Testing the Impact of a Pre-instructional Digital Game on Middle-Grade Students’ Understanding of Photosynthesis

• Alderman, M. K. (2013). Motivation for achievement: Possibilities for teaching and learning. New York, NY: Routledge.

  Google Scholar 

• Bloom, H. S., Richburg-Hayes, L., & Black, A. R. (2007). Using covariates to improve precision for studies that randomize schools to evaluate educational interventions. Educational Evaluation and Policy Analysis, 29(1), 30–59.

  Article  Google Scholar 

• Bloom, H., Zhu, P., Jacob, R., Raudenbush, S., Martinez, A., & Lin, F. (2008). Empirical issues in the design of group-randomized studies to measure the effects of interventions for children. MDRC working papers on research methodology. New York, NY: MDRC.

• Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. In A. Iran-Nejad & P. D. Pearson (Eds.), Review of research in education: 24 (pp. 61–100). Washington, DC: American Educational Research Association.

  Google Scholar 

• Brophy, J. E. (2010). Motivating students to learn. New York, NY: Routledge.

  Google Scholar 

• Buckingham, D. (2009). Beyond technology: Rethinking learning in the age of digital culture. In J. Pettersen (Ed.), Youth media democracy: Perceptions of new literacies. Proceedings of the youth media democracy conference (pp. 37–43). Dublin, Ireland: Center for Social and Educational Research.

• Cameron, L. (2002). Metaphors in the learning of science: A discourse focus. British Educational Research Journal, 28(5), 673–688.

  Article  Google Scholar 

• Chi, M. T. H. (2008). Three types of conceptual change: Belief revision, mental model transformation, and categorical shift. In S. Vosniadou (Ed.), Handbook of research on conceptual change (pp. 61–82). Mahwah, NJ: Lawrence Erlbaum Associates.

  Google Scholar 

• Chi, M. T. H., Roscoe, R. D., Slotta, J. D., Roy, M., & Chase, C. C. (2011). Misconceived causal explanations for emergent processes. Cognitive Science, 36(1), 1–61.

  Article  Google Scholar 

• Clark, D. B., Tanner-Smith, E., & Killingsworth, S. (2013). Digital games for learning: A systematic review and meta-analysis, Preliminary executive summary and brief. http://www.sri.com/work/projects/glasslab-research.

• Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., & Boyle, J. M. (2012). A systematic literature review of empirical evidence on computer games and serious games. Computers & Education, 59(2), 661–686.

  Article  Google Scholar 

• Connolly, T. M., Stansfield, M., & Hainey, T. (2009). Towards the development of a games-based learning evaluation framework. In T. Connolly, M. Stansfield, & L. Boyle (Eds.), Games-based learning advancements for multisensory human computer interfaces: Techniques and effective practices (pp. 251–273). Hershey, PA: IGI Global.

  Chapter  Google Scholar 

• de Freitas, S., & Oliver, M. (2006). How can exploratory learning with games and simulations within the curriculum be most effectively evaluated? Computers & Education, 46(3), 249–264.

  Article  Google Scholar 

• Dede, C. (2009). Immersive interfaces for engagement and learning. Science, 323(5910), 66–69.

  Article  Google Scholar 

• Deke, J., Dragoset, L., & Moore, R. (2010). Precision gains from publically available school proficiency measures compared to study-collected test scores in education cluster-randomized trials (NCEE 2010-4003). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.

• Driver, R., Squires, A., Rushworth, P., & Wood-Robinson, V. (1993). Making sense of secondary science. London: Routledge.

  Google Scholar 

• Duit, R. (2009). Bibliography—STCSE: Students’ and teachers’ conceptions and science education. http://www.ipn.uni-kiel.de/aktuell/stcse/stcse.html.

• Enders, C. K. (2010). Applied missing data analysis. New York, NY: Guilford Press.

  Google Scholar 

• Fraser, B. J. (1981). TOSRA test of science-related attitudes handbook. Hawthorn, VIC: Australian Council for Educational Research.

  Google Scholar 

• Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York, NY: Palgrave Macmillan.

  Google Scholar 

• Gupta, A., Hammer, D., & Redish, E. F. (2011). The case for dynamic models of learners’ ontologies in physics. Journal of the Learning Sciences, 19(3), 285–321.

  Article  Google Scholar 

• Hammer, D., Gupta, A., & Redish, E. F. (2011). On static and dynamic intuitive ontologies. Journal of the Learning Sciences, 20(1), 163–168.

  Article  Google Scholar 

• Helsper, E., & Eynon, R. (2009). Digital natives: Where is the evidence? British Educational Research Journal, 36(3), 503–520.

  Article  Google Scholar 

• International Telecommunications Union. (2013). Measuring the information society. ITU Publication No. 254. http://www.itu.int/en/ITU-D/Statistics/Documents/publications/mis2013/MIS2013_without_Annex_4.pdf.

• Juul, J. (2003). The game, the player, the world: Looking for a heart of gameness. In M. Copier & J. Raessens (Eds.), Level up: Digital games research conference proceedings (pp. 30–45). Utrecht: Utrecht University.

  Google Scholar 

• Ke, F. (2009). A qualitative meta-analysis of computer games as learning tools. In R. Ferdig (Ed.), Handbook of research on effective electronic gaming in education (Vol. 1, pp. 1–32). Hershey, PA: Information Science Reference.

  Chapter  Google Scholar 

• Ketelhut, D. J., & Schifter, C. C. (2011). Teachers and game-based learning: Improving understanding of how to increase efficacy of adoption. Computers & Education, 56(2), 539–546.

  Article  Google Scholar 

• Koschmann, T., Hall, R. P., & Miyake, N. (Eds.). (2013). CSCL 2. New York, NY: Routledge.

  Google Scholar 

• Lenhart, A., Kahne, J., Middaugh, E., Macgill, A. R., Evans, C., & Vitak, J. (2008). Teens, video games, and civics. http://www.pewinternet.org/Reports/2008/Teens-Video-Games-and-Civics.aspx.

• Linn, M. C., Davis, E. A., & Bell, P. (Eds.). (2004). Internet environments for science education. London: Routledge.

  Google Scholar 

• Malmberg, L. E., & Hagger, H. (2009). Changes in student teachers’ agency beliefs during a teacher education year, and relationships with observed classroom quality, and day-to-day experiences. British Journal of Educational Psychology, 79(4), 677–694.

  Article  Google Scholar 

• Mayer, D. P. (1999). Measuring instructional practice: Can policymakers trust survey data? Educational Evaluation and Policy Analysis, 21(1), 29–45.

  Article  Google Scholar 

• Millstone, J. (2012). Teacher attitudes about digital games in the classroom. New York: The Joan Ganz Cooney Center at Sesame Workshop in collaboration with BrainPOP.

• Mullens, J. E., & Gayler, K. (1999). Measuring classroom instructional processes: Using survey and case study field test results to improve item construction. NCES 1999-08. Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.

• Palincsar, A. S. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 49, 345–375.

  Article  Google Scholar 

• 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.

  Article  Google Scholar 

• PBS & Grunwald Associates, LLC. (2011). Deepening connections: Teachers increasingly rely on media and technology. http://www.pbs.org/teachers/research.

• Peugh, J. L., & Enders, C. K. (2004). Missing data in educational research: A review of reporting practices and suggestions for improvement. Review of Educational Research, 74(4), 525–556.

  Article  Google Scholar 

• Pianta, R. C., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109–119.

  Article  Google Scholar 

• Pianta, R. C., Hamre, B. K., Hayes, N., & Mintz, S. (2011). Classroom assessment scoring system-secondary (CLASS-S). Charlottesville, VA: University of Virginia.

  Google Scholar 

• Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31(6), 459–470.

  Article  Google Scholar 

• Prensky, M. (2003). Digital game-based learning. ACM Computers in Entertainment, 1(1), 1–4.

  Article  Google Scholar 

• Raudenbush, S. W., Bryk, A. S, & Congdon, R. (2004). HLM 6 for Windows. Computer software. Skokie, IL: Scientific Software International, Inc.

• Richland, L. E., Zur, O., & Holyoak, K. J. (2007). Cognitive supports for analogies in the mathematics classroom. Science, 316(5828), 1128.

  Article  Google Scholar 

• Rideout, V.J., Foehr, U.G., & Roberts, D.F. (2010). Generation M2: Media in the lives of 8- to 18-year-olds. http://kff.org/other/report/generation-m2-media-in-the-lives-of-8-to-18-year-olds/.

• Roschelle, J., Knudsen, J., & Hegedus, S. (2010). From new technological infrastructures to curricular activity systems: Advanced designs for teaching and learning. In M. Jacobson & P. Reimann (Eds.), Designs for learning environments of the future (pp. 233–262). New York, NY: Springer.

  Chapter  Google Scholar 

• Roth, W. M. (2013). On meaning and mental representation: A pragmatic approach. Rotterdam: Sense Publishers.

  Book  Google Scholar 

• Salen, K., & Zimmerman, E. (2003). Rules of play: Game design fundamentals. Cambridge, MA: MIT Press.

  Google Scholar 

• Schneps, M. H., Sadler, P. M., Woll, S., & Crouse, L. (1989). A private universe. Motion picture. Annenberg Foundation/Corporation for Public Broadcasting Math and Science Project. Cambridge, MA: Harvard Smithsonian Center for Astrophysics.

• Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for learning: The hidden efficiency of original student production in statistics instruction. Cognition and Instruction, 22(2), 129–184.

  Article  Google Scholar 

• Sheingold, K., Hawkins, J., & Char, C. (1984). “I’m the thinkist, you’re the typist”: The interaction of technology and the social life of classrooms. Journal of Social Issues, 40(3), 49–61.

  Article  Google Scholar 

• Slotta, J. D., & Chi, M. T. H. (2006). Helping students understand challenging topics in science through ontology training. Cognition and Instruction, 24(2), 261–289.

  Article  Google Scholar 

• Slotta, J. D., Chi, M. T. H., & Joram, E. (1995). Assessing students’ misclassification of physics concepts: An ontological basis for conceptual change. Cognition and Instruction, 13(3), 373–400.

  Article  Google Scholar 

• Smith, J. P., diSessa, A. A., & Roschelle, J. (1994). Misconceptions reconceived: A constructivist analysis of knowledge in transition. Journal of the Learning Sciences, 3(2), 115–163.

  Article  Google Scholar 

• Song, M., & Herman, R. (2010). Critical issues and common pitfalls in designing and conducting impact studies in education: Lessons learned from the what works clearinghouse (phase I). Educational Evaluation and Policy Analysis, 32(3), 351–371.

  Article  Google Scholar 

• Squire, K., Barnett, M., Grant, J. M., & Higginbotham, T. (2004). Electromagnetism Supercharged!: Learning physics with digital simulation games. In Proceedings of the 6th international conference on learning sciences (Vol. 6, pp. 513–520).

• Thomas, M. K., Barab, S. A., & Tuzun, H. (2009). Developing critical implementations of technology-rich innovations: A cross-case study of the implementation of Quest Atlantis. Journal of Educational Computing Research, 41(2), 125–153.

  Article  Google Scholar 

• Venville, G. (2008). Knowledge acquisition as conceptual change: The case of a theory of biology. In O. N. Saracho & B. Spodek (Eds.), Contemporary perspectives on science and technology in early childhood education (pp. 41–63). Greenwich, CT: Information Age Publishing.

  Google Scholar 

• Vosniadou, S. (2008). International handbook of research on conceptual change. New York, NY: Taylor & Francis.

  Google Scholar 

• Vosniadou, S. (2012). Reframing the classical approach to conceptual change: Preconceptions, misconceptions and synthetic models. In B. J. Fraser, K. Tobin, & C. J. McRobbie (Eds.), Second international handbook of science education (Vol. 1, pp. 119–130). New York, NY: Springer.

  Chapter  Google Scholar 

• Wayne, A. J., Yoon, K. S., Zhu, P., Cronen, S., & Garet, M. S. (2008). Experimenting with teacher professional development: Motives and methods. Educational Researcher, 37(8), 469–479.

  Article  Google Scholar 

• Young, M. F., Slota, S., Cutter, A. B., Jalette, G., Mullin, G., Lai, B., et al. (2012). Our princess is in another castle: A review of trends in serious gaming for education. Review of Educational Research, 82(1), 61–89.

  Article  Google Scholar 

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