Feedback is provided at the end of the sim-ulation by revealing the type of strategy a teacherselected, effectiveness of the choice made, session du-ration and decision making time.
• Phase 2 IVT Playback: The playback phase in-volves reflection and problem solving in order to fa-cilitate learning and knowledge transfer. ECTs areencouraged to share their feelings and to commentabout their choices. Furthermore, facial expressionsrecorded during simulation are shown during the re-play session, so that ECTs can observe their own fa-cial expressions (e.g., shocked or lost) in reaction tothe various situations, just as their students wouldobserve during a real-life class. This is particularlyimportant since some expressions may reinforce dis-ruptive behaviors.
The computer process is described in Figure 1. Dur-ing the practice phase, after selecting a classroom onthe website, the ECT is directed to a webGL simu-lator generated by Unity. The webGL simulator uti-lizes the input parameters of the selected classroom(vignette, level, behaviors etc.). Then the ECT’s ac-tions are recorded along with his/her facial expressionsthrough a web-cam. Once a final node is reached inthe simulation, this data is sent back to the databasethrough the IVT website. During the playback phase,ECTs receive feedback on their choices and can replaysimulations, and they can reflect on decisions made.
IVT SimulatorFrom the vignette to the simulationThis section explains the procedure required to imple-ment a vignette, and to produce a simulation scenario.In order to achieve this, we use a framework called
MASCARET, which establishes a flow between IVTscenes.
MASCARET framework To develop IVT, we usedMASCARET (Buche and Querrec 2011), a meta-modelable to provide a description of a virtual learning envi-ronment by interpreting UML concepts. MASCARETprovides us with a fast way to implement vignettesusing an UML modeling software. Simplification ofthese vignettes is very important considering the vi-gnettes’ massive initial size; Each vignette contains ap-proximately 50 pathways, and each pathway containsapproximately 20 actions/events. The use of MAS-CARET is, therefore, essential for IVT.
Vignettes illustrate the potential sequence of interac-tions between the ECT and the student avatars. Theycan be implemented as an UML activity diagram pro-vided by MASCARET; Each action leads to anotherconsequence, which follows the vignette flow.
The activity diagram which represents a vignette isthen transferred into the IVT simulator. When the sim-ulation is launched, MASCARET loads the vignettethrough the activity diagram so that the sequence ofactions can then be played. This process allows a semi-automatic implementation of the vignettes in a virtualenvironment.
Scene In IVT, a scene (Fig. 2) is an ordered sequenceof actions and choices realized by the different protago-nists of the classroom according to vignette flows. Pro-posed choices allow ECTs to practice monitoring andredirecting the disruptive avatars of the situation. Dur-ing the progression of the simulation, disruptive be-haviors are minimized when the ECT makes effectivechoices. Conversely, the student becomes more unrulywhen less effective decisions are made. Once a choicehas been selected, the corresponding action is automat-ically executed and the simulator starts performing thesequence following a given choice. The simulation alter-nates between sequences of actions and decision nodesuntil a final completion node is reached.
Figure 2: IVT Scene - Drum solo pathway
IVT EnvironmentClassroom Two 3D classrooms were designed forIVT, one 1st grade and one 6th grade. Multiple proto-types were developed and vetted by six educators with
extensive experience working in high-poverty schools.Their feedback and recommended revisions helped en-sure both classrooms were realistic and authentic. Ac-cordingly, to provide an immersive experience the class-rooms also required a high level of realism. Thus, spe-cial features like wall decorations, desks and chairs, andfurniture arrangement were carefully considered to en-hance the verisimilitude according to the grade.
Characters A total of 30 unique avatars (Fig. 3)were generated to accurately depict diverse students.Motion-capture technologies were used to animatethem, audio recording was employed to record chil-dren’s voices, and Unity navigation system was usedto create the virtual boundaries. Moreover, each stu-dent in the classroom was assigned a specific behavior.There are two kinds of behaviors:• Disruptive: A disruptive avatar can be off-task (OT),
I.E. daydreaming or looking out the window, oraggressive/non-compliant (A/NC), refusing to followinstructions or exhibiting hostile behaviors (verbaland/or physical). From the set of avatars generatedfor each classroom, a subset of four disruptive oneswere implemented, OT and A/NC for 1st grade and6th grade.
• Non-disruptive: Non-disruptive avatars are con-trolled by a finite state machine, which loops throughbehaviors relevant to the context of the vignettestory.
Figure 3: IVT Character - Face, body and animation
IVT WebsitePrevious work by the investigative team documentedthat ECTs preferred online rather than in person train-ing, so that they could practice at their convenienceand not be required to attend professional developmentduring the school day.
Both phases of IVT are contained in the website. Ini-tially, ECTs can practice their behavioral managementskills on the two classrooms with three levels of diffi-culty, and obtain feedback on it after the simulation.
The playback phase allows ECTs to reflect on deci-sions they made during the simulation. For a chosensimulation ECTs can replay the scene while viewingtheir own facial expressions which were recorded duringthe simulation.
Conclusion and Future WorkDifficulties preventing and responding to disruptive be-haviors is one of the top reasons why new teachers
leave the profession. In this paper, we have presentedthe IVT system, an advanced training system in whichearly career teachers working in high poverty schoolscan hone their behavioral management skills using dis-ruptive avatars in a virtual training environment.
The IVT application goals are to design, program,and gauge the effectiveness of early career teachers’ in-teractions inside a 3D virtual classroom occupied bystudent avatars. By simulating disruptive children,novice teachers can hone their skills and learn how tomanage a challenging classroom behaviors.
The next challenge is to evaluate IVT usability andperformance in classroom settings to verify the effec-tiveness of this system. Previous work has evaluatedthe effectiveness of virtual learning environments (An-netta et al. 2009; Dorn and Barker 2005), providingobjective evaluation data like learning curve formed bythe performance of learners (data on the completiontime of the task, the number of errors, etc.). Finally,studies have been done to assess the effectiveness oftransferring online learning to a real situation (Ganier,Hoareau, and Tisseau 2014; Bossard et al. 2008).
In order to properly evaluate the system, 16 pre-service teachers will provide feedback on the usabil-ity of the prototype, along with 64 early career teach-ers. These users will participate across approximately8 schools (6 in the pilot study).
AcknowledgementsThe research reported here was supported by the In-stitute of Education Sciences, U.S. Department of Ed-ucation, through Grant R305A150166 to the Rutgers,the State University of New Jersey; And by the Na-tional Science Foundation grant award No.IIS-1423260to Florida International University.
ReferencesAnnetta, L.; Minogue, J.; Holmes, S.; and Cheng, M.2009. Investigating the impact of video games on highschool students’ engagement and learning about genet-ics. Computers & Education 53(1):74–85.Bossard, C.; Kermarrec, G.; Buche, C.; and Tisseau, J.2008. Transfer of training in virtual environments: Anew challenge. Virtual Reality (12):151–161.Buche, C., and Querrec, R. 2011. An expert systemmanipulating knowledge to help human learners intovirtual environment. Expert Systems With Applications38(7):8446–8457.Calvo, R. A. E.; D’Mello, S. K. E.; Gratch, J. E.; andKappas, A. E. 2015. The Oxford handbook of affectivecomputing.Creemers, B. P. M. 1994. Effective instruction as abasis for effective education in schools. Tijdschrift VoorOnderwijsresearch 19(1):3–16.Crone, L. J., and Teddlie, C. 1995. Further examinationof teacher behavior in differentially effective schools: Se-
lection and socialization process. Journal of ClassroomInteraction 30(1):1–9.Denton, C. A., and Hasbrouck, J. 2009. A descrip-tion of instructional coaching and its relationship toconsultation. Journal of Educational and PsychologicalConsultation 19:150–175.Dieker, L.; Hynes, M.; Stapleton, C.; and Hughes, C.2007. Virtual classrooms: Star simulator building vir-tual environments for teacher training in effective class-room management. New Learning Technology SALT4(1):1–22.Dorn, L., and Barker, D. 2005. The effects of drivertraining on simulated driving performance. Accident ;analysis and prevention 37(1):63–9.Ganier, F.; Hoareau, C.; and Tisseau, J. 2014. Eval-uation of procedural learning transfer from a virtualenvironment to a real situation : a case study on tankmaintenance training. Ergonomics 57(6):828–843.Grossman, P., and McDonald, M. 2008. Back to thefuture: Directions for research in teaching and teachereducation. American Educational Research Journal45:184–205.Herviou, D., and Maisel, E. 2006. ARéViRoad : avirtual reality tool for traffic simulation. In Proceedingsof Urban Transport, 297–306.Ingersoll, R. M., and Smith, T. M. 2003. The wrong so-lution to the teacher shortage. Educational Leadership60(8):30–33.Magnentat-Thalman, N., and Thalmann, D. 2005. Vir-tual humans: thirty years of research, what next? TheVisual Computer 21(12):997–1015.Oliver, R. M., and Reschly, D. J. 2010. Special ed-ucation teacher preparation in classroom management:Implications for students with emotional and behavioraldisorders. Behavioral Disorders 35(3):188–199.Popovici, D. M.; Buche, C.; Querrec, R.; and Harrouet,F. 2004. An interactive agent-based learning environ-ment for children. In Nakajima, M.; Hatori, Y.; andSourin, A., eds., International Conference on Cyber-worlds, 233–240. IEEE Computer Society.Reigeluth, C. M., and Carr-Chellman, A. A. 2009.Instructional-design theories and models: Building acommon knowledge base.Shernoff, E. S.; Maríñez-Lora, A. M.; Frazier, S. L.;Jakobsons, L. J.; Atkins, M. S.; and Bonner, D. 2011.Teachers Supporting Teachers in Urban Schools: WhatIterative Research Designs Can Teach Us. School psy-chology review 40(4):465–485.Shernoff, E. S.; Frazier, S. L.; Maríñez-Lora, A. M.;Lakind, D.; Atkins, M. S.; Jakobsons, L.; Hamre, B. K.;Bhaumik, D. K.; Parker-Katz, M.; Neal, J. W.; Smylie,M. A.; and Patel, D. A. 2016. Expanding the roleof school psychologists to support early career teach-ers: A mixed-method study. School Psychology Review45(2):226–249.
