While video games have become a source of excitement for educational designers, creating informal game experiences that players can draw on when thinking and reasoning in non-game contexts has proved challenging. In this paper we present a design principle for creating educational video games that enables players to draw on knowledge resources gained in-game to reason about non-game phenomena. Games that incorporate this design principle, which we call constructible authentic representations, engage players in the construction of artifacts that are visually and epistemologically aligned to tools and representations utilized in the target domain. We illustrate this principle with a study of six children (ages 7–13) playing a racing video game of our own design. Players that struggled with a formal graphing task before playing the game showed improvement on the same task in post-game interviews creating qualitatively correct velocity versus time graph that incorporated key kinematic features such as moments of constant velocity and varying degrees of acceleration. An analysis of pre- and post-game clinical interviews also revealed that players more fluidly drew on a variety of knowledge resources when reasoning about the game, real world, and formal representations. We hypothesize that designing games to include constructible authentic representations may allow for the creation of educational video games that can survive in the non-school gaming ecosystem.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Warm-up questions centered on feedback on the game rather than on commercial games participants have played.
The speedometer does in fact measure speed rather that velocity. We chose to use the term “velocity” in the game and in the graphing task because of its alignment with formal terminology that may be used in the classroom.
We provided a brief description of how this second prototype game, Particles!, incorporates the CAR principle in Sect. 1.2.
Annetta, L. A. (2008). Video games in education: Why they should be used and how they are being used. Theory into Practice, 47(3), 229–239.
Bamberger, J. (1996). Turning music theory on its ear: Do we hear what we see; do we see what we say? International Journal of Computers for Mathematical Learning, 1, 33–55.
Barab, S., Sadler, T. D., Heiselt, C., Hickey, D., & Zuiker, S. (2007a). Relating narrative, inquiry, and inscriptions: Supporting consequential play. Journal of Science Education and Technology, 16(1), 59–82.
Barab, S., Thomas, M., Dodge, T., Carteaux, R., & Tuzun, H. (2005). Making learning fun: Quest Atlantis, a game without guns. Educational Technology Research and Development, 53, 86–107.
Barab, S., Zuiker, S., Warren, S., Hickey, D., Ingram-Goble, A., Kwon, E., et al. (2007b). Situationally embodied curriculum: Relating formalisms and contexts. Science Education, 91(5), 750–782. doi:10.1002/sce.20217.
Barendregt, W., & Bekker, T. M. (2011). The influence of the level of free-choice learning activities on the use of an educational computer game. Computers & Education, 56(1), 80–90. doi:10.1016/j.compedu.2010.08.018.
Behesthi, E., Jona, K., Horn, M., Trouille, L., Weintrop, D., & Wilensky, U. (2013). The physics of angry birds. CT-STEM Group. http://ct-stem.northwestern.edu/lesson-plans.
Boucher-Genesse, F., Riopel, M., & Potvin, P. (2011). Research results for Mecanika, a game to learn Newtonian concepts. In C. Steinkuhler, C. Martin, & A. Ochsner (Eds.), Proceedings of the 7th Annual Games, Learning, and Society Conference. Madison, WI.
Brofenbrenner, U. (1979). The ecology of human development: Experiment by nature and design. Cambridge, MA: Harvard University Press.
Cheng, P. C.-H. (2011). Probably good diagrams for learning: Representational epistemic recodification of probability theory. Topics in Cognitive Science, 3(3), 475–498.
Clark, D. B., & Martinez-Garza, M. (2012). Prediction and explanation as design mechanics in conceptually integrated digital games to help players articulate the tacit understandings they build through game play. In C. Steinkuhler, K. Squire, & S. Barab (Eds.), Games, learning, and society: Learning and meaning in the digital age. Cambridge: Cambridge University Press.
Clark, D. B., Nelson, B., Chang, H., Martinez-Garza, M., Slack, K., & D’Angelo, C. M. (2011). Exploring Newtonian mechanics in a conceptually-integrated digital game: Comparisons of learning and affective outcomes for students in Taiwan and the United States. Computers & Education, 57, 2178–2195.
Clark, D. B., Nelson, B., D’Angelo, C. M., Slack, K., & Menekse, M. (2010). SURGE: Assessing students’ intuitive and formalized understandings about kinematics and Newtonian mechanics through immersive game play. Presented at the Annual Meeting of the American Educational Research Association, Denver, CO.
Collins, A. (1995). Design issues for learning environments. In S. Vosniadou, E. de Corte, H. Mandle, & G. Robert (Eds.), International perspectives on the psychological foundations of technology-based learning environments (pp. 347–361). Hillsdale, NJ: Lawrence Erlbaum.
Cooper, S., Dann, W., & Pausch, R. (2000). Alice: A 3-D tool for introductory programming concepts. Journal of Computing Sciences in Colleges, 15, 107–116.
diSessa, A. A. (1993). Toward an epistemology of physics. Cognition and Instruction, 10, 105–225.
diSessa, A. A., Hammer, D., Sherin, B., & Kolpakowski, T. (1991). Inventing graphing; Meta-representational expertise in children. Journal of Mathematical Behavior, 10, 117–160.
Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan.
Gee, J. P. (2007). Good video games and good learning. New York, NY: Peter Lang.
Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: A general role for analogical encoding. Journal of Educational Psychology, 95, 393–408.
Gick, M. L., & Holyoak, K. J. (1980). Analogical problem-solving. Cognitive Psychology, 12, 306–355.
Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38.
Ginsberg, H. P. (1997). Entering the child’s mind: The clinical interview in psychological research and practice. New York: Cambridge University Press.
Habgood, J. M. P., & Ainsworth, S. E. (2011). Motivating children to learn effectively: Exploring the value of intrinsic integration in educational games. Journal of the Learning Sciences, 20, 169–206.
Hammer, D., & Elby, A. (2002). On the form of personal epistemology. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemology: The psychology of beliefs and knowledge and knowing (pp. 169–190). Mahwah, NJ: Erlbaum.
Hammer, D., Elby, A., Scherr, R. E., & Redish, E. F. (2005). Resources, framing, and transfer. In J. Mestre (Ed.), Transfer of learning from a modern multidisciplinary perspective (pp. 89–120). Greenwich, CT: Information Age Publishing.
Holbert, N. (2009). Learning Newton while crashing cars. Presented at the Games, Learning, and Society 5.0, Madison, WI.
Holbert, N. (2013). Reimagining game design (RiGD): Exploring the design of constructible representations for science reasoning (doctoral dissertation). Evanston, IL: Northwestern University.
Holbert, N., & Wilensky, U. (2010a). FormulaT racing. Evanston, IL: Center for Connected Learning and Computer-based Modeling.
Holbert, N., & Wilensky, U. (2010b). FormulaT racing: Combining gaming culture and intuitive sense of mechanism for video game design. In K. Gomez & J. Radinsky (Eds.), Proceedings of the 9th International Conference of the Learning Sciences. Chicago, IL.
Holbert, N., & Wilensky, U. (2011). FormulaT racing: Designing a game for kinematic exploration and computational thinking. In C. Steinkuhler, C. Martin, & A. Ochsner (Eds.), Proceedings of 7th Annual Games, Learning, and Society Conference. Madison, WI.
Holbert, N., & Wilensky, U. (2012). Particles!. Evanston, IL: Center for Connected Learning and Computer-based Modeling.
Itō, M. (2008). Education vs. entertainment: A cultural history of children’s software. In K. Salen (Ed.), The ecology of games: Connecting youth, games, and learning (pp. 89–116). Cambridge, MA: MIT Press.
Itō, M. (2010). Hanging out, messing around, and geeking out: Kids living and learning with new media. Cambridge, MA: MIT Press.
Kafai, Y. B. (1996). Learning design by making games: Children’s development of design strategies in the creation of a complex computational artifact. In Y. B. Kafai & M. Resnick (Eds.), Constructionism in practice: Designing, thinking, and learning in a digital world. Mahwah, NJ: Lawrence Erlbaum.
Kelleher, C., & Pausch, R. (2006). Lessons learned from designing a programming system to support middle school girls creating animated stories. In J. Grundy & J. Howse (Eds.), IEEE symposium on visual languages and human-centric computing (pp. 165–172). Brighton, UK.
Ketelhut, D. J., Clarke, J., & Nelson, B. C. (2010). The development of river city, a multi-user virtual environment-based scientific inquiry curriculum: Historical and design evolutions. In M. J. Jacobson & P. Reimann (Eds.), Designs for learning environments of the future (pp. 89–110). US: Springer.
Lenhart, A., Kahne, J., Middaugh, E., Macgill, A. R., Evans, C., & Vitak, J. (2008). Teens, video games, and civics. PEW Internet & American Life Project.
Levy, S. T., & Wilensky, U. (2009). Students’ learning with the connected chemistry (CC1) curriculum: Navigating the complexities of the particulate world. Journal of Science Education and Technology, 18, 243–254.
Mestre, Jose. (2002). Transfer of learning: Issues and research agenda. Arlington, VA: National Science Foundation.
Minsky, M. (1986). The society of mind. New York: Simon & Schuster.
Nemirovsky, R., Tierney, C., & Wright, T. (1998). Body motion and graphing. Cognition and Instruction, 16, 119–172.
Noss, R., & Hoyles, C. (1996). Windows on mathematical meanings: Learning cultures and computers. Dordrecht: Kluwer Academic Press.
Papastergiou, M. (2009). Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation. Computers & Education, 52(1), 1–12.
Papert, S. (1980). Mindstorms: Children, computers and powerful ideas. New York: Basic Books.
Papert, S. (2000). What’s the big idea? Toward a pedagogy of idea power. IBM Systems Journal, 39(3.4), 720–729.
Papert, S., & Harel, I. (1991). Situating constructionism. In S. Papert & I. Harel (Eds.), Constructionism. New York: Ablex Publishing.
Piaget, J. (1929). The child’s conception of the world. London: Rowman & Littlefield.
Pratt, D., & Noss, R. (2010). Designing for mathematical abstraction. International Journal of Computers for Mathematical Learning, 15(2), 81–97.
Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60–67.
Robertson, J., & Howells, C. (2008). Computer game design: Opportunities for successful learning. Computers & Education, 50(2), 559–578. doi:10.1016/j.compedu.2007.09.020.
Roschelle, J., Kaput, J. J., & Stroup, W. (2000). SimCalc: Accelerating students’ engagement with the mathematics of change. In M. J. Jacobson & R. B. Kozma (Eds.), Innovations in science and mathematics education: Advanced designs for technologies of learning (pp. 47–76). Hillsdale, NJ: Earlbaum.
Russ, R. S., Lee, V. R., & Sherin, B. L. (2012). Framing in cognitive clinical interviews about intuitive science knowledge: Dynamic student understandings of the discourse interaction. Science Education, 96(4), 573–599. doi:10.1002/sce.21014.
Sherin, B. (2000). How students invent representations of motion: A genetic account. Journal of Mathematical Behavior, 19, 399–441.
Squire, K. (2006). From content to context: Videogames as designed experience. Educational Researcher, 35, 19–29.
Squire, K., & Barab, S. (2004). Replaying history: Engaging urban underserved students in learning world history through computer simulation games. In Proceedings of the 6th International Conference on the Learning Sciences (pp. 505–512).
Tasar, M. H. (2010). What part of the concept of acceleration is difficult to understand: The mathematics, the physics, or both? ZDM, 42, 469–482.
The Alice Team. (n.d.). Alice. What is Alice? http://www.alice.org/index.php?page=what_is_alice/what_is_alice.
Trowbridge, D. E. (1989). Graphs and tracks: An application of manipulable graphics. Academic Computing, May, 24–25.
Trowbridge, D. E., & McDermott, L. C. (1981). Investigation of student understanding of the concept of acceleration in one dimension. American Journal of Physics, 49, 242–253.
Valve Corporation. (2013). Teach with portals. http://www.teachwithportals.com.
Wilensky, U. (1991). Abstract meditations on the concrete and concrete implications for mathematics education. In I. Harel & S. Papert (Eds.), Constructionism. Norwood, NJ: Ablex Publishing Corp.
Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories–and embodied modeling approach. Cognition and Instruction, 24, 171–209.
Wilkerson-Jerde, M. H., & Wilensky, U. (2010). Restructuring change, interpreting changes: The deltatick modeling and analysis toolkit. In J. E. Clayson (Ed.), Proceedings of constructionism 2010. Paris, France.
The authors would like to thank Bruce Sherin, Reed Stevens, Rosemary Russ, Corey Brady, Michael Horn, Pryce Davis, David Weintrop, and all members of the CCL for their insightful comments on this work.
About this article
Cite this article
Holbert, N.R., Wilensky, U. Constructible Authentic Representations: Designing Video Games that Enable Players to Utilize Knowledge Developed In-Game to Reason About Science. Tech Know Learn 19, 53–79 (2014). https://doi.org/10.1007/s10758-014-9214-8
- Video games