3
Simulations and Games in the Classroom

This chapter considers the use of simulations and games for science learning in the context of formal education. After describing the variety of contexts in which individuals interact with simulations and games, it discusses opportunities for using simulations and games in classrooms as well as constraints on their use. It goes on to outline alternative approaches to addressing these constraints and realizing the potential of simulations and games to support learning in science classrooms. The chapter ends with conclusions and recommendations.

INTRODUCTION: LEARNING CONTEXTS

Individuals interact with simulations and games in a variety of different contexts, comprised of interrelated physical, social, cultural, and technological dimensions (Ito, 2009; National Research Council, 2009). One dimension is the physical setting, either the formal environment of a school or university science classroom or an informal learning environment (the home, museum, after-school program, or other setting). Dimensions of the context that may influence learning include the involvement of other participants, who they are (experts, peers, family, teachers), and the technology itself (e.g., handheld devices, immersive environments provided on laptops).

Games and simulations can create local contexts that can similarly engage learners, whether at home, in school, or in after-school programs. At the same time, however, research has shown that the surrounding context can significantly shape how a learner interacts with a simulation or game and the extent to which this interaction supports science learning (Linn et al., 2010). Perhaps the most important psychological difference between using a simulation or game at school or college and using it informally is motiva-



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 57
3 Simulations and Games in the Classroom This chapter considers the use of simulations and games for science learning in the context of formal education. After describing the variety of contexts in which individuals interact with simulations and games, it dis- cusses opportunities for using simulations and games in classrooms as well as constraints on their use. It goes on to outline alternative approaches to addressing these constraints and realizing the potential of simulations and games to support learning in science classrooms. The chapter ends with conclusions and recommendations. INTRODUCTION: LEARNING CONTEXTS Individuals interact with simulations and games in a variety of different contexts, comprised of interrelated physical, social, cultural, and technological dimensions (Ito, 2009; National Research Council, 2009). One dimension is the physical setting, either the formal environment of a school or university science classroom or an informal learning environment (the home, museum, after-school program, or other setting). Dimensions of the context that may influence learning include the involvement of other participants, who they are (experts, peers, family, teachers), and the technology itself (e.g., handheld devices, immersive environments provided on laptops). Games and simulations can create local contexts that can similarly engage learners, whether at home, in school, or in after-school programs. At the same time, however, research has shown that the surrounding context can significantly shape how a learner interacts with a simulation or game and the extent to which this interaction supports science learning (Linn et al., 2010). Perhaps the most important psychological difference between using a simulation or game at school or college and using it informally is motiva- 

OCR for page 57
 Learning Science Through Computer Games and Simulations tion. In the context of formal education, the professor or teacher requires the students to interact with the simulation or game, and the students may or may not be motivated. In informal contexts, individuals play a game or manipulate a simulation for fun, motivated by their own interest and enjoy- ment (see Chapter 4 for further discussion). Reflecting this difference, most studies have focused on using educational simulations and games in either a formal or informal context; few have explored their potential to support learning across the boundaries of time and place. This chapter therefore focuses on formal educational settings, and informal settings are discussed separately in the following chapter. OPPORTUNITIES Simulations and games have great potential to improve science learning in elementary, secondary, and undergraduate science classrooms. They can individualize learning to match the pace, interests, and capabilities of each particular student and contextualize learning in engaging virtual environ- ments. Because schools serve all students, increased use of simulations and games in science classrooms could potentially improve access to high-quality learning experiences for diverse urban, suburban, and rural students. The U.S. Department of Education’s (2010) draft National Education Technology Plan states (p. vi): The challenge for our education system is to leverage the learning sciences and modern technology to create engaging, relevant, and personalized learning experiences for all learners that mirror students’ daily lives and the reality of their futures. In higher education, where faculty members generally have more control over selection of curriculum and teaching methods than do K-12 teachers, the use of simulations is growing. The number of higher education institutions accessing the PhET simulations online more than doubled over the past five years, from 580 in 2005-2006 to 1,297 in 2009-2010, and the number of online sessions by users at these institutions grew from 13,180 to 269,177 (Perkins, 2010). Among physics faculty responding to a 2008 survey about research- based instructional strategies, small proportions reported currently using other simulations and simulation-based learning environments, including Physlets (13.0 percent), RealTime physics virtual laboratories (7.3 percent), and Open Source Physics (21.8 percent) (Henderson and Dancy, 2009). The use of simulations and virtual laboratory packages is also gaining 1The PhET simulations can also be downloaded and installed for use offline, but no data are available on the number of offline sessions.

OCR for page 57
Simulations and Games in the Classroom  momentum in high schools and middle schools (Scalise et al., 2009), and games are being tested in a few schools and districts. In K-12 settings, sci- ence teachers may use a simulation or game to engage students’ interest at the beginning of a unit of instruction, build understanding of a particular topic in the unit, or as a form of assessment. Alternatively, a teacher, often in collaboration with researchers, may focus an extended unit of instruction on a simulation-based learning environment or game. Opportunities in School Settings Although many different types of simulations and games have been tested in K-12 and undergraduate classrooms, only a few have been widely implemented. Some examples are the Taiga Park curriculum unit in Quest Atlantis, which has been used by thousands of students in elementary schools, after-school clubs, and science centers, and the simulation-based learning environments developed by Songer, Kelcey, and Gotwals (2009), which have been used by hundreds of students in the Detroit Public Schools. The developers of the River City game-based curriculum unit have investigated the process of widely implementing the unit, as well as its effectiveness for learning (see Box 3-1). To capture lessons learned from this experience and research, the committee asked lead developer Christopher Dede (2009c) to outline the opportunities and constraints that formal classroom settings offer for simulations and games. Dede (2009c) identified five opportunities that classroom settings offer for using simulations and games. First, the teacher is a resource to sup- port learning and can also provide valuable information to developers on student misconceptions inadvertently generated by a game or simulation. For example, a teacher observed that a student team using River City once spent substantial time repeatedly using the mosquito catcher (a virtual tool to help students assess the local prevalence of insects that serve as a vector for malaria), well beyond what was needed for statistical sampling. When she investigated, she found that the students believed they could reduce ill- ness in the simulation by “catching” enough mosquitoes to block the disease. The teacher informed the developers, who used this feedback to modify the instructions for playing the game. Second, classroom settings offer the opportunity to reach students who might otherwise view science as boring. The growing popularity of gaming outside school reduces teachers’ work to prepare students for using educational simulations and games and builds learners’ motivation for them. Some students who enjoy gaming for entertainment but shun educational games find that as- signed gaming experiences in the classroom are unexpectedly fascinating, build- ing their interest and self-efficacy in school (Clarke, 2006; Ketelhut, 2007). Third, the responsibility of the teacher to grade students can present

OCR for page 57
0 Learning Science Through Computer Games and Simulations BOX 3-1 Implementation of River City In 2002, River City was piloted, along with a matched control curricu- lum, in three Boston area public schools with large percentages of English language learners and students eligible for free and reduced-price meals. A total of 63 sixth- and seventh-grade students participated in the River City unit, and an additional 36 students received the control curriculum. The students used either River City or the control curriculum during their regularly scheduled science classes over the course of two weeks. In 2003-2004, three variations of the curriculum unit, along with the matched control curriculum, were tested in urban schools in New England, the Mid- west, California, and the Southeast (Ketelhut et al., 2006). Like the students involved in the pilot, the 2,500 urban students in this larger test included large percentages of English language learners and students eligible for free and reduced-price meals. By 2007, over 8,000 students had been taught using River City (Ketelhut, 2007). both an opportunity and a constraint. Students and teachers using River City reported that, when the learning experience was evaluated by the teacher as part of the course grade, some students took the game or simulation more seriously, while others lost engagement. Fourth, classrooms present the opportunity to use study designs that control for confounding variables, allowing researchers to more clearly isolate whether, and to what extent, a simulation or game affects student learning. Finally, public schools offer the opportunity to deliver educational games and simulations to an entire population of students, scaling up the potential learning gains. Opportunities for Individualized Learning Simulations and games designed for science learning allow the learner some control over the pacing and content of the learning. This and other features provide the possibility of individualizing learning to match each learner’s unique needs, strengths, and weaknesses. Classroom settings provide opportunities to both tap and extend this capacity (Dede, 2009b). First, teachers can assign students to teams based on their knowledge

OCR for page 57
Simulations and Games in the Classroom  of students’ intellectual and psychosocial characteristics. For example, River City and other immersive learning environments use “jigsaw” pedagogies, in which each team member has access to data that others do not, requiring collaboration for collective success (Dede, 2009a). Teachers assigning stu- dents to these teams have worked to ensure that each team includes students with interests in science, in games, and in collaborative leadership. Teachers have also tried to place each learner in a role that matches his or her current capabilities. For example, students who struggle to read English text can aid their teams by gathering numeric data. Finally, teachers have tried to select team members so that one person does not dominate the interaction. Such nuanced composition of learning groups is much more difficult in unsuper- vised informal settings. Second, science teachers can alter their classroom instruction and sup- port on the basis of the feedback that games and simulations provide. For example, teachers working with the River City curriculum unit received daily, detailed logs of students’ chats and behaviors, as well as their scores on embedded assessments and their postings in online notepads. Most teachers reported that they liked receiving these data (Dieterle et al., 2008). In classroom settings, the teacher can take advantage of feedback from the simulation or game to enhance and individualize learning—an opportunity that is not available in informal settings. Third, science games and simulations can be adapted for students with special needs, allowing them to be mainstreamed in science classrooms. For example, the developers of an augmented reality curriculum adapted it to meet the needs of a student who was visually impaired (Dunleavy, Dede, and Mitchell, 2009). Hansen, Zapata-Rivera, and Feng (2009) are testing a new simulation-based learning system with integrated assessment that shows promise of supporting science learning for all students, including those with disabilities. As another illustration, a special needs teacher modified the River City curriculum so that her class of cognitively challenged students could complete a substantial part of the curriculum, with very positive effects on their motivation and self-efficacy. Classrooms offer opportunities for teachers to extend the supports that can be embedded in science games and simula- tions to meet special needs. Fourth, educational games and simulations can potentially help prepare students to take full advantage of other science learning activities. For ex- ample, Metcalf, Clarke, and Dede (2009) are currently designing and studying a learning environment focusing on virtual ecosystems. The researchers plan to study whether students who experience this learning environment are better prepared to take full advantage of their visits to real ecosystems. Fifth, teachers, through their knowledge of students, can relate virtual experiences in science games and simulations to what is happening in the real world or in students’ lives. For example, some students in urban settings

OCR for page 57
 Learning Science Through Computer Games and Simulations noted that the tenement houses in River City were infested by diseases that, over a century later, are still prevalent in their neighborhoods; immigrant students experiencing River City made similar observations about current conditions in their native countries. Teachers were instrumental in helping learners make these types of connections. Further research is needed on what types of professional development are most effective in helping teachers to realize these opportunities for individualizing learning with simulations and games (Schwarz, Meyer, and Sharma, 2007). Opportunities for Psychosocial Learning and Motivation Games and simulations draw on psychosocial factors to motive and to educate. There is evidence that well-designed games and simulations can enhance students’ psychosocial development, particularly in adolescence (Durkin, 2006), and schools can support this potential. Schools provide a setting in which students can informally discuss simula- tions and games, complementing the more structured, formal discussions in their science classes. As described in the previous chapter, Steinkuehler and Duncan (2008) found evidence that online discussions of the commercial game World of Warcraft supported shared learning. In schools, teachers can leverage students’ physical proximity to foster similar discussion and learn- ing, face to face. For example, some River City teachers were amazed by students’ eagerness to spend extra time on the curriculum during lunch hour or before or after school. By providing supervised access to the curriculum at these times, the schools allowed students to develop communication skills and social relationships centered on science learning. Schools also host clubs and other organizations that provide opportunities for learning informally with simulations or games. The growth of robotics illustrates this potential; similar to augmented reality games, robotics adds a kinesthetic dimension to learning (Rogers and Portsmore, 2004). Science games and simulations may motivate informal learning in similar ways, if they allow the user to modify the game or simulation, similar to modifying one’s robot. “Modding” is now possible in many games and is extensively used by many participants for fun and informal learning about the models underlying the entertainment experience. Some games (e.g., Little Big Planet, Spore) even require learner design of processes that involve scientific prin- ciples, although no support is provided for this. Science teachers can employ modding to encourage students to learn by designing simulations or games (Annetta et al., 2009; see Chapter 4 for further discussion).

OCR for page 57
Simulations and Games in the Classroom  CONSTRAINTS OF SCHOOL SETTINGS Dede (2009c) identified several constraints on the use of educational games and simulations in formal classroom settings, some of which are closely related to the opportunities described above. One is that the classroom teacher may not always implement the game or simulation in the manner intended by its designers, inadvertently undercutting student learning. For example, although River City is designed to motivate and support students in moving from exploring the virtual environment to formulating and testing a hypothesis, some teachers have asked students to use the curriculum to simply confirm correct answers that the teachers provided in advance (Ketelhut et al., 2007). As noted in Chapter 1, students often find inquiry learning difficult (National Research Council, 2005b). To effectively help students through these difficulties, teachers require deep content knowledge and effective teaching strategies. These requirements, together with practical constraints, such as lack of time and the press of high-stakes science assessments focusing on content knowledge, may discourage teachers from using games to engage students in inquiry learning. Another constraint is that schools often lack the technology infrastructure required to support a game or simulation. A chronic problem in implementing the River City curriculum has been teachers’ lack of access to an adequate, reliable technology infrastructure. These problems include difficulty providing one-to-one student access to computers and challenges in obtaining network access to outside resources. The requirement that teachers grade student work, including work with simulations and games, can also pose a constraint. Both students and teachers who worked with River City reported that, when the teacher evaluated stu- dents’ learning in the curriculum as part of the course grade, some students became less engaged and interested, while others took the game more seri- ously. Another constraint is posed by current assessment methods. Current high-stakes science tests do not accurately measure the complex understand- ings and skills developed by high-quality simulations and games (Quellmalz et al., 2009), yet current education policy focuses on student performance on these high-stakes tests. This can discourage the use of simulations and games. For example, science curriculum coordinators for three large urban districts refused to allow teachers to use River City because an emphasis on science inquiry might interfere with students doing well on content-oriented high-stakes science tests (Clarke and Dede, 2009). Although science classrooms offer opportunities for research designs that control some variables, obtaining permission to do research in schools is typically very difficult. For example, in taking the River City curriculum to scale, the developers had to satisfy one school district that demanded three times the documentation that the Harvard University institutional review

OCR for page 57
4 Learning Science Through Computer Games and Simulations board (IRB) required, mandated customized changes to the researchers’ standard letters of consent approved by the Harvard IRB, and took almost a year to reach a favorable decision. Another district required researchers to be fingerprinted by the district, because the state refused to accept finger- prints done elsewhere. Other challenges arose in school districts due to breakdowns in internal communications between the curriculum, research, and technical departments. ALTERNATIVE APPROACHES TO EXPANDING CLASSROOM USE Experts have proposed alternative approaches to overcome these constraints and realize the opportunities for using simulations and games in classroom settings. For example, to address the constraint that teachers sometimes undercut the intended goals of a simulation or game, Dede (2009c) emphasized the value of teacher learning, both formal and informal. Teacher learning improves the fidelity of implementation of the curriculum. Among teachers using River City, the number of years of experience implementing the curriculum was significantly correlated with both greater teacher com- fort with it and better learning outcomes for students. In addition, a large majority (94 percent) of teachers rated the developers’ 4-hour online pre- implementation training as useful. Trainers working in the field to support River City reported fewer problems with teachers who participated in the developers’ professional development. Students of teachers who were trained online performed significantly better on the posttest, on average (controlling for gender, socioeconomic status, reading level, and pretest performance), than students whose teachers were trained face to face. These findings on successful online training build on other research demonstrating the effectiveness of several models of online professional development (Dede, 2006; Falk and Drayton, 2009). Such research could lead to the emergence of new models of online professional development to help teachers adapt science games and simulations for effective use in their particular situations (Dede, 2009b). To address technology constraints, the River City team included a part- time technology specialist to handle the unique school-by-school and district- by-district network configurations. When technical problems arose, science teachers reported that often their students were adept at resolving them. Horwitz (2009) suggests that both technology and assessment constraints could be addressed by outsourcing technology services to an educational service provider. The service provider would provide updated hardware and 2Schools systems and developers are exploring web-based delivery of games and simula- tions to avoid the need to install games on school networks (see Chapter 6).

OCR for page 57
Simulations and Games in the Classroom  software to support continued innovation in simulations and games and would maintain data on students’ progress, as measured by embedded performance assessments, in secure databases. More broadly, financially self-sustaining educational service providers could provide simulations, games, and related curriculum, instruction, and assessment scaffolds to schools on an ongoing basis. These entities could potentially address the problem that technological innovations rarely last beyond the time frame of the grant-funded project that created them. However, the logistics and business models of this approach have not yet matured. Despite these possibilities to overcome constraints, Dede (2009c, p. 11) concluded that “current educational systems pose formidable challenges to implementation at scale.” Noting that many variables influence adoption (or avoidance) of any educational intervention, he observed that scaling up an intervention is very difficult, even if it has been demonstrated as effective, economical, and logistically practical in a few classrooms (Dede, Honan, and Peters, 2005; Venkatesh and Bala, 2008). One important variable influencing adoption is the learning goal (or goals) of the game or simulation. A simulation focusing on development of content knowledge—which is a widely accepted goal in current science education—may be less challenging, but also less transformative, for a teacher to use than a game that engages students in authentic scientific inquiry in a complex virtual environment (Dede, 2009b). The challenges of inquiry teaching and learning were noted earlier in this chapter. At the same time, state science standards and assessments emphasizing science facts encour- age teachers to emphasize content knowledge, leaving little time for inquiry. Science teachers who use a game to engage students in inquiry will require extensive support to transform their teaching practices in the face of these challenges. An Evolutionary Approach In a response to Dede, Culp (2009) suggests that wider use of simulations and games to enhance learning might best be realized through incremental, evolutionary change, rather than dramatic shifts in teaching and learning approaches. Drawing on three decades of research on the integration of technology into classrooms, Culp (2009) argues that adoption of any edu- cational intervention is driven not only by the factors discussed above—the personal capacity of teachers and the institutional capacity of schools and 3In a few cases, private foundations have solicited proposals from learning technology projects that are nearing the end of their federal grants. Foundations have selected the most promising proposals and provided funding to prepare the technologies for large-scale deploy- ment and also to create a business plan.

OCR for page 57
 Learning Science Through Computer Games and Simulations districts—but also by other important realities. These realities, Culp argues, are often ignored when developers create electronic games for research purposes or to demonstrate proof of concept models. One of these realities is teachers’ and administrators’ view of the alignment between their local learning goals and priorities and the perceived goals of the proposed inter- vention. Another is teachers’ perceptions of the extent of alignment between their students’ existing, persistent learning needs and the perceived goals and effectiveness of the proposed intervention. Culp (2009) pointed to technological tools that have been widely adopted in schools, including graphing calculators, probes linked to computers, and electronic whiteboards (Roschelle, Patton, and Tatar, 2007). Each of these tools is a discrete, freestanding piece of technology designed to address spe- cific challenges or sticking points in learning that teachers are very familiar with. In addition, each is flexible and adaptable to many different curricular contexts and can be used simply at first and with growing sophistication over time. Based on this analysis, Culp (2009) proposes using the design process to support incremental adoption of simulations and games. Specifically, she advocates designing simulations and games to be discrete, flexible, and adaptable by teachers and including expert teacher perspectives in the design process. In addition, she proposes mobilizing time and support for teachers to explore connections between specific electronic games or simulations and their own unique curriculum and teaching goals. An Integrative Approach Songer (2009) expressed another perspective, based on 15 years of ex- perience in developing and testing simulation-based learning environments in Detroit Public Schools. She proposes that integration of technology into schools is critical to transform current science education. In her view, neither using technology to supplement the current curriculum nor conducting com- parative studies of using technology versus no technology will dramatically improve students’ science learning. Instead, she suggests integrating simula- tions and games into science instruction by following design principles that are, for the most part, identical to the basic design principles for supporting deep science learning more generally. These general design principles include focusing on a few big ideas in science (Linn et al., 2000); providing learners with systematic guidance to develop more complex ideas, including scaffolds for both content learning and inquiry reasoning; and allowing learners to systematically revisit and deepen their understandings. Songer’s research team has applied these general principles to develop- ment of digital learning environments built on publicly available scientific databases that are revised to be educationally focused and accessible to

OCR for page 57
Simulations and Games in the Classroom  middle school learners. For example, the Animal Diversity Web designed for adult use has been revised to create an interactive Critter Catalogue that has been shown to support science process skills and understanding, questioning, and development of scientific explanations by fourth through sixth graders (Songer, Kelcey, and Gotwals, 2009). Students using these environments have demonstrated growth in content understanding as well as complex reasoning. In addition to the general design principles, Songer identified three instructional design principles that she sees as unique to technology-based learning: (1) engage learners in data gathering, modeling, and sharing; (2) support social construction of knowledge among learners; and (3) engage learners in role playing (in her research, students become authorities on the revised data sets). Songer concluded that simulations are essential to support students in thinking deeply about core science topics. CONCLUSIONS Individuals interact with simulations and games in a variety of different contexts, comprised of interrelated physical, social, cultural, and techno- logical dimensions. These contexts influence the extent of interaction with simulations and games and whether, and to what extent, these interactions support learning. Conclusion: The context in which a simulation or game is used can signifi-­ cantly shape whether and how participants learn science. Simulations and games have great potential to improve science learning in K-12 and undergraduate science classrooms. They can individualize learning to match the pace, interests, and capabilities of each particular student and contextualize learning in engaging virtual environments. Because schools serve all students, increased use of simulations and games in science class- rooms could potentially improve access to high-quality learning experiences for diverse urban, suburban, and rural students. Conclusion: Schools offer unique opportunities to embed a game or simu-­ lation in a supportive learning environment, to improve equity of access to high-­quality learning activities, to individualize learning, and to increase the use of games for science learning. In K-12 education, inadequate infrastructure, institutional and organiza- tional constraints, and lack of teacher and administrator understanding and 4This learning environment does not include simulations.

OCR for page 57
 Learning Science Through Computer Games and Simulations preparation pose challenges for using games and simulations to support learning. Simulations have been taken up more in higher education than in elementary or secondary education. There are different models of implementing games and simulations in schools. In an evolutionary model, they can be designed to increase the productivity of learning without dramatic changes to current science teach- ing approaches. In other models, they can be designed to more dramatically transform science teaching and learning, advancing science process skills as well as conceptual understanding. The more transformative models require greater support for schools and teachers, and they may infuse technology into the whole instructional environment. Conclusion: There are currently many obstacles to embedding games and simulations in formal learning environments. However, alternative models for incorporating games and simulations in classrooms are beginning to emerge. Science educational standards that include many topics at each grade level pose a constraint to increased use of simulations and games in K-12 science classrooms. Simulations and games are often designed to support learners in thinking deeply about selected science concepts by engaging them in active investigations, but teachers and administrators may avoid using them because of the pressure to cover all of the topics included in current standards within limited time frames. Conclusion: Well-­designed and widely accepted science standards, focusing on a few core ideas in science, could help to reduce the barriers to wider use of simulations and games posed by current state science standards. Such standards might potentially encourage the use of simulations and games.