The Potential of Simulated Environments in Teacher Education

Abstract

The future of virtual environments is evident in many fields but is just emerging in the field of teacher education. In this article, the authors provide a summary of the evolution of simulation in the field of teacher education and three factors that need to be considered as these environments further develop. The authors provide a specific example of the work at two universities that use a specific virtual environment, TLE TeachLivE™, in teacher education. This environment is already being used in teacher preparation at 32 universities to collaboratively find ways to enhance teacher practice while using a standardized tool often found in medicine, business and military training, and virtual simulation.

Keywords

teacher education virtual environments effective teaching

Reforming teacher preparation continues to be an ongoing discussion at the local, state, and national levels with attention from philanthropic entities from the Bill & Melinda Gates Foundation to the Great Schools Network and within every office of the United States Department of Education. Currently, the literature in the area of simulation and training within the field of teacher education is limited (Clarke, 2013), having only emerged around 2007. Fortunately, literature in the area of simulation and training does exist for other professional disciplines such as aviation, military, and medicine. Drawing on the extant literature, the field of teacher education can develop virtual environments to affect teacher preparation and practice (Mullen, Beilke, & Brooks, 2007). In this article, we framed the state of simulation and training, in general, as it is related to teacher education. Highlighting the limited but existing literature in this area, we provided specific recommendations of components that must be included to use this technology effectively. We concluded with a beginning example of the use and impact of a fully immersive simulator in teacher preparation being used by a partnership university.

The use of simulated environments is a part of the evolution in teacher education being realized through emerging technologies. Just as teachers are changing the way they use technology in student learning, so must teacher education adapt and evolve to take advantage of the numerous opportunities that technological tools can provide to shape teacher practice and the field of teacher education.

Before personalized simulated environments can evolve to a high level of usefulness, the field must first define the essential targeted teacher behaviors to be addressed in these virtual environments. If the ultimate target for the field of teacher education is to affect student learning outcomes through effective teacher preparation, the aim of evolving simulated environments should be directed toward specific performance targets. The Bill & Melinda Gates Foundation (2010) has launched a large-scale study (Measure of Effective Teaching [MET]) in an attempt to determine effective teaching behaviors. The MET study has provided the field of teacher education several high leverage practices that target specific behaviors. In addition, the research literature in the 1980s (e.g., Brophy & Good, 1986; Good & Brophy, 1986; Rosenshine & Meister, 1992; Rosenshine & Stevens, 1986) already reveals some strong characteristics of an effective teacher (e.g., praise, wait time, guided practice, higher level questioning). This accumulation of research findings, however, has yet to pinpoint the specific traits needed for an “effective” teacher of K-12 students with a range of disabilities. If a research-based consensus could be reached as to effective teaching behaviors, one of the outcomes of using simulated environments would be to shape very discrete and targeted practices in the simulated environment.

Status of Simulation in Teacher Education

Focusing on critical behaviors, teacher educators could enhance the preparation of the next generation of in-service and pre-service teachers using simulations and virtual environments. Simulations allow individuals to have repeated trials involving high stakes situations without risking the loss of valuable resources (e.g., money, time, and people). There are currently varying levels of simulators being used in teacher preparation (e.g., Dieker, Hynes, Hughes, & Smith, 2008; McPherson, Tyler-Wood, McEnturff Ellison, & Peak, 2011). The impact of virtual environments on the key practices of teacher behavior is grounded in three components that are used with simulators in other professional disciplines. These three critical components must be purposefully planned for and are realized in strong simulated environments: (a) personalized learning, (b) suspension of disbelief, and (c) cyclical procedures to ensure impact.

Traditionally, individualized teacher preparation has occurred only in internships or practicum placements, when pre-service teachers are matched with specific cooperating teachers. Brand (1998) cautioned against a “one size fits all” instructional model noting that the approach is not effective in changing teacher behavior. He suggested that teachers should identify their current interests and that training should be geared to a teacher’s needs and goals using diversified instructional strategies. Despite the fact that the Horizon report (Johnson, Smith, Willis, Levine, & Haywood, 2011) indicates that we are still two to three years away from complete personalized learning technology platforms, systems that enable self-directed use of technology for students and teachers are emerging. Flexible learning environments (e.g., www.cast.org), for learning and growth will be the challenge in the next decade of teacher preparation. Personalized learning platforms could provide teachers with the tools to assist them in ascertaining critical skills needed for their success and, most importantly, for the success of the students they will teach.

For simulated environments to be effective, they must provide a sense of “real presence,” much like the difference between a pre-service teacher reading about behavior management to experiencing real students and real classrooms. This phenomenon of “presence” is the key to an effective simulator (Dede, 2009). These environments must provide a personalized experience that each teacher believes is real (i.e., the teacher “suspends his/her disbelief”). At the same time, the teacher must feel a sense of personal responsibility for improving his or her practice grounded in a process of critical self-reflection. These personalized learning environments are needed for teachers to experience self-directed professional development where mentors/coaches and experts in content and pedagogy work collaboratively with teacher candidates in a safe technology-driven environment to produce effective teachers. Simulations are just one form of these personalized learning environments that are emerging, and the time is now for the field of teacher education to harness the use of these tools from lessons learned in other disciplines to effectively affect teacher education.

The notion of suspension of disbelief is not a concept that has been part of the teacher education literature, and its importance to high quality simulations is paramount. The literature from other fields gives a sense of this importance. Dede (2009), an expert on the impact of presence through technology, shared that when a high level of engagement occurs between human and technology, the user believes that he or she is in that environment physically and cognitively. This concept is one most of us have experienced when we meet a character at a theme park, and we know it is a real person in the costume. The environment of the theme park suspends our belief of the “real” world into one that is altered. When we enter the park, we know that the large stuffed character is probably a young adult, yet we believe, at some level, that the character is real. Kantor, Waddington, and Osgood (2000) went as far as to remind the field of simulation that if suspension of disbelief does not occur, then the system will fail. This same lesson is important to the field of teacher education as we embark on using the power of simulated environments.

The third and final component that teacher education must have in place to embrace the future of simulation in practice is a cyclical process (Dede, 2009). Simulations are an industry standard in business, medicine, and aviation, and are widely used in the military, with all having a clear cyclical process. In teacher education, a cyclical process is exemplified through the teacher observation cycle of a pre-service or in-service teacher where there is an objective to the observation of the teacher, the observation occurs, and then there is a debriefing about what occurred. This process in the world of simulation is called the Action Review Cycle (ARC; Darling, Parry, & Moore, 2005; Parry, Pires, & Sparkes-Guber, 2007). According to Holman, Devane, and Cady (2007), the ARC originated in 1981 at the U.S. Army Training Center and has been refined throughout the years. The protocol for the ARC has been used in the military for more than 35 years. Research using ARC focuses on “an interactive discussion . . . [to] decide what happened, why it happened, and how to improve or sustain collective performance in future exercises” (Institute of Defense Analyses, 1999). By incorporating the ARC into simulated environments, teachers have the opportunity for self-reflection, to ask questions, be coached, and to think outside their comfort zones to work for positive social and academic outcomes in the classroom.

The ARC procedures are similar to the continuous improvement model (CIM) commonly used in educational settings (Mercier Smith, Fien, Basaraba, & Travers, 2009). In an ARC, teachers reflect before and after the session using these three stages: (a) Before Action Review (BAR)—plan for what you hope to learn from the simulator, (b) Action—experience the simulation, and (c) AAR—teacher examines the gap between intended and actual results. This ARC provides a teacher a much more person-centered personalized platform for learning, which is the core concept behind simulated experiences.

We already know in teacher education that reflection is a powerful tool but that this process needs structure to move teachers from reflection-on-action to reflection-in-action (Dieker & Monda-Amaya, 1995; Schon, 1983). Teachers who are at the initial stages of development often can tell what they would change about a teaching experience (reflection-on-action), but they rarely have the opportunity to try again. The opportunity to try again can occur if the original mistakes happen in a simulated environment. Moreover, dependent on the severity of the mistakes, the underlying rapport between the teacher and his or her real students may be too damaged for a second attempt. In the virtual environment, making multiple attempts to facilitate and manage the classroom or to teach a concept is more than possible; it is desirable. Rehearsing a lesson, classroom management technique, a teaching strategy, behavior management techniques, or explaining content are all possible in the simulation world. This “virtual rehearsal” has the potential to improve practice, in the simulator and the classroom.

Teachers must also learn to reflect in-action by making instructional adjustments during the act of teaching. This skill might also be developed and enhanced in a simulated environment as part of virtual rehearsals. Any simulated environment must be grounded in effective teaching practice, such as those identified in the effective teaching research or that are emerging from the MET study (Bill & Melinda Gates Foundation, 2010) by teachers using reflection in-action and virtual rehearsal to improve their classroom practices based on such research on effective teaching practice.

Based on what we know from other fields, if simulators are to affect teacher practice, these tools need to be personalized in their approach and ensure that a suspension of disbelief occurs and that a systematic process is in place to ensure that change in both practice and learning occur. Currently, in the field of teacher practice and research, these types of emerging environments are present in three areas: online learning, Second Life (a blend of online and presence), and immersive simulations, which are still very limited in the field. A summary of each of these areas specifically related to the components of personalized learning, suspension of disbelief, and the cyclical feedback process (ARC) are provided. This summary is followed by the preliminary findings of a specific example of the work being done in a fully-immersive simulated environment in collaboration with 23 universities and led by the team of co-authors on this article.

Online Learning as a Simulated Environment

The nature of technology has increased in the level of applications and opportunities that exist in an asynchronous environment. In asynchronous types of environments, the potential for more of the components of a virtual environment to be available is emerging. In the past, a teacher in online learning would watch a module or get information and then attempt to use it in practice (much like traditional face-to-face professional development). Today, however, there are two components of simulated worlds found in the online environment, which approach more of the potential of simulation—bug-in-the-ear coaching and rapid feedback model. This work is critically important to the field in that it provides “just in time” feedback and, for the teacher, is still anchored in a real environment, but for the coach, this work asks them to have “presence,” an almost physical presence virtually in the environment to provide feedback. Rock et al. (2009) found that advanced online technologies could be used to give real-time feedback to teachers as they sought to provide evidence-based interventions in K-12 classrooms. The bug-in-ear technology proved to be a practical and effective instructional practice where teachers received direct instruction on practice from a distance. Mason (2011) applied this same principle in trying to get her students to be successful through a process that originally occurred in her teacher preparation program during face-to-face instruction. In this study, Mason took students through the virtual simulation of meetings (including the before and after elements) to understand meeting implications while in a simulated environment. In Mason’s as well as Rock and colleagues’ work, the cyclical process of feedback and a simulated or real environment was used. Neither study in these real environments, however, could allow for the type of repeated practice that a fully immersive simulated environment could afford teachers.

The second type of environment that moves the teacher into the role of presence but has waxed and waned in use is the virtual world of “Second Life” in which online avatars are used for teacher practice. In this environment, the teacher attempts presence by embodying an avatar that interacts with other avatars that are human generated. Via voice or typing, teachers can work toward lesson objectives. Knutzen and Kennedy (2012) and Kim and Blankenship (2013) used “Second Life” to affect teacher practice for second language learners. These environments have the potential to support all components of a fully immersive simulator in an online environment. To make the experience authentic, however, there is still a level of game-based suspension of disbelief that is needed as the teacher types or talks as the avatar in “Second Life.” It may be more difficult to suspend disbelief in a fully immersive environment when the image and the audio are simulated. In the area of teacher preparation in art, a beginning discussion is emerging considering the use of 3-D images (Lu, 2011) to shape teachers thinking about contemporary art instruction and, of course, typical online courses with asynchronous components. These environments may provide presence and personalized learning, but they do not necessarily have a cyclical process for feedback. Online simulation versus fully immersive simulators could serve different purposes in teacher education. Online simulators tend to be less expensive and could be used with a targeted skill prior to entering a fully immersive environment. In teacher education, these types of simulators could be used to target specific practices proven by research to be effective.

A third type of environment that may provide all three components of traditional simulators are fully developed immersive simulators, but these types of environments are currently limited in the literature to just two tools. The first is SIM School. This tool provides teachers an opportunity to make online game-based decisions that are personalized and immersive within an online environment and provides feedback on the decisions made within the game environment. SIM School is typically used in more of the pedagogical practices of teaching. Fischler (2007) discussed the impact of this tool on practice and further development, and research on this tool continues today.

The second tool is a fully developed immersive simulator that has all three components of a traditional simulator found in other disciplines. The research and development work at the University of Central Florida (UCF) have produced a simulator called TLE TeachLivE™. This Lab is a mixed-reality, avatar-based simulation environment to prepare teacher candidates or improve the effectiveness of in-service teachers. The Lab provides participants the opportunity to learn teaching skills and craft their practice without placing “real” students at risk during the learning process while incorporating the critical components of personalized learning, suspension of disbelief and a cyclical process. TLE TeachLivE™ evokes personalized learning and the suspension of disbelief by providing a room the teacher physically enters (not online) where everything looks like a middle-school classroom, including props, whiteboards, and of course, students, but it is a mixed-reality setting and the students in the classroom are avatars. The virtual students may act like typically developing or not-typically developing students, depending on the objectives of the experience. Teacher candidates and practicing teachers then interact with the virtual students and review previous work, present new content to students and provide scaffolding or guided practice in a variety of content areas, and monitor students while they work independently (promoting that suspension of disbelief and experiencing real learning). If a teacher performs poorly or if he or she wants to experiment with a new teaching idea while using TLE TeachLivE™, there is no adverse effect on any real student, but the experience feels real.

In the remainder of this article, we shared an overview of the research of the TLE TeachLivE™ Lab to this point and an example of how the technology is being applied at one partner site. This example comes from 1 of the 23 universities using TLE TeachLivE™, which was the first university partner to integrate this tool into its teacher preparation program.

TLE TeachLivE™ Research at UCF

There have been six research projects conducted in the TLE TeachLivE™ Lab at UCF in addition to the first of a three-year large scale research study currently underway. Of the past seven studies, one focused on the area of counseling (Gonzalez, 2011), one focused on recruiting middle-school students into teaching and STEM careers (Dieker, Grillo, & Ramlakan, 2011), one focused on teacher preparation in Algebra (Andreasen & Haciomeroglu, 2009), and the four others focused on special education. Of the special education directed studies, the Lab was used with teachers and students. The four studies included preparing teachers to use discrete-trial-training for students with autism (Vince-Garland, Vasquez, & Pearl, 2012), adapting the simulated environment to teach young adults with cognitive disabilities job interview skills (Walker, 2012), investigating teacher perceptions about Latino males who are and are not labeled as emotionally disturbed in the environment (Lopez, 2013), and comparing differing methods of performance feedback (Rodriguez, 2011). Four of these studies are dissertation projects, and two were faculty- and doctoral-level research study.

In the next three years, UCF faculty plan to expand the capabilities of the TLE TeachLivE™ system by increasing the number of Interactors prepared to support the environment, the age range of the avatars for use in the environment (high school avatars will be launched in the fall of 2013 and second language learners have already been put into the simulation), the number and diversity of avatars available for choice by any given site, and the range of artificial behaviors available in the environment (e.g., hand raising, talking out, moving into groups, responding as a group, and demonstrating continuity of actions).

The simulated environment focuses on teachers clearly understanding behavior, diversity, disability, and effective instruction in inclusive settings, holding teachers accountable for the practices and strategies expected in the real classroom. The ideology is that instead of basic (textbook) level knowledge about inclusive diverse settings, the practical environment of TLE TeachLivE™ Lab (in addition to the opportunities of after action review, modeling, and repeated trials) allows for application of pedagogy in a personalized and realistic environment. For example, if there were three distinct classroom environments and 15 avatar students to work with at various grade levels, teachers using the TLE TeachLivE™ Lab would have access to students from diverse cultural and linguistic backgrounds, as well as students with varied abilities and disabilities. Therefore, teacher performance across each classroom of students could be used for reflection by the teacher themselves while teacher educators could begin to make some statements about how to change bias exhibited in a simulated environment before a teacher enters into practice. In addition, teacher educators could use this simulator or a similar type of environment that might evolve within “Second Life” or SIM School with teachers practicing with the same students as are in a more immersive simulator but with easier access than going to a higher-end simulation experience.

Application of TLE TeachLive™ at a Partner University

With the evolution of TLE TeachLivE™ Lab came the need to expand the use beyond UCF to other universities. Utah State University (USU) has been the external partner and pioneer, using the system for the past five years. In fact, USU’s needs have precipitated new applications of the tool over time. This section provides a brief description of how one university is using the simulator in special education teacher preparation.

In 2009, USU began to integrate the TLE TeachLivE™ technology into their alternative preparation programs to prepare teachers of students with severe and mild to moderate disabilities. In both of these programs, in-service teachers spend their days in public schools working with students with disabilities and, in the evening, taking classes toward their education licensure. The TLE TeachLivE™ Lab was used to help teachers refine and practice basic teaching repertoires.

Preparation of Teachers of Students With Severe Disabilities

In the program to prepare teachers of students with severe disabilities, the TLE TeachLivE™ Lab was used to conduct approach-based reinforcer preference assessments and refine strategies for individualized discrete trial training (DTT). Preference assessments are used to address a common concern for teachers working with students with severe disabilities—insufficient student motivation. The general goal of a preference assessment is to identify powerful reinforcers that may improve student progress. In a preference assessment for students with severe disabilities, the teacher presents a variety of items or activities to a learner and measures the individual’s interaction with these items or activities. During the assessment, patterns emerge indicating that the individual prefers or interacts with some materials more than others. These desired items and activities are then used in specific instructional programs to increase the student’s motivation to demonstrate desired skills and classroom behavior. One research-based preference assessment procedure is a paired stimulus preference assessment (e.g., Fisher et al., 1992). In a paired stimulus preference assessment, the teacher presents two items to the student and records which item the student approaches. The student is then given access to the item or activity for a short period of time. After every item or activity is paired with every other item or activity, a summary is created by counting the number of times the item is approached and dividing by the number of times the item is available. The results are converted to a percentage and arranged into a hierarchy of preference from high to low percentage (e.g., 100%-0% approached).

In the TLE TeachLivE™ Lab, teachers practiced implementing a paired stimulus preference assessment with “Austin,” an avatar who has few verbal skills but indicates his preference by reaching toward an object. Austin may also exhibit a variety of difficult behaviors including inattentiveness and making strange noises. In the Lab, a table was placed in front of the screen, and pairs of potential reinforcers (e.g., toys, food, and items used in various activities) were presented to Austin. Austin indicated his preference by reaching toward a particular toy, food, or item. In the TLE TeachLivE™ Lab, teachers learned to implement the paired stimulus preference procedure in sessions lasting 2 to 3 minutes. The teachers were later presented with complete data sets in which they determined Austin’s preferences for the various items. Importantly, the intensity of Austin’s behavior during and across sessions varied systematically to help teachers learn to implement the procedure under different conditions. For example, initially, Austin responded to every request until the teacher demonstrated proficiency with the instructional routine. In subsequent sessions, Austin looked away continually, requiring the teacher to prompt his attention, or made strange noises or reached for both items on the table. Austin showed these behaviors individually or in combination to create a more complex and increasingly realistic context that required the teacher to integrate classroom management routines into his instruction. The ability to systematically vary Austin’s behavior to increase the difficulty of the instructional context was a critical element and advantage of the simulation.

The second application used in the program to prepare teachers of students with severe disabilities is DTT. In discrete trial instruction, the teacher presents a stimulus to which the child is expected to respond. Following the child’s response, the teacher either reinforces a correct response or implements one or more identified correction procedures. Finally, the teacher briefly pauses before presenting the next trial in the sequence. While this routine may be implemented quickly and simply with a knowledgeable and compliant child, it can become quite complex when the teacher needs to adjust the correction procedure in response to repeated errors or to a child’s inattention. In the TLE TeachLivE™ Lab, these variables are systematically varied, while teachers learn to implement a discrete trial instructional routine. In a recent pilot study, Myers, Reier, and Lignugaris/Kraft (2010) observed two teachers implement discrete trial instruction in an actual classroom. They then implemented discrete trial instruction in the TLE TeachLivE™ Lab with an instructional coach and finally observed the teachers again following their Lab experience. Prior to their Lab experience, Teacher 1 implemented none of the discrete trial instructional steps correctly and Teacher 2 implemented 34% of the discrete trial instructional steps correctly in their actual classrooms. Following approximately 40 minutes of practice in the TLE TeachLivE™ Lab with an instructional coach, both teachers implemented the steps in their classrooms with 100% accuracy. If the coach was required to visit each teacher in their school, the training would have required several hours because of the travel time to schools. While there are several clear limitations in this pilot study (e.g., limited number of participants, instructional targets, and number of data points), the implication of this demonstration is that the TLE TeachLivE™ Lab may be an efficient and effective tool for preparing teachers to implement foundation instructional routines.

Preparation of Teachers of Students With Mild and Moderate Disabilities

Finally, in USU’s program to prepare teachers for students with mild and moderate disabilities, teacher educators have begun exploring the utility of the TLE TeachLivE™ Lab to implement more complex instructional and behavior management routines with as many as four student avatars. Teachers in this program use the TLE TeachLivE™ Lab to learn strategies for gaining student attention, introducing a lesson, reviewing classroom rules, maintaining an appropriate lesson pace, strategically providing nonverbal group and verbal individual response opportunities, developing questioning strategies, and using teacher proximity, praise, and extinction to manage the student avatar’s problem behaviors. Teachers and their instructional coaches initially work to implement the scripted routines fluently and confidently. As a teacher demonstrates skills under relatively simple conditions, the complexity of the instructional situation may increase along several dimensions including the complexity of the lesson, the intensity with which individual student avatars demonstrate problem behavior, the number of student avatars exhibiting problem behavior, and the variety of learning or behavioral problems. This application is one of several that have emerged from the first conference held to talk about simulation in teacher education, and this evolving work has lead to several potential implications and research to potentially affect teacher education.

Implications for Research and Practice

Important Variables and Phenomena of the Suspension of Disbelief

Based on what has been discovered using virtual environments in teacher preparation, the overarching hypothesis is that teachers who engage in these virtual environment experiences that contain all three components found in other disciplines will improve student content knowledge and address their individual needs as well as improve teacher pedagogical and content knowledge. We also hypothesize that students will be more likely to learn from teachers who have experienced virtual environments. As the technology of the digital puppetry-based virtual environments evolves each year, the expected outcome is even greater teacher learning gains. In addition to continuously testing the effectiveness and user interface of the TLE TeachLivE™ Lab, iterative improvements to the underlying technology occur daily as new technologies emerge, which will continue to occur in all emerging simulators in teacher education. Primarily, simulated systems are evolving to be more user-friendly and affordable by using low-cost, commodity tracking devices while simultaneously placing fewer demands on how the human and technology interact (Mapes, Tonner, & Hughes, 2011). For example, one transition that has already occurred with the technology in the TLE TeachLivE™ simulator is the effective use of the $100 Microsoft Kinect™ to reduce camera tracking needs (which originally just two years ago cost $1,500). With the decrease in cost and advancements in technology comes the opportunity for stronger personalized learning and even greater suspension of disbelief. Pairing these advancements with a standardized process of reflection in teacher education could position the field for a strong and lasting impact from the evolution of simulation.

Cyclical Process

Currently, the TLE TeachLivE™ system and “SIM School” are built on the components of the ARC cycle used in most military simulators so that the teachers who enter the environments are asked to meet session objectives. If teachers, novice or experienced, fail to meet a session objective, they can reenter the virtual environments with a new plan and try again to teach the same students the same concept or skill after having received feedback and being given a chance to reflect on their practice. In simulated environments, instruction and management routines as well as content may be repeated with an individual teacher or across several teachers using the same instructional context until the skill or routine is mastered. The instruction or management context may then be changed systematically to examine how participants respond to a changing classroom environment or lesson objectives throughout.

Teachers Can Encounter Multiple Types of Students

In the TLE TeachLivE™ Lab and in the online environment of “SIM Schools,” teachers encounter a range of students. In TLE TeachLivE™, participants spend less than 10 minutes per virtual rehearsal in the Lab. (10 minutes in a simulator is equal to 45-60 minutes in the real world.) Using the software concept of a “sandbox,” a term that roughly translates into an environment that isolates testing from production, the TLE TeachLivE™ technology allows the virtual classroom to be populated with students, representing a range of ages, cultures, backgrounds, abilities, and behaviors, so that teachers can practice with virtual students exhibiting high and low-incidence disabilities prior to encountering real students in their classrooms.

Virtual environments can provide many educational experiences and opportunities that may not be available in real-world settings (Cobb, 2007; Limniou, Roberts, & Papadopoulos, 2008; Winn, 2002). The exposure to the tools and methods available for training and education using virtual environments have been shown to provide opportunities to construct knowledge through direct interactions and develop the psychological process involved with learning (Winn, 1993). Interactions that occur in virtual environments give learners the feeling of actually being in the “real” environment and provide them with the ability to act on their thoughts, ideas, or experiences for self-directed learning (Cobb, 2007; Limniou et al., 2008). The experiences are particularly relevant to the transfer of knowledge from one environment to the next and also from acquisition to application. Virtual environments embrace the emergence of more “student centric” learning, which is moving us to personalized and individualized learning platforms. In these models, students and teachers move at their own rate (personalized learning) to ensure mastery of skills. These types of platforms allow acceleration or remediation for students and teachers alike using a cyclical development process. A dearth of literature exists regarding immersive technologies as a means to bridge the gap between traditional classrooms and practice in virtual classrooms. Unlike research in actual classrooms, where controlled data collection is difficult to attain, simulated environments enable consistency in preparation, immediate feedback, and ongoing data collection, as well as refinement of the environment to ensure the maximum impact on teacher performance and student learning. In addition, the virtual simulation is designed with the user in mind—individual interactions and skills are the focus, not the capacity of the technology being used (Dekanter, 2005; Klopfer & Yoon, 2005).

From a teacher preparation and an administrative viewpoint, creating a tool that novice teachers return to each time to try something new (reflection-on-action) can support teachers moving more rapidly to reflection-in-action. It is estimated that teachers in all settings make approximately 1,300 instructional decisions in a single day (Jackson, 1968). In a world where the self-esteem of students is already vulnerable, where the need for strong instruction and a positive learning environment, not just management of behaviors, is critical, and where students rebel or even dropout if the environment does not support their social/emotional and behavioral needs, teachers who are skilled in creating positive learning environments are critical.

Administrators could use these tools for induction training of new teachers over the summer before they start in their classrooms. Techniques such as lesson study could be used by a group of teachers to allow them to work in the virtual environment and talk about their strengths and weaknesses related to behavior management before the start of the school year. Finally, these tools also could be used for in-service or retooling of teachers who might be struggling in classroom management or teaching specific content standards.

Significance of the Virtual Environment on Teacher Practice

Overall, the concepts developed and tested in virtual environments are based on the belief that performance assessment and improvement are most effective in contextually meaningful settings. A common issue in the field of education is the lack of skill transfer from one setting to another. Lessons learned in college classrooms, micro-teaching experiences, observations in real classrooms, and “practice teaching” in a classroom are teacher education experiences that have not been shown to be effective methods of assuring that novice teachers have teaching skills that will result in student achievement. These common teacher education experiences typically do not allow for repetition after reflection and do not offer exposure to specific situations such as student misbehaviors, misconceptions, and errors.

Providing teacher education instruction in contextually meaningful settings typically means that pre-service and in-service teachers who are struggling undergo assessment in the classrooms in which they are or will carry out the tasks for which they are trained. These student teaching experiences or experiences with instructional coaches occur with real children whose learning may be impaired by ineffective or incorrect teaching. This is not the time or place to change teaching behaviors. Rather, it is a time when teacher effectiveness is assessed. Thus, there is a gap in teacher education instruction where teacher candidates and struggling teachers can rehearse their skills, improve their skills, and build confidence in their abilities.

The key is to provide an authentic simulated environment using mixed reality in which generic physical objects take on personalized appearances and the suspension of disbelief occurs (Hughes, Stapleton, Hughes, & Smith, 2005). By providing a safe, controlled environment, teacher candidates and struggling teachers can focus on achieving specific, desired outcomes that will improve their success as teachers. Our belief is that student outcomes will increase as effective teacher behaviors are more fully developed. Unlike “practice instruction in real classrooms,” teachers can reenter the environment to fix errors with avatars and ensure student success, processes that we hypothesize will transfer to “real” classrooms when instructing “real” students.

Currently, the field of teacher education has tied together effective teaching and reflective practice literature. A gap exists, however, in how this transcends into virtual environments. The challenge for the field is to learn from other disciplines as these new tools are developed, adopted, and systemically integrated into our practice that focuses on personalized learning environments, suspension of disbelief, and a cyclical process to make not only changes in teacher practice but also the ultimate goal of the field of simulation and teacher education alike, student learning outcomes.

Footnotes

Authors’ Note

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This material is based in part on work supported by the National Science Foundation under Grant CNS1051067.

Author Biographies

Lisa A. Dieker is a Pegasus Professor and Lockheed Martin Eminent Scholar Chair in the Department of Child, Family, and Community Sciences at the University of Central Florida.

Jacqueline A. Rodriguez is an assistant professor of special education at College of William & Mary.

Benjamin Lignugaris/Kraft is professor and department head of special education and rehabilitation at Utah State University.

Michael C. Hynes is Pegasus Professor and director of the School of Teaching, Learning, and Leadership at the University of Central Florida.

Charles E. Hughes is Pegasus Professor in the Department of Electrical Engineering and Computer Science. He is codirector of the Synthetic Reality Laboratory (SREAL).

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