|Title:||Molecules and Minds: Optimizing Simulations for Chemistry Education|
|Principal Investigator:||Plass, Jan||Awardee:||New York University|
|Program:||Science, Technology, Engineering, and Mathematics (STEM) Education [Program Details]|
|Award Period:||3 years||Award Amount:||$1,136,028|
|Type:||Development and Innovation||Award Number:||R305K050140|
Co-Principal Investigators: Catherine Milne, Bruce Homer, and Trace Jordan
Recent evidence indicates that U.S. students lag behind their international counterparts in science achievement. In this project, the investigators are developing and assessing the potential of instructional simulations to improve student learning and achievement in chemistry. At the end of this project, the investigators will have a set of computer simulations intended as activities to support a high school chemistry course. A subset of these simulations could be combined to form a complete high school chemistry curriculum.
Purpose: The primary purpose of the project is to improve high school chemistry education. Recent evidence suggests that U.S. students lag behind their international counterparts with regard to their science skills. The investigators plan to develop and assess the potential of instructional simulations to improve student learning and achievement in chemistry. At the end of this project, the investigators will have a set of computer simulations and data showing whether or not using these simulation modules have the potential to facilitate learning chemistry concepts. A subset of these simulations could be combined to form a complete curriculum for a grade 9 chemistry course.
Setting: The participants for the research will come from New York City public high school chemistry classes. Three classes of approximately 25 students each will be recruited from four different schools for a total of 12 chemistry classes.
Population: Approximately 720 high school chemistry students (ages 15-17) will participate in the research studies to be conducted in years 1 to 3 of the project. The student population at the participating schools is racially and ethnically diverse (7% White, 45% Black, 42% Hispanic, and 5% Other). Approximately 51% of students are eligible for free lunch.
Intervention: Two related areas in the high school chemistry curriculum will be targeted-the kinetic theory of heat and the behavior of ideal gases- in which to first explore the potential efficacy of multimedia simulations on student learning. The simulations will be based on 3 principles of learning: (a) active engagement of the learner, (b) optimization of visual cognitive load, and (c) consideration of the impact of learner characteristics (e.g., prior knowledge, spatial ability and metacognitive skills) on the learning process. The researchers will develop a total of 18 versions of computer simulations for 6 different chemistry concepts, a subset of which could ultimately be combined to form a complete curriculum for grade 9.
Research Design and Methods: In Year 1, four different versions of two chemistry education simulations (gas laws and kinetic theory of heat) will be developed. One variant will follow the typical design identified in currently used materials. The researchers will then develop three additional versions that incorporate different components of the theoretical framework. An iterative design approach will be used to develop the simulations and a series of lab-based experiments will be conducted to guide the design of the simulations. At the end of Year 1, four versions of two additional simulations will be developed for use in the next phases of the project. The specific topics of these additional simulations will be decided in collaboration with the high school chemistry teachers whose classrooms will be participating in the research.
Year 2 will involve design experiments in the form of quasi-experimental field-testing of the simulations created in Year 1. For this second phase of the research, the four simulations developed during Year 1 will be tested with students enrolled in high school chemistry in urban New York City schools. During the summer of Year 2, two additional simulations will be developed, informed by the results of Year 1 and Year 2 research. In this development project, a small experimental study to evaluate the potential of the simulations to improve student learning in chemistry will be conducted in the final year. Three classrooms (approximately 25 students each) from each of four different high schools will participate in the study. Each class will be randomly assigned to either an experimental group or to a control group.
Control Condition: Participants in the control condition will receive the standard high school chemistry curriculum (with no simulations).
Key Measures: A wide range of standardized and experimenter-designed measures will be employed to assess student learning and achievement in chemistry; attitudes towards chemistry; and individual learner characteristics such as prior knowledge, visual ability, and self-regulation.
Data Analytic Strategy: One-way analyses of covariance (ANCOVA's) will be conducted for each simulation with group (experimental vs. control) as the independent variable, and the individual learner characteristics entered as covariates. Separate analyses will be conducted for the two main dependent variables (learning in chemistry and attitude towards chemistry). This development project is intended only to obtain evidence of the potential efficacy of the intervention; the study is under-powered for analysis at the unit of random assignment (classroom) and will be analyzed at the level of the student.
Project Website: http://create.alt.ed.nyu.edu/molecules/.
Related IES Projects: Molecules and Minds: Developing Bridging Scaffolds to Improve Chemistry Learning (R305A090203)
Brunken, R., Plass, J.L., and Moreno, R. (2010). Current Issues and Open Questions in Cognitive Load Research. In J.L. Plass, R. Moreno, and R. Brunken (Eds.), Cognitive Load Theory (pp. 253–272). New York: Cambridge.
Homer, B.D., and Hayward, E.O. (2008). Cognitive and Representational Development in Children. In K.B. Cartwright (Ed.), Literacy Processes: Cognitive Flexibility in Learning and Teaching(pp. 19–41). New York: Guilford Press.
Kalyuga, S., and Plass, J.L. (2008). Evaluating and Managing Cognitive Load in Educational Games. In R.E. Ferdig (Ed.), Handbook of Research on Effective Electronic Gaming in Education (pp. 719–737). Hershey, PA: IGI Global Press.
Milne, C. (2007). Power, Status and the Whole Shebang: A Personal Perspective of Collaborative Research. In S. Ritchie (Ed.), Research Collaboration: Relations and Praxis (pp. 107–122). Rotterdam, Netherlands: Sense Publishers.
Plass, J.L., Kalyuga, S., and Leutner, D. (2010). Individual Differences and Cognitive Load Theory. In J.L. Plass, R. Moreno, and R. Brünken (Eds.), Cognitive Load Theory (pp. 65–90). New York: Cambridge.
Journal article, monograph, or newsletter
Domagk, S., Schwartz, R.N., and Plass, J.L. (2010). Interactivity In Multimedia Learning: An Integrated Model. Computers in Human Behavior, 26(5): 1024–1033.
Homer, B.D., and Nelson, K.N. (2009). Naming Facilitates Young Children's Understanding of Scale Models: Language and the Development of Symbolic Understanding. Journal of Cognition and Development, 10(1): 115–134.
Homer, B.D., and Plass, J.L. (2009). Expertise Reversal for Iconic Representations in Science Visulizations. Instructional Science: An International Journal of the Learning Sciences, 38(3): 259–276.
Homer, B.D., Plass, J.L., and Blake, L. (2008). The Effects of Video on Cognitive Load and Social Presence in Computer-Based Multimedia-Learning. Computers in Human Behavior, 24(3): 786–797.
Lee, H., Plass, J.L., and Homer, B.D. (2006). Optimizing Cognitive Load for Learning From Computer-Based Science Simulations. Journal of Educational Psychology, 98(4): 902–913.
Plass, J.L., Homer, B., and Hayward, E. (2009). Design Factors for Educationally Effective Animations and Simulations. Journal of Computing in Higher Education, 21(1): 31–61.
Plass, J.L., Homer, B.D., Milne, C., Jordan, T., Kalyuga, S., Kim, M., and Lee, H.J. (2009). Design Factors for Effective Science Simulations: Representation of Information. International Journal of Gaming and Computer-Mediated Simulations, 1(1): 16–35.
Nongovernment report, issue brief, or practice guide
Plass, J.L. (2009). Using Cognitive Load Theory to Improve Teaching and Learning of Surgery.Chicago: American College of Surgeons.
Kalyuga, S., and Plass, J.L. (2007). Managing Cognitive Load in Instructional Simulations. In Proceedings of the IADIS International Conference E-Learning(pp. 198–219). E-Learning: IADIS Press.