Measuring the effectiveness of computer-based scientific visualisations for conceptual development in Australian chemistry classrooms

Visual modes of representation have always been very important in science and science education. Interactive computer-based animations and simulations offer new visual resources for chemistry education. Many studies have shown that students enjoy learning with visualisations but few have explored how learning outcomes compare when teaching with or without visualisations. This study employs a quasi-experimental crossover research design and quantitative methods to measure the educational effectiveness - defined as level of conceptual development on the part of students - of using computer-based scientific visualisations versus teaching without visualisations in teaching chemistry. In addition to finding that teaching with visualisations offered outcomes that were not significantly different from teaching without visualisations, the study also explored differences in outcomes for male and female students, students with different learning styles (visual, aural, kinesthetic) and students of differing levels of academic ability

Teaching with Interactive Simulations: One Small Contribution Toward Science Education for all

Many of the greatest challenges facing humanity in coming decades have a scientific component: energy needs, disease pandemics, water and food security, climate change, machine intelligence and many not yet imagined. The tendency has been to assume that the solutions to these challenges will be developed by scientists, engineers and technologists, but it is increasingly important that all citizens have sufficient understanding of science to participate in the democratic processes that are necessary to address major issues. Enhancing the science education of all citizens is a huge challenge in itself, and will require a very wide range of strategies and approaches. One small contribution can come from teaching approaches using new technologies, including interactive simulations. This paper briefly describes interactive simulations and an approach to teaching using them, and addresses evidence of the effectiveness of this approach. Outcomes showed significant learning gains, relative to a control group, that were not differentiated by gender, or for students at different levels of academic achievement, suggesting that this approach may be effective as one contribution toward science education for all

The Empty Centre : Power/Knowledge, Relationships and the Myth of \u27Student Centered Teaching\u27 in Teacher Education.

The notion of ‘student centred learning’ is a popular and influential one in education at all levels. Questions of exactly how this may be defined, and what it would look like in practice are, however, much more difficult to address. During second semester 1998, I was involved in teaching a Masters level unit on teacher action research to a group of middle school teachers. I placed a high value on the knowledge, values and experience of these students, and attempted to allow them considerable freedom to construct their own learning activities and assessment procedures. Some students accepted the offered challenges, and after some initial disorientation were able to construct powerful and valuable educative programs for themselves. Others, however, felt threatened by the perceived lack of structure and direction in the course, and felt that their time was being wasted. This paper explores my own experiences and ethical/theoretical commitments through discussion of contemporary reflective texts and narratives. It also addresses some of the complex meanings that may be ascribed to the phrase ‘student centred teaching’, and suggests that a teacher’s withdrawal from an intensive, controlling classroom role must be negotiated with students in ways that avoid the creation of an ‘empty centre’

Representing critical reflections in teacher education

This critical action research study explores the professional growth of a middle school teacher and two teacher educators. It focuses on a professional development program in which one author (Bev) had the role of student, one of teacher (Peter), and one of the teacher's 'critical friend' (David). The program's epistemology was based on Habermas' theory of 'knowledge and human interests', emphasising the 'emancipatory' interest's potential for creating empowering learning environments. The teaching and learning roles of the participants, with their professional development and new understandings, are explored with reference to a 'critical incident' that sparked this inquiry. Narrative accounts are used to explore the sometimes conflicting meanings constructed by the authors, highlighting the complex nature of their educative discourses and problematising notions of emancipatory curriculum and student empowerment

Model-based geostatistics: some issues in modelling and model diagnostics

Spatial modelling is examined in a model-based geostatistical context using the Gaussian linear mixed model in a likelihood framework. Complex spatial models developed provide practitioners with a practical and best-practice guide for spatial analysis. Adequate modelling theory and matrix algebra are provided to ground the methods demonstrated. A multivariate model over two time points and three-dimensional space is developed which is novel to the field of soil science. Soil organic carbon measurements at three soil depths and two time points from a cropping field with four soil classes are used. The spatial process is assessed for second-order stationarity and anisotropic correlation. Univariate spatial modelling is used to inform bivariate spatial modelling of pre- and post-harvest soil organic carbon at each soil depth. Bivariate modelling is extended to the multivariate level, where both time points and the three soil depths are incorporated in a single model to pool maximum information. A common correlation structure is tested and is supported for the response variable at each of the six time-depth combinations. Separable correlation structures are used for computational efficiency. The difficulty of estimating nugget effects suggests a sub-optimal sampling design. Preferred fitted models are all isotropic. Equations for predictions and the variance of prediction errors are extended from well-known results and maps of predicted values and variance of prediction errors are produced and show close correspondence with observed values. Finally, univariate models for spatially referenced seed counts from small sampling plots are examined within a Gaussian framework using Box-Cox transformations. The discrete nature of the data, small sample size and computational problems hamper model fitting. Anisotropy is examined using a variogram envelope diagnostic technique. ASReml-R software is shown to be a powerful analytical tool for spatial processes

Embodying our values in our teaching practices: Building open and critical discourse through computer mediated communication

Computer mediated communication—including web pages, email and web-based bulletin boards—was used to support the development of a cooperative learning community among students in a web-based distance education unit for practicing science and mathematics educators. The students lived in several Australian states and a number of Pacific Rim countries. They reported increased satisfaction with their studies, decreased feelings of isolation, and better support for their learning processes. This article describes the iterative processes of research and design involved in developing and refining the unit, which was based in a social constructivist/constructionist conception of teaching and learning, between 1997 and 1999. Issues and implications for others planning to develop web-based teaching units, including the time and energy commitment involved, and the challenges of credibly assessing online participation, are also considered

Model-based geostatistics: some issues in modelling and model diagnostics

Spatial modelling is examined in a model-based geostatistical context using the Gaussian linear mixed model in a likelihood framework. Complex spatial models developed provide practitioners with a practical and best-practice guide for spatial analysis. Adequate modelling theory and matrix algebra are provided to ground the methods demonstrated. A multivariate model over two time points and three-dimensional space is developed which is novel to the field of soil science. Soil organic carbon measurements at three soil depths and two time points from a cropping field with four soil classes are used. The spatial process is assessed for second-order stationarity and anisotropic correlation. Univariate spatial modelling is used to inform bivariate spatial modelling of pre- and post-harvest soil organic carbon at each soil depth. Bivariate modelling is extended to the multivariate level, where both time points and the three soil depths are incorporated in a single model to pool maximum information. A common correlation structure is tested and is supported for the response variable at each of the six time-depth combinations. Separable correlation structures are used for computational efficiency. The difficulty of estimating nugget effects suggests a sub-optimal sampling design. Preferred fitted models are all isotropic. Equations for predictions and the variance of prediction errors are extended from well-known results and maps of predicted values and variance of prediction errors are produced and show close correspondence with observed values. Finally, univariate models for spatially referenced seed counts from small sampling plots are examined within a Gaussian framework using Box-Cox transformations. The discrete nature of the data, small sample size and computational problems hamper model fitting. Anisotropy is examined using a variogram envelope diagnostic technique. ASReml-R software is shown to be a powerful analytical tool for spatial processes