Session Information
09 SES 05.5 PS, General Poster Session
General Poster Session
Contribution
1. Introduction
Imagination and creativity are the curial element to dominate the present economy and culture (McCormack, 2010). Today’s scientific education is the best opportunity for emphasizing imagination and innovation. However, there is less literatures to discuss the importance of imagination in science education. In order to understand imagination in science education, Ho, Wang, and Cheng (2013) proposed that the scientific imagination process was constructed based on the professional knowledge and rich experiences of award-winning teachers (Ho et al., 2013).They divided the process into three stages: Initiation, Dynamic Adjustment, and Virtual Implementation. Four different key components operate during each of the three stages: Brainstorming, Association, Transformation/Elaboration, and Conceptualization/Organization/Formation. Based on this process (Ho et al., 2013), this study aims to develop an verbal test to measure pupils’ scientific imagination for 5th and 6th graders.
In recent years, Rasch techniques have been widely applied to test quality of questionnaires in various fields such as human science, education, medical science and management (Wang, 2004). Rasch techniques possess objective and interval properties and thus can improve limitations of classical test theory and benefit to test quality of assessment through multiple sources of evidence. Therefore, we utilize the Rasch techniques to conduct the validation of SIT-Verbal in the study.
Method
Expected Outcomes
References
1. Ho, H. C., Wang, C. C., & Cheng, Y. Y. (2013). Analysis of the Scientific Imagination Process. Thinking Skills and Creativity, 10, 68-78. 2. Holland, P. W., and Wainer, H. (Eds.) (1993). Differential item functioning. Hillsdale, NJ: Lawrence Erlbaum. 3. Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174. 4. McCormack, A. J. (2010). Imagine and invent: Create a great future. Journal of College Science Teaching, 22, 14-15. 5. Wang, W.-C. (2004). Rasch measurement theory and application in education and psychology. Journal of Education and Psychology, 27, 637-694. 6. Wright, B. D., & Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8, 370. 7. Wu, M. L., Adams, R. J., & Wilson, M. R. (2007). ConQuest [Computer software and manual]. Camberwell, Victoria, Australia: Australian Council for Educational Research.
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