Research Article Investigating the Effectiveness of Computer Simulations for Chemistry Learning

Are well-designed computer simulations an effective tool to support student understand- ing of complex concepts in chemistry when integrated into high school science classrooms? We investigated scaling up the use of a sequence of simulations of kinetic molecular theory and associated topics of diffusion, gas laws, and phase change, which we designed and experimentally tested. In the two effectiveness studies reported, one in a rural and the other in an urban context, chemistry teachers implemented two alternate versions of a curricular unit—an experimental version, incorporating simula- tions, and a control version, using text-based materials covering the same content. Participants were 718 high school students (357 rural and 361 urban), in a total of 25 classrooms. The implementation of the simulations was explored using criteria associated with fidelity of implementation (FOI). Each context provided insights into the role of FOI in affecting the effectiveness of the interventions when working with groups of teachers. Results supported the effectiveness of this sequence of simula- tions as a teaching tool in a classroom context, and confirmed the importance of FOI factors such as adherence and exposure in determining the specific environments in which these materials were most effective. 2012 Wiley Periodicals, Inc. J Res Sci Teach 49: 394-419, 2012

[1]  Eva Alerby,et al.  The Sounds of Silence: Some remarks on the value of silence in the process of reflection in relation to teaching and learning , 2003 .

[2]  Neil Taylor,et al.  PRE-SERVICE PRIMARY TEACHERS' MODELS OF KINETIC THEORY: AN EXAMINATION OF THREE DIFFERENT CULTURAL GROUPS , 2002 .

[3]  Robert B. Kozma,et al.  Th e Use of Multiple Representations and the Social Construction of Understanding in Chemistry , 2012 .

[4]  Noah S. Podolefsky Learning science through computer games and simulations , 2012 .

[5]  Catherine Milne,et al.  Understanding Engagement in Science Education: The Psychological and the Social , 2012 .

[6]  Sara Hennessy,et al.  Situated Expertise in Integrating Use of Multimedia Simulation into Secondary Science Teaching , 2006 .

[7]  N. Vaidya,et al.  Science Teaching for the 21st Century , 2002 .

[8]  J. Graham,et al.  Missing data analysis: making it work in the real world. , 2009, Annual review of psychology.

[9]  E. Soloway,et al.  Creating Usable Innovations in Systemic Reform: Scaling Up Technology-Embedded Project-Based Science in Urban Schools , 2000 .

[10]  J. Bruner The Narrative Construction of Reality , 1991, Critical Inquiry.

[11]  Brian C. Nelson,et al.  Design-based research strategies for studying situated learning in a multi-user virtual environment , 2004 .

[12]  J. Lemke Talking Science: Language, Learning, and Values , 1990 .

[13]  Paul Theobald Urban and Rural Schools: Overcoming Lingering Obstacles , 2005 .

[14]  Allen Munro,et al.  Productivity tools for simulation-centered training development , 1992 .

[15]  Courtney B. Cazden,et al.  Classroom Discourse: The Language of Teaching and Learning. Second Edition. , 2001 .

[16]  C. Dede,et al.  Scaling Up Success : Lessons Learned from Technology-Based Educational Improvement , 2005 .

[17]  Deborah Bybee,et al.  Fidelity Criteria: Development, Measurement, and Validation , 2003 .

[18]  Okhee Lee,et al.  Effects of fidelity of implementation on science achievement gains among english language learners , 2009 .

[19]  Chris Dede,et al.  Scaling Up: Evolving Innovations beyond Ideal Settings to Challenging Contexts of Practice , 2005 .

[20]  Robert B. Kozma,et al.  Students Becoming Chemists: Developing Representationl Competence , 2005 .

[21]  Vanessa May,et al.  What is Narrative Analysis , 2010 .

[22]  Slava Kalyuga,et al.  Design Factors for Effective Science Simulations: Representation of Information , 2009, Int. J. Gaming Comput. Mediat. Simulations.

[23]  Barry J. Fishman,et al.  Bringing Urban Schools into the Information Age: Planning for Technology vs. Technology Planning , 2001 .

[24]  Anthony S. Bryk,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[25]  Joseph Krajcik,et al.  Examining the effect of teachers' adaptations of a middle school science inquiry-oriented curriculum unit on student learning , 2011 .

[26]  I. Seidman Interviewing as qualitative research , 1991 .

[27]  Jan L. Plass,et al.  Interactivity in multimedia learning: An integrated model , 2010, Comput. Hum. Behav..

[28]  Randy L. Bell,et al.  Computer Simulations to Support Science Instruction and Learning: A critical review of the literature , 2012 .

[29]  Mary A. Carskadon,et al.  When Worlds Collide: Adolescent Need for Sleep Versus Societal Demands. , 1999 .

[30]  C. Vanderbilt The Jasper experiment: An exploration of issues in learning and instructional design , 1992 .

[31]  Michael J. Hannafin,et al.  Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice , 2011, Comput. Educ..

[32]  Wiebe E. Bijker,et al.  Science in action : how to follow scientists and engineers through society , 1989 .

[33]  B. Flay Efficacy and effectiveness trials (and other phases of research) in the development of health promotion programs. , 1986, Preventive medicine.

[34]  D. Ardaç,et al.  Effectiveness of multimedia-based instruction that emphasizes molecular representations on students' understanding of chemical change , 2004 .

[35]  Hee-Sun Lee,et al.  Research towards an expanded understanding of inquiry science beyond one idealized standard , 2003 .

[36]  Daniel L. Schwartz,et al.  Spatial Learning and Computer Simulations in Science , 2009 .

[37]  Tx Station Stata Statistical Software: Release 7. , 2001 .

[38]  Helen R. Quinn,et al.  A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas , 2013 .

[39]  Michael J. Padilla,et al.  The Construction and Validation of the Test of Graphing in Science (TOGS). , 1986 .

[40]  Okhee Lee,et al.  Dilemmas in Scaling Up Innovations in Elementary Science Instruction With Nonmainstream Students , 2005 .

[41]  Daniel S. Nagin,et al.  Analyzing developmental trajectories: A semiparametric, group-based approach , 1999 .

[42]  Dorothy L. Gabel,et al.  Improving Teaching and Learning through Chemistry Education Research: A Look to the Future , 1999 .

[43]  Jan L. Plass,et al.  Design factors for educationally effective animations and simulations , 2009, J. Comput. High. Educ..

[44]  Ton de Jong,et al.  Scientific Discovery Learning with Computer Simulations of Conceptual Domains , 1998 .

[45]  Jae Young Han,et al.  Critical Graphicacy: Understanding Visual Representation Practices in School Science , 2005 .

[46]  Steven C. Mills,et al.  A tool for analyzing implementation fidelity of an integrated learning system , 2000 .

[47]  Kristin G. Congdon Attendance , 2010 .

[48]  David A. Gillam,et al.  A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas , 2012 .

[49]  Amelia Wenk Gotwals,et al.  Fidelity of Implementation in Three Sequential Curricular Units , 2005 .

[50]  Carol L. O'Donnell Defining, Conceptualizing, and Measuring Fidelity of Implementation and Its Relationship to Outcomes in K–12 Curriculum Intervention Research , 2008 .

[51]  Eric R. Scerri Normative and Descriptive Philosophy of Science and the Role of Chemistry , 2006 .

[52]  R. Bosker Boekbespreking van "A.S. Bryk & S.W. Raudenbusch - Hierarchical linear models: Applications and data analysis methods" : Sage Publications, Newbury Parki, London/New Delhi 1992 , 1995 .

[53]  Chris Dede,et al.  The Cambridge Handbook of the Learning Sciences: Scaling Up , 2005 .

[54]  Gary King,et al.  Amelia II: A Program for Missing Data , 2011 .