Integrating Sims in High School Science Classroom - Literature Review

Literature Review

During the last few decades, science education has been highly influenced by constructivism and constructivist approaches to teaching and learning science has been widely promoted (Roscoe, 2004). This perhaps can be attributed to the trend that school curricula tend to be based on learner-centered constructivism to promote students who can function successfully in real-world contexts. As learner-centered psychological principles provide a framework for developing and incorporating the components of new designs for schooling, it has been widely acknowledged that learning is influenced by environmental factors including technology and instructional practices and is most effective within the context of real-world learning situations (American Psychological Association, 1997). The learner-centered approaches are associated with learner control characterized by learners making choices in the pacing, sequence and selection of instructional materials (Merrill, 1983; Reigeluth & Stein, 1983). Intrinsic motivation, which is proved as associated with high educational achievement and enjoyment by students, can be facilitated on tasks that are comparable to real-world situations and meet needs for choice and control (APA, 1997).

With the rapid advancement of technological innovation, efforts in integrating new instructional technologies into learner-centered teaching have been proved successful (Leider, 1999). One evidence is that computer and Internet technology continues to displace the brick-and-mortar classroom and online schooling came to be one of today’s fastest-growing education sectors, with some half-million course enrollments nationwide (Dillon, 2006). As a consequence, e-learning environments such as simulations have become a widely used science teaching tool that enable teachers and learners to explore new domains, make predictions, design experiments, and interpret results in science class (Steinberg, 2000). Following the first era (Observation Era) and the second era (Experimentation Era), science education has now entered its third era – the Era of Simulation (Blanton, 2006). From K-12 schools to higher education institutions, simulation-based instructional designs such as virtual laboratories, educational games, and cyber classrooms provide new teaching and learning experiences for educators and learners. Recently reported by the New York Times, a virtual chemistry laboratory alone has about 150,000 high school students enrolled around the nation, doing experiments that would be too costly or dangerous to do at their local school settings (Dillon, 2006).

Likewise, the Epic White Paper on simulations (Clark, 2006) articulates that while time, cost and danger would be issues that hinder the notion of learning through experience, simulations, by contrast, can help achieve that notion with quick, cheap and safe solutions. In detail, the white paper lists the advantages of simulations as following:

Simulations, although difficult to design, have some significant advantages over other methods of delivering learning. These benefits include: elimination of risk and danger, elimination of the need for costly sites and equipment, lower environmental impact, the ability to do things that are impossible in the real world, increase in learner motivation, ability to learn through repeated failure, acceleration of learning, integration of knowledge and skills, deepened learning, increased retention through reinforcement and realism, better transfer of learning to real-world, anytime, anywhere access to learning content, cheap replication and distribution, better assessment through actual performance, and better evaluation of performance. (p. 4)

Simulations can provide animated, interactive, and game-like environments in which students learn through exploration. For example, physics teachers use simulations to establish the connections between real-life phenomena and the underlying science, mapping the visual and conceptual models of expert physicists accessible to students (Perkins, Adams, Dubson, Finkelstein, Reid, Wieman, & LeMaster, 2006). Scatteia (2005) found that space-themed simulation videogames could effectively promote space because they represent reality “not only as a collection of images or text, but also as a dynamic system that can evolve and change.” Features in this genre, which is labeled with “edutainment,” include “a very high level of realism in the reproduction of a real space system” and “a steep learning curve, as a direct result from the level of realism,” contributing significantly to delivering educational scientific messages.

The advantages of simulation use in education, on the one hand, have made it a useful supplemental approach for science teachers. The virtuality of its nature, on the other hand, has aroused wide concerns over the learning authenticity when the quality of educational simulations comes under experts’ scrutiny. A recent criticism focusing on virtual laboratories, for instance, is questioning that whether the hands-on experiences can be substituted with the laboratory practice on the cyberspace (Dillon, 2006). Harasim, Hiltz, Teles, and Turoff (1995) argue that software simulations are not satisfactory for achieving learning comprehension in many laboratory experiments. Others (Hamza, Alhalabi, Hsu, Larrondo-Petrie, & Marcovitz, 2002) believe that while simulations have a significant place in distance education, they can hardly replace the need for real laboratory experiences that tend to simulate and intensify all types of learning skills in students. The lack of real response of real physical elements to real inputs suggests that simulation software should be used for a limited set of experiments. In situations when real labs are not as appropriate or effective, however, simulations provide substantial assistance:

Simulations are appropriate for teaching in a controlled environment, such as teaching theoretical concepts, confronting students with their misconceptions, and teaching students with limited metacognitive skills. When the concepts accentuate theory, a well-designed simulation package will meet instructional objectives. (Hamza et al, 2002, p.188)

While Hamza et al (2002) focus on simulation-related concerns such as designers’ subjectivity on the simulation design, software error, limitation by the scope of distance learning parameters, lack of feelings of spontaneity, and absence of the excitement and interest, one very realistic limitation of simulation would be associated with the extensive cost and technological support that are critical to produce and implement simulations. There is little doubt that it is harder to produce and launch a successful instructional design with simulation technology comparing with other electronic approaches, because both the design and update of simulations are very costly and time-consuming (Silverthorne, 2002). From a cost-effectiveness point of view, however, the benefits of the use of simulation in e-learning outweigh this limitation as we compare the development cost to the resources saved, the training time reduced, the safety ensured, and the unique motivational quality in learning received (Clark, 2006).

A unique voice among the critics, Clark (2006) articulates that the biggest limitation to the wide spread of simulation use is neither technological-bound, nor cost-related, but of our limited imagination, as “the field of simulations is much wider and more diverse than many people think.” This implies that simulations should not only be designed innovatively, but also implemented creatively. Furthermore, because using computer simulations in class instruction requires a fundamentally different way than the knowledge gain with original materials, their impact would largely depend on the details of the program and the way in which it is implemented (Steinberg, 2000).

Indeed, it is the elaborate design, careful selection, and on-task delivery that really matter in terms of creating an effective learner-centered science classroom with the simulation technology. Despite of the concerns on time, cost and virtuality, the immersivity and edutainability of computer simulations will put promises in engaging students in authentic learning.

Reference

American Psychological Association's Board of Educational Affairs (1997, November). Learner-Centered Psychological Principles: A Framework for School Redesign and Reform. Retrieved June 2006 from http://www.apa.org/ed/cpse/LCPP.pdf

Blanton, P. (2006). Incorporating simulations and visualizations into physics instruction. The physics teacher, 44(3), 188-189. Retrieved on October 30, 2006, from http://ejournals.ebsco.com/direct.asp?ArticleID=46FBA98D1C2F8FCF940B

Clark, D. (2006). Simulations and e-learning. Epic whitepaper. Retrieved on November 1, 2006, from http://www.epic.co.uk/content/resources/white_papers/sims.htm

Dillon, S. (2006). No test tubes? Debate on virtual science classes. The New York Times. Retrieved on October 24, 2006, from http://www.nytimes.com/2006/10/20/ education/20online.html?_r=1&oref=slogin

Hamza, M. K., Alhalabi, B., Hsu, S., Larrondo-Petrie, M. M., & Marcovitz, D. M. (2002). Remote labs: The next high-tech step beyond simulation for distance education. Computers in the schools, 19 (3-4), 171-190.

Harasim, L., Hiltz, S. R., Teles, L., & Turoff, M. (1995). Learning networks: A field guide to teaching and learning online. Cambridge: MIT Press.

Leider, S. (1999). Successfully Integrating Technology. ERIC Digest. ED422989. Retrieved July 19, 2007 from http://www.ericdigests.org/1999-2/technology.htm

Merrill, M. D. (1983). Component display theory. In C. Reigeluth (ed.) Instructional design theories and models. Erlbaum, Hillsdale, NJ.

Perkins, K., Adams, W., Dubson, M., Finkelstein, N., Reid, S., Wieman, C., & LeMaster, R. PhET: Interactive simulations for teaching and learning physics. The physics teacher, 44 (1), 18-23. Retrieved on November 1, 2006, from http://ejournals.ebsco.com/direct.asp?ArticleID=4309993119F1F437D8BF

Reigeluth, C., & Stein, F. (1983). The elaboration theory of instruction. In C. Reigeluth (ed.), Instructional design theories and models. Hillsdale, NJ: Erlbaum.

Roscoe, K. (2004). Lonergan's Theory of Cognition, Constructivism and Science Education. Science & Education, 13 (6), 541-551. Retrieved July 19, 2007 from http://ejournals.ebsco.com/direct.asp?ArticleID=3QTD7D42TUYEDGH1N9P5

Scatteria, L. (2005). Space-themed videogames: An effective way to promote space. The electronic library, 23(5), 553-566.

Silverthorne, S. (2002). Marrying distance and classroom education. Harvard Business School working knowledge (online). Retrieved on November 2, 2006, from http://hbswk.hbs.edu/item/3219.html

Steinberg, R. N. (2000). Computers in teaching science: To simulate or not to simulate? American Journal of Physics, 68 (S1), S37–S41. Retrieved July 19, 2007 from http://scitation.aip.org.proxy.bsu.edu/journals/doc/AJPIAS-ft/vol_68/iss_S1/ S37_1.html