This study examines the effects of a teaching method using 3D virtual reality stimulations on achievement and attitude toward science. An experiment was conducted with fifth-grade students (N=41) to examine the effects of 3D simulations, designed to support inquiry-based science curriculum. An ANOVA analysis revealed that the 3D group scored significantly higher on the achievement test (F=7.03, p<.05) than the control group using traditional 2D visuals. A positive change of attitude toward science was identified in both 3D and 2D groups, but it was not statistically significant. A robust regression analysis revealed that neither gender nor ethnicity has any significant effect on achievement tests or attitude. However, prior attitude had a significant determining effect for later attitude in both groups.
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As part of the ePortfolio development project with STEP (Stanford Teacher Education Program), the Sunnyvale School District partnering with SUSE IT has conducted an experimental study and a qualitative study. Included here are the results of the empirical study.
A dual-display-mode electronic portfolio system, designed to serve as a resource-based learning space, was tested in a 5th grade science class. The control group students accessed a traditional folder-based information display and the experimental group students accessed a visual map-based information display to review a science portfolio on the Earth’s atmosphere. The student-constructed science portfolio was a result of a collection of digital artifacts such as graphic images, instructional videos, textual files on terms and definitions relevant to the Earth’s atmosphere. In the information processing performance test, the experimental group students scored significantly higher and spent much less time in finding answers to the questions presented. Also, in the three-day delayed memory retention tests, the experimental group students achieved higher scores (statistically significant at p<.001). The multiple regression models confirm that the visualization variation is the most significant predictor for student performance (i.e., comprehension and access time). Also, the regression models suggest that language arts proficiency may reduce overall system access time; while higher math proficiency may predict retention scores.
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