Abstract
In this paper, we conduct a review over the existing empirical research to discuss how science and its specific aspects are viewed by the general population. We particularly highlight the potential gap existing in how people perceive science in an abstract sense and science in its more specific forms. We first demonstrate the tendency of people to possess a mix of positive and negative views toward science depending on whether they think in terms of general science or school science, reporting findings from both self-report and implicit measures of attitudes. Second, we discuss about a set of findings speculating about people’s views toward scientists and other science-related individuals. Such studies suggest that people’s images are often affected by stereotypes, which do not portray reality and potentially distance science from people. Based on such facts, we point out several tasks of science education to narrow the gap between people’s abstract and stereotypical images of science and the more specific and actual science.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
As a more specific description of the procedure involved in the IAT, participants of the test are instructed to sort a list of stimuli (e.g., rose, spider, love, death) which appears on the screen in a random sequence into appropriate categories by, for instance, pressing either a right-hand or a left-hand key. In a matching trial, the categories flower and pleasant are assigned to the same key while the categories bug and unpleasant are assigned to the other key. In the other half of the trials (mismatching trial), the set of categories are reversed, so the categories flower and unpleasant are paired and the categories bug and pleasant are paired. Participants are asked to categorize the words as quickly as possible, and are recorded on their response latency. The researchers compare the latencies for the matching and mismatching trials to consider the difference in fluency for the participants to process a category and its corresponding attribute. For an online interactive demonstration of the actual procedure, visit: https://implicit.harvard.edu/implicit/demo.
References
Japan Ministry of Internal Affairs and Communication: Survey of research and development 2012. http://www.stat.go.jp/data/kagaku/2012 (2012). Accessed 28 Apr 2013
National Science Foundation, National Center for Science and Engineering Statistics: National patterns of R&D resources: 2010–11 data update. http://www.nsf.gov/statistics/nsf13318 (2013). Accessed 28 Apr 2013
OECD: Main science and technology indicators. http://www.oecd.org/sti/msti_2012_2_documentation_e.pdf (2013). Accessed 28 Apr 2013
Ministry of Education, Culture, Sports, Science and Technology in Japan: Report on general school survey 2012. http://www.mext.go.jp/b_menu/toukei/chousa01/kihon/kekka/k_detail/1329235 (2012). Accessed 28 Apr 2013
Osborne, J., Simon, S., Collins, S.: Attitudes towards science: a review of the literature and its implications. Int. J. Sci. Educ. 25, 1049–1079 (2003)
National Center for Education Statistics, Institute of Education Sciences: Digest of education statistics: 2011. http://nces.ed.gov/programs/digest/d11 (2012). Accessed 29 Apr 2013
The Research Business: Views of Science Among Students, Teachers, and Parents. Institution of Electrical Engineers, London (1994)
Archenhold, F., Bell, J., Great Britain Department of Education and Science, et al.: Science at Age 15: A Review of APU Survey Findings, 1980–84. H.M.S.O, London (1988)
Ebenezer, J.V., Zoller, U.: Grade 10 students’ perceptions of and attitudes toward science teaching and school science. J. Res. Sci. Teach. 30, 175–186 (1993)
Jones, M.G., Howe, A., Rua, M.J.: Gender differences in students’ experiences, interests, and attitudes toward science and scientists. Sci. Educ. 84, 180–192 (2000)
Kawakami, M., Koshiro, E., Sakata, H.: Research on undergraduates’ images of science (1). In: Poster Presented at the 48th Annual Meeting of Japanese Social Psychological Association, Waseda University, Tokyo, 22–24 Sept 2007
Kawakami, M., Koshiro, E., Sakata, H.: University students’ view of science and nature. Hum. Sci. Res. Bull. 7, 57–65 (2008)
Greenwald, A.G., McGhee, D.E., Schwartz, J.L.K.: Measuring individual differences in implicit cognition: the implicit association test. J. Pers. Soc. Psychol. 74, 1464–1480 (1998)
Nosek, B.A., Banaji, M.R., Greenwald, A.G.: Math = me, me = female, therefore math ≠ me. J. Pers. Soc. Psychol. 83, 44–59 (2002)
Kessels, U., Rau, M., Hannover, B.: What goes well with physics? Measuring and altering the image of science. Brit. J. Edu. Psychol. 76, 761–780 (2006)
Hannover, B., Kessels, U.: Self-to-prototype matching as a strategy for making academic choices. Why high school students do not like math and science. Learn. Instr. 14, 51–67 (2004)
Rotter, N.G.: Images of engineering and liberal arts majors. J. Vocat. Behav. 20, 193–202 (1982)
Rampal, A.: Images of science and scientists: a study of school teachers’ views. I. Characteristics of scientists. Sci. Educ. 76, 415–436 (1992)
Fiske, S.T., Cuddy, A.J.C., Glick, P.: Universal dimensions of social cognition: warmth and competence. Trend Cogn. Sci. 11, 77–83 (2007)
Fiske, S.T., Cuddy, A.J.C., Glick, P., et al.: A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition. J. Pers. Soc. Psychol. 82, 878–902 (2002)
Cabinet Office, Government of Japan: Opinion poll about science technology and society. http://www8.cao.go.jp/survey/h21/h21-kagaku (2010). Accessed 01 May 2013
Chambers, D.W.: Stereotypic images of scientists: the draw-a-scientist test. Sci. Educ. 67, 255–265 (1983)
She, H.: Gender and grade level differences in Taiwan students’ stereotypes of science and scientists. Res. Sci. Technol. Educ. 16, 125–135 (1998)
Scherz, Z., Oren, M.: How to change students’ images of science and technology. Sci. Educ. 90, 965–985 (2006)
Steele, J.M., Walberg, H.J., House, E.R.: Subject areas and cognitive press. J. Educ. Psychol. 66, 363–366 (1974)
de Castro, L.N.: Fundamentals of natural computing: an overview. Phys. Life Rev. 4, 1–36 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Japan
About this chapter
Cite this chapter
Hashimoto, T., Karasawa, K. (2015). Science, so Close and yet so Far Away: How People View Science, Science Subjects, and Scientists. In: Suzuki, Y., Hagiya, M. (eds) Recent Advances in Natural Computing. Mathematics for Industry, vol 9. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55105-8_4
Download citation
DOI: https://doi.org/10.1007/978-4-431-55105-8_4
Published:
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-55104-1
Online ISBN: 978-4-431-55105-8
eBook Packages: EngineeringEngineering (R0)