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Simulation as a Strategy in Teacher Educationlocked

Simulation as a Strategy in Teacher Educationlocked

  • David KaufmanDavid KaufmanSimon Fraser University
  •  and Alice IrelandAlice IrelandSimon Fraser University

Summary

Simulations provide opportunities to extend and enhance the practice, feedback, and assessment provided during teacher education. A simulation is a simplified but accurate, valid, and dynamic model of reality. A simulation allows users to encounter problem situations, test decisions and actions, experience the results, and modify behavior cost-effectively and without risking harm. Simulations may or may not be implemented using digital technologies but increasingly take advantage of them to provide more realism, flexibility, access, and detailed feedback. Simulations have many advantages for learning and practice, including the ability to repeat scenarios with specific learning objectives, practice for longer periods than are available in real life, use trial and error, experience rare or risky situations, and measure outcomes with validated scoring systems. For skills development, a simulation’s outcome measures, combined with debriefing and reflection, serve as feedback for a formative assessment cycle of repeated performance practice and improvement.

Simulations are becoming more common in preservice teacher education for skills such as lesson planning and implementation, classroom management, ethical practice, and teaching students with varying learning needs. Preservice teachers can move from theory into action, with more practice time and variety than would be available in limited live practicum sessions and without negatively affecting vulnerable students. While simulations are widely accepted in medical and health education, examples in teacher education have often been research prototypes used in experimental settings. These prototypes and newer commercial examples demonstrate the potential of simulations as a tool for both preservice and in-service teacher education. However, cost, simulation limitations, and lack of rigorous evidence as to their effectiveness has slowed their widespread adoption.

Subjects

  • Professional Learning and Development
  • Technology and Education

Introduction

As calls increase for school accountability (Feng, Figlio, & Sass, 2018), teaching quality faces scrutiny and frequent criticism. Teachers need an ever-broader range of knowledge, skills, attitudes, and behaviors for guiding and motivating students to achieve measurable learning goals. This challenges teacher education programs to find new ways to ensure that their graduates will be effective in highly demanding work settings.

Simulations are well-established learning tools in many disciplines. Although their use is relatively uncommon in teacher education, research and experience in other fields, particularly medical and health education, point to their potential for developing effective teachers. Drawing on examples from several disciplines, this article highlights ways that simulations can strengthen critical aspects of teacher preparation as programs look for ways to better equip their graduates for future challenges.

Teaching Quality and Teacher Education

Teaching quality is commonly viewed and measured as a teacher’s ability to achieve student learning gains, regardless of student demographics or social considerations (Hanushek & Rivken, 2012). Although there is little consensus on the specifics of quality teaching (Levine, 2006), teachers are expected to have a wide range of knowledge, dispositions, and skills, including subject matter knowledge, pedagogical knowledge and skills, supportive and caring attitudes, professionalism, and skills in planning and managing diverse groups of students. As a result of policy initiatives and the movement to data analytics, however, teaching effectiveness is being increasingly defined and evaluated in terms of outcomes-based models (Darling-Hammond, Amrein-Beardsley, Haertel, & Rothstein, 2012). Therefore, teacher education programs are under increasing pressure to ensure that their graduates can produce measurable student learning gains in the face of growing criticism that they are not preparing teachers for early 21st-century contexts and conditions (Allen, Coble, & Crowe, 2014; Knight et al., 2015; Levine, 2006; Liston, 2013).

Attempting to understand how individual teachers promote student achievement, researchers have identified distinct dimensions of effective teaching practice (Stronge, Ward, & Grant, 2011). Stronge et al. identified evidence for four broad practice categories: instructional delivery; student assessment and feedback; the learning environment, including classroom management; and personal qualities, including caring positive relationships, fairness, enthusiasm, and encouraging students to take responsibility. Their study found measurable differences in classroom management and personal qualities between top- and bottom-performing teachers, as measured by student achievement. The Gates Foundation Measures of Effective Teaching (MET) study (Kane, Kerr, & Pianta, 2014) found similar relationships. Classroom behaviors associated with “press” (keeping student busy, on task, thinking rigorously, and persisting through difficulty) and “support” (interesting lessons together with caring, communicative, helping behavior) were positively associated with improved learning outcome in the large-scale study. Reporting in more detail on MET study outcomes, Teaching Works (2014) identified 19 “high-leverage practices” linked to student success. These and other studies argue for a stronger teacher education focus on effective classroom and support practices.

Classroom practices have historically been developed through the practicum, where pre-service teachers practice applying their knowledge and skills, receive feedback, and gain experience in working with students and managing the classroom environment. Practicum experiences allow teacher candidates to learn and grow in protected settings and are often viewed as the most important aspect of teacher education programs (Arnett & Freeburg, 2008; Darling-Hammond, 2006; Girod & Girod, 2008). However, the practicum often suffers from problems including a lack of appropriate or diverse field placements, host teacher shortages, host teachers’ poor teaching practices, lack of opportunities to work with special-needs students, limited opportunities for repeated practice, and poor integration with the university curriculum (Billingsley & Scheuermann, 2014; McPherson, Tyler-Wood, McEnturff Ellison, & Peak, 2011; Wilson, Floden, & Ferinni-Mundy, 2001).

Some researchers have called for strengthening teacher education’s practice component by moving to a focused emphasis on core practices that contribute to teaching effectiveness (Ball & Forzani, 2009; Forzani, 2014; Grossman, Hammerness, & McDonald, 2009). Fundamental to this approach are “pedagogies of enactment,” in which discrete parts of complex practices are role-played, evaluated, and refined based on feedback (Grossman et al., 2009). These make classroom practice an integral part of teacher education rather than a separate stage near its conclusion.

Teachers’ personal qualities and supportive behaviors, long acknowledged as important, have been the focus of research on dispositions for teaching. Various definitions of dispositions have been used (DeMuth, 2012), expressing a broad constellation of values and behavior patterns that affect classroom practice. Helm (2010b, p. 237) listed as examples kindness, caring, initiative, fairness, decency, service, prosocial behaviour, honesty, humility, trust, empathy, healing, a sense of community, having high expectations for students and themselves, teaching students to think critically, having a strong work ethic, and having an appreciation of cultural diversity. Helm (2010a) explored assessing candidates’ dispositions before they are admitted to teacher training, concluding that some candidates are better suited than others to be good teachers and that dispositions need to be developed through modeling, assessment, and feedback during teacher preparation. Harrison, Smithey, McAffey, and Weiner (2006) described a comprehensive process for assessing candidates’ dispositions, before admission and at various education stages, that focused on observable behaviors. These assessments were used to screen program candidates and provide formative feedback at the start and end of the practicum.

Improved initial assessment, together with increased practice, observation, and feedback during teacher training, are thus likely to enhance new teachers’ classroom skills and teaching dispositions, improving their future student learning outcomes. Several types of simulations provide opportunities to extend and enhance this practice and feedback. The following discussion outlines their characteristics, gives examples of their use, and suggests ways in which they can enhance aspects of teacher education related to student achievement.

Simulations for Learning Professional Practice

A simulation is a simplified but accurate, valid, and dynamic model of reality implemented as a system (Sauvé, Renaud, Kaufman, & Marquis, 2007). Simulations are distinguished from games in that they do not involve competition. A simulation allows users to encounter problem situations, try decisions and actions, experience the results, and modify their behavior without risking harm. Simulations have been widely used for many years in settings such as aviation and medicine, where real-world skills practice is logistically challenging, dangerous, or costly (e.g., see Drews & Bakdash, 2013; Lu, Hallinger, & Showanasai, 2014). Simulations began to take advantage of digital technologies in the 1970s and 1980s and increasingly have relied on them to provide learners with more realism, flexibility, access, and detailed feedback. Teaching simulations arose as a fertile research and practice area in the early to mid-2000s, as seen in several of the references cited in this article.

For teacher education, Orland-Barak and Maskit (2017) point out that

simulated experiences, as many teacher educators would contend, are valuable as training tools because they can recreate the real complex world of teaching. During training, they allow student teachers to recreate “reality” accurately so that they can transfer the experience back into their own future real situations. They address the question: “If I do this, what happens then?” (p. 64)

Simulations have many advantages for learning and practice, including the ability to repeat scenarios with specific learning objectives, practice for longer periods than are available in real life, use trial and error, experience rare or risky situations, and clearly measure outcomes with validated scoring systems. For skills development, a simulation’s outcome measures, combined with debriefing and reflection (Crookall, 2010), serve as feedback for a formative assessment cycle of repeated performance practice and improvement (Ferry et al., 2005; Girod & Girod, 2008).

Simulations are becoming more widely available for pre-service teacher education, allowing practice and feedback for skills such as lesson planning and implementation, classroom management, teaching and understanding students with varying learning needs and challenges, handling complex interactions with parents, and confronting ethical dilemmas (e.g., see Bradley & Kendall, 2014; Girod & Girod, 2008; Orland-Barak & Maskit, 2017; Shapira-Lishchinsky, 2013). Pre-service teachers can move from theory into action, with more practice time and variety than would be available in limited live practicum sessions and without negatively affecting vulnerable students (Carrington, Kervin, & Ferry, 2011; Hixon & So, 2009). As in other domains, learning from simulations in teaching depends on reflection and repeated practice (Girod & Girod, 2006).

Teacher assessment with simulations appears less common, but examples from other domains point to potential in this area as well (Kaufman & Ireland, 2015). A simulation’s outcome measures, combined with debriefing and reflection (Crookall, 2010), can provide feedback for formative assessment, allowing a cycle of repeated performance practice and improvement (Ferry et al., 2005; Girod & Girod, 2008). Summative assessment is more challenging, since the simulation must demonstrate, with defensible evidence, both achievement of learning objectives and transfer of the learning to performance in practice (Andreatta & Gruppen, 2009; Mislevy, 2013; Salas, Rosen, Held, & Weismuller, 2009). For a summative assessment with a high-stakes outcome, such as professional certification or competitive hiring, the simulation needs rigorous validity (Andreatta & Gruppen, 2009), reliability, and practicality in terms of cost and logistics.

Situational Simulations

Simulations have been categorized in many ways, based on their situations, tasks, disciplines, and supporting technologies (e.g., Alessi & Trollip, 2001; Bradley & Kendall, 2014; Maier & Grössler, 2000). Alessi and Trollip identified “situational simulations” as those that model aspects of working environments and interpersonal interactions and are therefore particularly applicable to teacher training and assessment. As described by Lyons (2012), a situational simulation

could be a clinical scenario, a conflict situation, or an emergency situation where the student makes decisions to respond to the situation and develops strategies to rectify the situation as they would do in real life contexts. The provision of a real life situation gives learners a sense of immediacy and involvement where time and the chosen response matter to the successful outcomes. (p. 4)

Medical and health educators use situational simulations for practice and evaluation in scenarios such as patient interviews, crisis response, and emergency departments. In management and other fields they are also used to support hiring decisions. In medical and health education, in particular, they are supported by extensive research and validation as training and assessment tools. Three broad types of situational simulations, discussed next, are likely to be especially useful as teacher education tools.

Scenario/Role-Play Simulations

In a scenario/role-play simulation, the student assumes a role and performs tasks such as diagnosing an illness (as a physician), coordinating an emergency response, or teaching a lesson. When the scenario is presented, the student may have to do research to complete the tasks. The scenario might progress following a branching tree logic based on the user’s decisions or a linear scenario requiring actions in sequence. In the area of administration, the “in-basket” exercise (Stearns, Ronald, Greenlee, & Crespy, 2003) is a variation in which the role involves handling multiple tasks based on a collection of memos, documents, and requests. These often require effective priority-setting and communication with others under time pressure and are used in recruiting to test the skills of potential managers and school leaders (e.g., Schroffel, 2012). Team-based scenario/role-play simulations, with students performing multiple roles, are used for team training in healthcare (Eppich, Howard, Vozenilek, & Curran, 2011).

Problem-based learning (PBL) is a scenario/role-play simulation approach that is particularly important in medical and health care education (Hartling, Spooner, Tjosvold, & Oswald, 2010). (Case-based learning is sometimes regarded as a separate approach [Srinivasan, Wilkes, Stevenson, Nguyen, & Slavin, 2007] but is included with PBL for the purposes of this discussion.) There are many styles of PBL, ranging from short, single-paragraph cases used in residency and continuing medical education to long, multiple-page cases used in the first and second years of medical school. Depending on the instructional goals and the student’s prior knowledge, the case may demand anything from quick judgment to in-depth, multistage reasoning and research. Cases that simulate actual patient problems are used for training in diagnosis and clinical reasoning, as well as for assessment by many professional bodies (e.g., in step 3 of the United States Medical Licensing Examination). PBL was originally developed using paper-based delivery but is now supported by a range of learning technologies (Jin & Bridges, 2014; Tambouris et al., 2012); for example, McLean, Brazil, and Johnson (2014) described a mobile PBL application in which virtual patients are introduced via video, patient data is released online in intervals, and students work in virtual clinical teams to manage patient diagnosis and treatment.

In teacher education, scenario/role-play simulations are not new, but they are gaining prominence as the need for practice in authentic situations is emphasized. As far back as 1968, Allen and Eve (1968) introduced “microteaching”—5- to 20-minute classes with small numbers of students allowing student-teachers to practice and receive targeted feedback on specific teaching skills. Choi and Lee (2009) described CBL-CMPS, a web-based learning environment using a structured approach to help student-teachers develop skills and dispositions needed for solving real-world, ill-structured classroom dilemmas. Ball and Forzani (2009) discussed short role-plays focusing on specific classroom tasks (e.g., teaching fractions to a fourth-grader) as a vehicle to reflect on and improve specific cognitive and relational practices that contribute to learning. Butvilofsky, Escamilla, Soltero-González, and Aragon (2012) described a simulation in which second-language teachers role-played their students and were taught in a language that they did not know well. Reflecting on their experience of discomfort and confusion led them to better understand effective teaching techniques and to empathize with their students’ learning challenges. Hume (2012) described a similar exercise in which pre-service science teachers role-played their students and were able to better see how specific teaching practices could address their students’ needs. In another application, an online, scenario-based diversity simulation has been successfully used to introduce classroom diversity considerations and promote pre-service teachers’ creativity and team-building (Manburg, Moore, Griffin, & Seperson, 2017). And in a new form of technology support for scenario simulations, a virtual-reality simulation places a student-teacher inside a filmed classroom for practice in classroom and student behavior management (University at Buffalo, 2018).

Following the example of business recruiting, in-basket and role-play simulations are also used in some programs to screen potential teacher candidates. Stanford University uses an office-hour simulation to screen potential second-language teaching assistants for their language accuracy, fluency, and communication style (Stanford University, n.d.). The not-for-profit group Teach for America requires candidates to teach simulated lessons as part of their final interviews before hiring (Teach for America, 2018). Uplift Education, a Texas charter school network, has included in their teacher candidate screening framework a set of role-play exercises involving emailing an upset parent, teaching a model lesson, and analyzing student performance (Pappano, 2011). The U.S. not-for-profit organization Citizen Schools uses “job simulation activities,” in-basket exercises that include lesson planning and email correspondence based on hypothetical student profiles, as part of a multistage tutor hiring process (Citizen Schools, n.d.).

Simulations With Standardized Patients and Students

A standardized patient is a healthy person (a professional or amateur actor) who is trained to realistically and accurately reproduce a medical scenario (McMaster University, 2018). Standardized patients are used in the Objective Structured Clinical Examination (OSCE), a type of situational simulation used extensively in medical and healthcare education for both practice and final assessment of clinical and interpersonal skills. At an OSCE “station,” students are given a task to perform in a specific time period, such as taking a history, performing a physical examination, or giving bad news. An expert assessor uses a predetermined checklist to assess the student either at the station or later using a video recording of the interaction. Shorter OSCEs (e.g., five stations) are used for training and feedback, while longer ones (12 or more stations) are typically used to increase validity and reliability in high-stakes examinations (Kahn, Gaunt, Ramachandran, & Pushkar, 2013; Pell, Fuller, Homer, & Roberts, 2010). OSCEs have also been used at admissions to assess candidates’ interpersonal skills (Eva, Rosenfeld, Reiter, & Norman, 2004). More complex simulations using multiple standardized patients have been used to develop skills in leadership, teamwork, and patient care management (Horsley, Bensfield, Sojka, & Schmitt, 2014).

A similar approach, the Objective Structured Teaching Exercise (OSTE), has been used for teacher training in medicine (Sturpe & Schaivone, 2014; Trowbridge, Snydman, Skolfield, Hafler, & Bing-You, 2011). Using a trained standardized student, the OSTE requires a learner, playing the teacher role, to manage the situation, responding to a standardized student’s individual behaviors, learning characteristics and possibly special needs. Immediate feedback is based on a predetermined behaviorally based scale or checklist. Trowbridge et al. noted that based on qualitative evidence, the OSTE improves teaching performance and has potential for developing and evaluating specific teaching competencies. OSTE implementation is costly and resource-intensive and so far has been limited to simulations with single standardized learners rather than full classes.

eduSIMS (2018) uses standardized parents, students, and community members to train pre-service teachers and school leaders in communication and management skills (Dotger, 2009; Dotger & Alger, 2012). Simulations focus on issues that teachers and leaders commonly encounter, such as struggling or disabled students, concerned parents, ethical dilemmas, or school bullying (eduSIMS, 2018). Each simulated interaction is captured on video for feedback and debriefing.

Computer-Based Clinical Simulations

Situational simulations that use technology to model people and/or learning environments often provide a more realistic user experience of practice in clinical settings. Computer-based clinical simulations are widely used in medical and health education for practice at many levels, from isolated clinical skills through comprehensive protocols (Drews & Bakdash, 2013). A patient simulator, for example, presents an interactive patient and clinical work environment through a physical human model, computer displays, or virtual reality. It allows a user to work through steps in a simulated medical case including history-taking, physical examination, laboratory tests, diagnosis, and, in some cases, management of the patient’s condition (Gaba, 2007). The simulation may provide detailed feedback on the user’s performance, including skill mastery and patient outcomes (Cook et al., 2011). Multiuser physical and virtual training environments are used for team training, for example in emergency medicine, disaster preparedness, and cardiac life support (Heinrichs, Youngblood, Harter, & Dev, 2008; Khanal et al., 2014).

Computerized classroom simulations are the teacher education analog of clinical simulations. The early microcomputer-based Curry Teaching Simulations (Strang, 1997; Strang & Loper, 1985–1986) offered practice and feedback on student-teacher dialogue, individualized student management, activity pacing, classroom management, and other skills. Initially requiring two operators to translate teacher and student responses between the simulation and its user (a pre-service teacher), they evolved by 1993 into a fully computerized simulation and received promising evaluations even in their initial form (Office of Postsecondary Education, 1990). The Cook School District simulation uses simulated students based on real people to support pre-service teachers as they practice connecting teaching and learning (Girod, Girod, & Denton, 2007). This simulation animates the Teacher Work Sample Methodology (TWSM; Girod, 2002), which dates from the 1970s and models in detail connections between teacher actions and student learning. Originally used in the context of an authentic field experience with real students, TWSM requires a student to define and defend learning goals, pedagogical approaches, and lesson plans; administer pre- and posttests; analyze student results; and reflect on connections among teaching, student learning, and personal professional growth (Girod & Girod, 2006). The students in the simulation are based on real students, taken from the experience of former classroom teachers. In the simulated environment, users are able to repeat and modify their teaching strategies and plans in a variety of grade levels and content areas. Interaction is in the form of choices, with feedback provided through documents and reports. Cues, prompts, and personal notes encourage reflection during and following the simulation, and feedback is provided through impact of user decisions and actions on student learning. The TWSM is being used for assessing teacher performance at U.S. institutions that are part of the Renaissance Teacher Work Samples group, although the simulation itself is used only for practice of TWSM skills.

ClassSim, an online simulation, focuses on training teachers for special-needs students. (Ferry et al., 2005). The simulation uses virtual episodes in a kindergarten class setting with decision points for the teacher about lesson structure, classroom management, and interactions with students. Learning is supported with materials, online links, and a reflection space. There is evidence that ClassSim can contribute to the development of pre-service teachers’ professional identities and to their skills in connecting theory to real-life practice (Carrington et al., 2011).

Fischler (2007) reported on an online simulation for teacher education that he developed alone over a two-year period. In his simulation, pre-service teachers become SimTeachers in a virtual school, applying theory they are learning to teaching scenarios in a simulated environment. The virtual schools contain fictional characters with whom students in the scenarios interact in branching scenarios. SimTeachers are able to perform routine teacher activities, such as creating lessons plans, taking attendance, or completing an Individualized Educational Program for a child with special needs.

In a very different example, the U.S. Army announced Enhanced Dynamic Geo-Social Environment (EDGE), a computer-based simulation to train school staff in responding to a school shooting scenario. Adapted from a safety training simulation for soldiers, EDGE is based on real events and uses modifiable suspects and weapons. It allows school staff to assess the results of different responses and school safety measures (such as intercoms or automatically locking doors). It also lets teachers practice how to effectively act in the midst of chaos to minimize damage (ABC News, 2018).

In one of few commercially available simulations for teacher training, the company Aten Inc. offers a stand-alone or web-based “Classroom Teacher Training 3D Simulation” that contains branching scenarios in which student-teachers make classroom management decisions, receive expert advice, and view outcomes from other decisions. Learning modules cover various classroom situations (Aten Intelligent Educational Systems Inc., 2018).

Other simulations attempt to reproduce more fully the experience of working in a classroom setting. simSchool offers web-based practice experiences for pre-service teachers (Badiee & Kaufman, 2014; Christensen, Knezek, Tyler-Wood, & Gibson, 2011). It uses screen shots of a classroom of randomly generated student avatars, seen from the teacher’s position at the front of the room. Students have a range of cognitive abilities and personalities, including English as a second language and autism, and the simulation dynamically generates learner behaviors in response to teacher actions, chosen from lists of possibilities and based on a model of cognition, personality, and communication theory. Studies have evaluated simSchool’s effectiveness for general teaching practice (Badiee & Kaufman, 2014; Deale & Pastore, 2014), developing student-teachers’ self-efficacy (Christensen et al., 2011), pre-service teacher assessment (Gibson & Halverson, 2004), and learning to work with diverse and special-needs student populations (McPherson et al., 2011; Rayner & Fluck, 2014). These have indicated a range of positive learning outcomes for pre-service teachers after simSchool use, although users have questioned its realism.

TLE TeachLivE attempts to fully reproduce a classroom using a “mixed reality environment” that blends human and artificial content. Because suspension of disbelief (i.e., belief that the simulated environment is in some sense “real”) is important for learner engagement in a simulation (Dede, 2009), users teach in a physical classroom environment (or with a TV-cart display) with simulated student avatars operated as puppets by a trained human (Dieker, Rodruiguez, Lignugaris/Kraft, Hynes, & Hughes, 2014). The puppetry approach allows a wider range of learner behaviors to be flexibly modeled without the need for full psychometric computational models. Classroom scenarios can be set up to teach specific skills and behaviors, and the system enables repeated practice. In 2018 it was used at 51 universities and other institutions across the United States. TLE TeachLivE has been shown to enhance pre-service teachers’ self-efficacy (Bautista & Boone, 2015). In addition to teaching general classroom management skills, TLE TeachLivE has been successfully used to train teachers of special-needs learners including severely autistic students (Dieker et al., 2014).

TLE TeachLivE is partnering with other groups to enhance its depth and range of applications. In a partnership with the University of Virginia, the team is building a mixed-reality simulator based on the Curry Teaching Simulations (University of Virginia Curry School of Education Foundation, 2018). And in a study across 10 U.S. partner sites, TLE TeachLivE has been shown to increase the frequency of specific instructional practices that increase student learning, making it an effective tool for teacher professional development (Dieker, Hughes, Hynes, & Straub, 2017).

In the first large-scale use of simulation for teacher assessment, TLE TeachLivE is the technological foundation for the Educational Testing Service (ETS) National Observational Teaching Exam (NOTE), a performance assessment for teacher licensing. Based on research identifying critical practices for effective teachers (ETS NOTE, 2018b; Teaching Works, 2014), NOTE assessments use interactive workstations that put teachers in simulated classrooms for standardized teaching scenarios that are recorded and rated according to standards for accuracy, fairness, and validity (ETS NOTE, 2018a).

Challenges and Implementation Issues

Ideally, simulation use should be based on a strong theoretical foundation, clear understanding of the behaviors to be practiced or assessed; a valid simulation model; enough realism to engage users; and mechanisms for evaluation, feedback, reflection, and debriefing. These make simulation adoption quite challenging, but adopting the strategy for teacher education becomes even more so when considering the larger context of innovation within education systems. Orland-Barak and Maskit (2017, p. 69) identify drawbacks associated with integrating simulation into teacher education, including difficulties with software use, pre-service teachers’ lack of prior exposure to being taught with modeling and simulations, lack of time for them to become comfortable with new teaching tools, and student resistance arising from limited simulation realism compared to “real” situations. Miller and Bull’s (2013) survey of nursing faculty concluded that faculty needed time to play with and understand a simulation and that they needed to see its value as an academic asset rather than as a politically imposed change in their teaching methods.

Cost and time constraints, as well as educators’ reluctance to change teaching approaches and accept new technologies, can be barriers, although these vary with simulation type and complexity and with educators’ prior experience. In universities, the choice to use simpler simulations such as role-plays is typically made by individual faculty members, at the cost of the professor’s time to develop or source scenarios and to integrate them into classroom-based practice. Using standardized students involves additional costs for actors playing classroom roles. Support from institutional and departmental leaders is crucial for the adoption of simulations in teacher education, and Gibson, Knezek, Redmond, and Bradley (2014) provide suggestions for what these leaders should know and do to advance simulation use in their programs.

Finally, implementing computer-based simulation requires new investment in software and possibly hardware, instructor training, and ongoing costs for technology support. One possibility for managing some of these costs has been introduced by simSchool, whose pricing options include per-user licensing fees that can be charged back to students.

Critique of Simulation in Teacher Education

Despite their potential to enhance teacher education, technology-based simulations have not been widely adopted. Several reasons may explain this. First, most available simulations are limited in their fidelity, so users are not able to “suspend disbelief” and immerse themselves fully in the simulated classroom. For example, simSchool is enjoyable and engaging but lacks realism and authentic interaction with students. Second, the instructional methods that can be employed in classroom simulations are teacher directed and didactic. Once again, simSchool is an example of this limitation. As a result, today’s modern learning-centered, constructivist methods, such as PBL (Hartling et al., 2010; Hushman & Napper-Owen, 2011), inquiry learning (Wink & Hwang-Chlo, 2008), and cooperative learning (Jolliffe & Snaith, 2017), cannot be practiced. Third, a simulation will not be effective unless it is closely integrated into the teacher education curriculum (Fischler, 2007), which has often not been the case. Fourth, more realistic high-fidelity simulations can be expensive to purchase and implement and complicated to set up and use. For example, TeachLivE costs $120 per hour (for an unlimited number of trainees) or $20 per recommended 10-minute training session and requires a dedicated training room setup (EdSurge, 2018). Finally, no rigorous research demonstrates skills transfer from the simulated classroom environment to authentic classrooms. Without this evidence base, it is understandable that teacher education administrators are unwilling to invest in this new technology.

Conclusions: Looking to the Future

While simulations are widely accepted in medical and health education, the examples cited here in teacher education are often research prototypes used in experimental settings. However, commercial simulations for teacher education and assessment are growing in visibility and reach, as shown by simSchool, TLE TeachLivE, ETS® NOTE, and Aten Inc.’s Classroom Teacher Training 3D product. These and the research examples show that simulations can serve as candidate assessment tools, provide opportunities to practice specific skills and interpersonal behaviors, and help to develop dispositions to support effective teaching. In particular, they can be tools to augment practicum experience with a cycle of practice, feedback, reflection, and repeat practice.

Also, technology advances promise greater realism, distributed access, and applications on mobile devices (e.g., Gibson, 2013) and with virtual reality (University at Buffalo, 2018). Teacher education is likely to gain significantly if technology-supported teaching simulations become more realistic, less costly, and more effectively introduced and implemented. However, if teacher educators are expected to adopt these tools, rigorous evaluation studies will need to be done to demonstrate their effectiveness in improving real-world teaching quality.

Acknowledgments

This article has been adapted by permission from Springer Nature.

References