University students' interpretation of media reports of science and its relationship to background knowledge, interest, and reading difficulty

Public Understanding of Science

Volumn 12, Issue 2, 2003, Pages 123-145

  Norris, Stephen P ^a   Phillips, Linda M ^a   Korpan, Connie A ^b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b Grande Prairie Regional College   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0041877429     PISSN: 09636625     EISSN: None     Source Type: Journal    
DOI: 10.1177/09636625030122001     Document Type: Article

References (96)

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45. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
46. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
47. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
48. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
49. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
50. C.W. Anderson, "Inscription and science learning," Journal of Research in Science Teaching 36 (1999): 973-974; R. Millar and J. Osborne, eds., Beyond 2000: Science education for the future, the report of a seminar series funded by the Nuffield Foundation (London: King's College London, 1998); National Science Board, Science and engineering indicators-1998); Select Committee on Science and Technology, Science and society; S.P. Norris, and L.M. Phillips, "How literacy in its fundamental sense is central to scientific literacy," Science Education 87 (2003): 224-240; M. Shortland, "Advocating science: Literacy and public understanding," Impact of Science on Society 38 (1988): 305-316; F.X. Sutman, "Scientific literacy, a functional definition," Journal of Research in Science Teaching 33 (1996): 459-460.
51. Pellechia, "Trends in science coverage."
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53. W.A. Evans, M. Krippendorf, J.H. Yoon, P. Posluszny, and S. Thomas, "Science in the prestige and national tabloid presses," Social Science Quarterly 71 (1990): 105-117; Pellechia, "Trends in science coverage."
54. P.M.D. Collins and W.F. Bodmer, "The public understanding of science," Studies in Science Education 31 (1986): 1057-1073; Wellington, "Newspaper science, school science."
55. P.M.D. Collins and W.F. Bodmer, "The public understanding of science," Studies in Science Education 31 (1986): 1057-1073; Wellington, "Newspaper science, school science."
56. J. Ryder, "Identifying science understanding for functional scientific literacy," Studies in Science Education 36 (2001): 1-44.
57. Ryder, "Identifying science understanding," p. 34.
58. Millar and Osborne, Beyond 2000.
59. B. Came, "Mysterious moon," Maclean's, (April 21, 1997): 42-43; S.D. Driedger, "Strong medicine," Maclean's (March 24, 1997): 60; W. Immen, "Skinny mice may help fat humans slim down," Globe and Mail (May 1, 1997); New animal species found in Vietnam, The Evening Telegram (August 6, 1992): 12; S. Strauss, "Axes to grind: Scientists contest cosmic hypothesis," Globe and Mail (May 3, 1997).
60. B. Came, "Mysterious moon," Maclean's, (April 21, 1997): 42-43; S.D. Driedger, "Strong medicine," Maclean's (March 24, 1997): 60; W. Immen, "Skinny mice may help fat humans slim down," Globe and Mail (May 1, 1997); New animal species found in Vietnam, The Evening Telegram (August 6, 1992): 12; S. Strauss, "Axes to grind: Scientists contest cosmic hypothesis," Globe and Mail (May 3, 1997).
61. B. Came, "Mysterious moon," Maclean's, (April 21, 1997): 42-43; S.D. Driedger, "Strong medicine," Maclean's (March 24, 1997): 60; W. Immen, "Skinny mice may help fat humans slim down," Globe and Mail (May 1, 1997); New animal species found in Vietnam, The Evening Telegram (August 6, 1992): 12; S. Strauss, "Axes to grind: Scientists contest cosmic hypothesis," Globe and Mail (May 3, 1997).
62. B. Came, "Mysterious moon," Maclean's, (April 21, 1997): 42-43; S.D. Driedger, "Strong medicine," Maclean's (March 24, 1997): 60; W. Immen, "Skinny mice may help fat humans slim down," Globe and Mail (May 1, 1997); New animal species found in Vietnam, The Evening Telegram (August 6, 1992): 12; S. Strauss, "Axes to grind: Scientists contest cosmic hypothesis," Globe and Mail (May 3, 1997).
63. B. Came, "Mysterious moon," Maclean's, (April 21, 1997): 42-43; S.D. Driedger, "Strong medicine," Maclean's (March 24, 1997): 60; W. Immen, "Skinny mice may help fat humans slim down," Globe and Mail (May 1, 1997); New animal species found in Vietnam, The Evening Telegram (August 6, 1992): 12; S. Strauss, "Axes to grind: Scientists contest cosmic hypothesis," Globe and Mail (May 3, 1997).
64. C. Haas and L. Flower, "Rhetorical reading strategies and the construction of meaning," College Composition and Communication 39 (1988): 167-183.
65. J. Leach, R. Driver, R. Millar, and P. Scott, "A study of progression in learning about the 'nature of science': Issues of conceptualization and methodology," International Journal of Science Education 19 (1997): 147-166; J. Solomon, J. Duveen, and L. Scott, "Pupils' images of scientific epistemology," International Journal of Science Education 16 (1994): 361-373.
66. J. Leach, R. Driver, R. Millar, and P. Scott, "A study of progression in learning about the 'nature of science': Issues of conceptualization and methodology," International Journal of Science Education 19 (1997): 147-166; J. Solomon, J. Duveen, and L. Scott, "Pupils' images of scientific epistemology," International Journal of Science Education 16 (1994): 361-373.
67. In Classical Test Theory (see F.M. Lord and M.R. Novick, Statistical Theories of Mental Test Scores (Reading, MA: Addison-Wesley, 1968)), the reliability of a test is a technical notion defined as the square of the correlation between observed scores (the scores examinees actually get on tests) and true scores (the error-free scores that represent their true performance). Because true scores are not observable, this correlation can never be computed directly, but must be estimated to various degrees of approximation from observed scores. The Kuder-Richardson formula 20, KR-20, is one such estimation technique. It provides a lower bound on the reliability of a test, that is, a number below which the real reliability, if it could be computed, would not fall; S.P. Norris, "Effect of eliciting verbal reports of thinking on critical thinking test performance," Journal of Educational Measurement 27 (1990): 41-48.
68. In Classical Test Theory (see F.M. Lord and M.R. Novick, Statistical Theories of Mental Test Scores (Reading, MA: Addison-Wesley, 1968)), the reliability of a test is a technical notion defined as the square of the correlation between observed scores (the scores examinees actually get on tests) and true scores (the error-free scores that represent their true performance). Because true scores are not observable, this correlation can never be computed directly, but must be estimated to various degrees of approximation from observed scores. The Kuder-Richardson formula 20, KR-20, is one such estimation technique. It provides a lower bound on the reliability of a test, that is, a number below which the real reliability, if it could be computed, would not fall; S.P. Norris, "Effect of eliciting verbal reports of thinking on critical thinking test performance," Journal of Educational Measurement 27 (1990): 41-48.
69. S.P. Norris, and R.H. Ennis, Evaluating Critical Thinking (Pacific Grove, CA: Midwest, 1989), 43-49.
70. Haas and Flower, "Rhetorical reading strategies."
71. K. Penney, S.P. Norris, L.M. Phillips, and G. Clark "The anatomy of junior high school science textbooks: An analysis of textual characteristics and a comparison to media reports of science," Canadian Journal of Science, Technology and Mathematics Education 3 (in press).
72. Norris and Phillips, "Interpreting pragmatic meaning."
73. We have come to realize that ambiguity in the meaning of "explain a phenomenon" makes our results difficult to interpret. In the sense we intended, "explain" means "provide a causal account of." The word has at least two other senses: "to justify or provide reasons for" and "to make intelligible." We see the same ambiguity affecting other work in this area. For example, Long uses interchangeably the terms "scientific explanation" and "explain scientific concepts and processes." According to her usage, both mean "make intelligible" (M. Long, "Scientific explanation in US newspaper science stories," Public Understanding of Science 4 (1995): 119-130). However, in our experience, particularly in the philosophy of science literature, "scientific explanation" is used typically in the sense of a causal account. Care is needed here, especially as causal accounts sometimes make events intelligible. Rowan has studied what she calls "explanatory writing," by which she means "explaining difficult ideas to nonexperts," (K.E. Rowan, "Cognitive correlates of explanatory writing skill," Written Communication 7 (1990): 316-341). Rowan, too, uses the term in the sense of making intelligible.
74. We have come to realize that ambiguity in the meaning of "explain a phenomenon" makes our results difficult to interpret. In the sense we intended, "explain" means "provide a causal account of." The word has at least two other senses: "to justify or provide reasons for" and "to make intelligible." We see the same ambiguity affecting other work in this area. For example, Long uses interchangeably the terms "scientific explanation" and "explain scientific concepts and processes." According to her usage, both mean "make intelligible" (M. Long, "Scientific explanation in US newspaper science stories," Public Understanding of Science 4 (1995): 119-130). However, in our experience, particularly in the philosophy of science literature, "scientific explanation" is used typically in the sense of a causal account. Care is needed here, especially as causal accounts sometimes make events intelligible. Rowan has studied what she calls "explanatory writing," by which she means "explaining difficult ideas to nonexperts," (K.E. Rowan, "Cognitive correlates of explanatory writing skill," Written Communication 7 (1990): 316-341). Rowan, too, uses the term in the sense of making intelligible.
75. Principal components analysis is a mathematical technique for creating new composite variables, called "principal components," from linear combinations of an existing set of variables. The transformations are made under two restrictions: a) the linear combinations create new variables that are uncorrelated with one another; and b) the first principal component is that linear combination of the existing variables having maximum variance, the second principal component is that linear combination of the existing variables uncorrelated with the first and having maximum variance, and so on for subsequent transformations. Each principal component can be thought of as defining a dimension held in common by the original variables. In the present example, we were testing whether anything held in common among knowledge, interest, and reading difficulty across all test sections provides greater predictability of performance on the interpretive questions than the original variables used either severely or jointly in a regression analysis. The first principal component represents the dimension along which the original variables have the most in common.
76. Pellechia, "Trends in science coverage."
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