Science simulation

Draft

Introduction

Science simulations are computer simulations that focus on science areas, in particular: physics, biology, chemistry, and earth science.

See also:

• computer simulation]
• math simulation

PHET Interactive Simulations

“Founded in 2002 by Nobel Laureate Carl Wieman, the PhET Interactive Simulations project at the University of Colorado Boulder creates free interactive math and science simulations. PhET sims are based on extensive education research and engage students through an intuitive, game-like environment where students learn through exploration and discovery.” Interactive Simulations For Science And Math (retr. April 24, 2019).

According to Perkins et al. (2012), the PhET project is anchored in constructivist and socio-constructivist learning theory. Sims are designed to “encourage and support the active process of constructing knowledge, an interactive exchange between the student(s) and the content, rather than transmitting knowledge.”. This, and an approach to implicit scaffolding leads to the following design goals of PhET simulations: (Perkins et al. (2012:437):

1. Engage in productive, scientist-like exploration. Students will pose their own questions, design experiments, make predictions, and use evidence to support and refine their ideas.
2. Assume and sense ownership of the learning experience. Students will perceive a sense of autonomy and choice, where they can direct their exploration and use of the sim.
3. Achieve conceptual learning. Students will develop an understanding of and use expert models, including visual representations. They will infer cause-effect relationships and use multiple representations.
4. Make connections to everyday life. Students will connect formal science ideas to their everyday life experiences, recognizing how science helps understand the world around us.
5. See science as accessible and understandable. Students will engage in authentic science practices and develop their identity as a scientific thinker. They will generate further interest in science.
6. Have fun. Students will engage in serious play (Rieber 1996) and productive “messing about” (Hawkins 1965). These goals influence every PhET sim, shaping the approaches used and choices made during design.

Simulations are developed using an user and research-centered design method based similar to Wiggins backwards design: “Central to the design process is a research base; we draw from education literature to inform sim design and then contribute our own research findings. Built into this development approach is an iterative process of testing and redesign for each sim, and an iterative process that evolves the broader design principles and approaches over the course of creating more than 100 sims.”. Besides socio-constructivist learning theory and implicit guidance, simulations also are based on design theory and cognitive load theory . Interviews with students are also of critical importance.

The PhET team, according to Perkings (2012:439:440) developed the following set of general design principles that we summarize below:

• Make sims highly interactive: Users can change key parameters (e.g. adjusting friction or adding water), use tools to make measurements and observations, and navigate and modify the environment (e.g. choosing track shapes, switching tabs, or showing/hiding controls).

• Provide dynamic feedback: “In response to each interaction, the sim provides real-time, immediate visual

feedback of the resulting changes (e.g., objects or readouts can be increasing or decreasing, slowing down or speeding up, changing forms, etc.). Feedback is critical to testing ideas, inferring cause-effect relationships, and developing a conceptual understanding.”

• Use multiple, linked representations: users can coordinate across representations (e.g., physical representations, graphs, numbers, vectors, text, etc.) and see the invisible (e.g., atoms, molecules, electric fields, etc).

• Allow actions that would be difficult or impossible: E.g. slowing down time, or directly manipulating individual atoms.

• Provide an intuitive interface: “Significant attention is focused on creating a highly intuitive and inviting user

interface – one useable without explicit instruction.” Simulations use commonly used controls like buttons and slides, drag and drop. Text is mostly used to label controls.

• Use implicit scaffolding: See above.

• Emphasize real world connections: “Where possible, sim designs connect to everyday life experiences. We adopt this approach with several goals in mind: 1) to reduce cognitive load and cue intuitive interaction, 2) to build connections to students prior knowledge and understanding, and 3) to increase motivation by making the context relevant to students’ experiences and cuing their natural curiosity of ‘what if?’ and ‘why?’ questions.”

• Create a game-like environment that is engaging, fun, and open: the environment should trigger curiosity, provide a sens of challenge and engage students to interact at length.

Podolefsky, Perkins & Adams (2010) describe a qualitative study that investigates student engagement in an implicitly scaffolded physics simulation. They conclude:

Fostering engaged exploration depends on building implicit scaffolding into education materials. In the sims, this scaffolding consists of affordances, productive constraints, analogies, and representations of phenomena that allow students to construct understanding of science topics.In the Wave Interference sim, students can explore the sim freely, choosing what order to use the representations. Since no two students use a sim in exactly the same way, this flexibility can actually be advantageous, and in practice we find that students tend to explore the sim in ways that are intuitive for them. This freedom to proceed along their own path is critical to students exploring like a scientist. How-ever, this exploration is implicitly guided by building sims so that students are likely to interact with certain sim elements first, and more likely to see some visual representations be-fore others. In this way, students tend to make connections between representations and arrive at interpretations that are useful for understanding scientific ideas. Furthermore, representations are presented in such a way that student interpretations of these representations, and hence their intuitions about phenomena, are productive for generating ideas about the science.

Guiding

As also discussed in the guided discovery community, giving a "pure" simulation to a student is not very effective. Both researchers and practitioners agree that learners need some explicit or implicit guidance and scaffolding. The question is how and how much. “When used in class, simulations become part of an integrated system of resources that guide learning – including implicit guidance from the simulation, as well as explicit guidance from the written activity and the instructor (Hennessy et al., 2006; Lee et al., 2006; Chang et al., 2008; Khan, 2011). While much research has contributed to present knowledge of optimal design elements for interactive simulations (Lee et al.,2006; Adams et al., 2008b; Plasset al., 2009), less is known about how the amount, timing, and type of guidance affects students’ interaction, interpretation, and learning with these educational tools” (Chamberlain et al. (2014:628) .

Perkins et al. (2012) highlight the overarching importance and use of implicit scaffolding within sims. “Explicit scaffolding or guidance is ubiquitous in education. Within science instruction, an environment with significant explicit guidance can result in students merely following directions as opposed to engaging in sense- making and productive inquiry. Implicit scaffolding aims to retain a student’s sense of autonomy while creating an environment in which multiple, natural, investigative pathways and questions lead toward the desired knowledge acquisition. In short, implicit scaffolding guides without students feeling guided.”

Chamberlain et al. (2014:628) compared three levels of guidance: heavy, medium and light. “{{{1}}}”

Bibliography

Other

Adams W. K., Reid S., LeMaster R., McKagan S. B., Perkins K. K.,Dubson M. and Wieman C. E., (2008a), A study of educationalsimulations part I – engagement and learning,J. Interact.Learn. Res.,19, 397–419.

• Adams W. K., Reid S., LeMaster R., McKagan S. B., Perkins K. K.,Dubson M. and Wieman C. E., (2008b), A study of educationalsimulations part II – interface design,J. Interact. Learn. Res.,19,551–577

• Chang K.-E., Chen Y.-L., Lin H.-Y. and Sung Y.-T., (2008), Effectsof learning support in simulation-based physics learning,Comput. Educ.,51, 1486–1498

• Hennessy S., Deaney R. and Ruthven K., (2006), Situatedexpertise in integrating use of multimedia simulation intosecondary science teaching,Int. J. Sci. Educ.,28(7), 701–732.

• Khan S., (2011), New pedagogies on teaching science withcomputer simulations,J. Sci. Educ. Technol.,20, 215–232.

• Lee H., Plass J. L. and Homer B. D., (2006), Optimizing cognitiveload for learning from computer-based science simulations,J. Educ. Psychol.,98(4), 902–913.