Media Exposure and Knowledge About Science
Media Exposure and Knowledge About Science
Vincent Kiernan
Graduate student, College of Journalism
University of Maryland, College Park
4600 Duke St., Apt. 1524
Alexandria VA 22304
703-370-3202
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A paper presented to the Science Communication Interest Group
at the annual convention
of the Association for Education in Journalism and Mass Communication,
Anaheim, California, August 1996
Media Exposure and Knowledge About Science
Abstract
In a secondary analysis of the 1992 National Science Foundation Survey
of Public Understanding of Science and Technology, high levels of exposure to
television news are associated with lower levels of knowledge of basic
scientific facts. High exposure to magazines and daily newspapers is associated
with higher knowledge, even after accounting for education and interest in
science news. The findings suggest that televised science news may be
misunderstood by viewers. Media Exposure and Knowledge About Science
Many members of the public have a poor grasp of scientific facts and
principles, as several studies have documented both in the United States and
abroad (Durant, Evans & Thomas, 1989; National Science Board, 1985; National
Science Board, 1987; National Science Board, 1989; National Science Board,
1991). This low level of understanding is troubling to some analysts because
they fear that an ill-informed public will be less able to make valid judgements
on public-policy issues that contain a scientific or technical component (Hazen
& Trefil, 1991; Miller, Suchner & Voelker, 1980).
However, fostering a higher level of science literacy requires a
better understanding of how the public acquires its knowledge about science,
whether from news media or from other sources. Information processing theories
of mass communication may be helpful in this regard. Information-processing
theories such as that of Graber (1988) maintain that an individual's cognitive
processes are responsible for the fashion in which that individual selects and
processes information from the news sources that are presented to the
individual. Moreover, each news source exhibits characteristics that make its
content easier or more difficult for the individual to process cognitively;
thus, individuals may learn more effectively from some news sources than from
others.
In this vein, Robinson and Levy (1986) reviewed studies of learning
from television and concluded that there is little evidence that viewers learn
from television news programming. They suggested that television news exhibits
characteristics -- such as its fast pace and emphasis on pictures rather than
text -- that may inhibit viewers' processing of the science-information content
of television news. By contrast, print media may be easier to process
cognitively, because a reader can read at his or her own pace and can reread
portions of the text that are difficult.
Few studies have focused specifically on learning of scientific
information from various media. Wade and Schramm (1969) found that individuals
in a 1957 national survey who were able to correctly answer four
science-knowledge questions were likely to rely principally on newspapers or
magazines for news, rather than television or radio. They suggested that the
vividness and immediacy of television journalism means that television is likely
to be a source of science information that is tied to dramatic events in the
news. By contrast, print media, which offer more perspective and interpretation
than television, are more likely to be sources of a broader range of long-term
science knowledge.
More recently, Robinson and Davis (1990) analyzed two sets of
national survey data and concluded that television news is less effective than
newspapers in informing media users. The two surveys did not deal with
scientific information but instead with information about current events.
Respondents in the two surveys told interviewers that television was their
principal source of information about current events. However, newspaper readers
were better able than television viewers to recall major news stories from the
preceding week. The present study is an adaptation of the approach used by
Robinson and Davis.
Data
The present study represents a secondary analysis of the 1992
National Science Foundation Survey of Public Understanding of Science and
Technology. Data were gathered through a telephone survey of a national
probability sample of the US population, aged 18 or over. Jon D. Miller of the
Chicago Academy of Sciences executed the survey under contract to the US
National Science Foundation. Data from this study have been reported in a
biennial report which the National Science Foundation is required by statute to
submit to the US Congress (National Science Board, 1993). The 1992 wave was the
seventh in the series.
Survey respondents were identified through a national probability
cluster design. Survey interviews were conducted by telephone from December 29,
1992, through April 9, 1993. Interviews averaged 26 minutes in length.
Interviews were conducted with 2,001 individuals, for a completion rate of 70
percent (Miller, Pifer & Ressmeyer, 1994).
Participants were asked a variety of questions regarding their
attitudes towards science. The survey inquired about respondents' use of various
media, such as newspapers and television. Respondents also were asked a series
of test questions designed to measure their level of science knowledge. The
survey instrument also gathered social locator data, such as sex, age,
employment and education.
The dependent variable for the present study, scientific knowledge,
is operationalized by calculating the number of correct answers that each
respondent provided for 19 science-knowledge questions that were asked in the
NSF survey. These 19 questions are listed in the Appendix. Thirteen of the
questions ask the respondent to state whether a particular statement -- such as
"radioactivity is man-made" -- is true or false. Two of the questions checked
respondents' knowledge by forcing them to make a choice, such as by asking
"which travels faster: light or sound?" The final four questions were based on
a hypothetical scenario about an inheritable disease. Respondents then were
asked about the accuracy of four statements describing the probabilities of a
couple passing the disease onto their children.
By definition, the knowledge score could take on any integer value
from 0 to 19. In this sample, however, values ranged from 2 to 19, with a mean
of 12.5, a median of 13.0, and a standard deviation of 3.4. If a respondent
replied "don't know" or "unsure" to a particular question, it was counted as an
incorrect answer. The distribution of scores is shown in Figure 1.
Independent variables in the present analysis include three measures
of media exposure and the respondent's education and level of interest in
science. Exposure to television news was measured by a question in which
respondents were asked how many hours they watched television on an average day.
Then they were asked: "About how many of these hours are news reports or news
shows?" Answers to this follow-up question ranged from 0 to 21 hours, with a
mean of 1.4 hours, a median of 1 hour, and a standard deviation of 1.2 hours.
For the current analysis, this variable was recoded into a three-level variable
distinguishing respondents who reported watching television news every day for
less than one hour, for one to two hours, or for more than two hours. With this
recoded variable, 23.5 percent of respondents had exposures of less than one
hour, 63.3 percent had exposures of one to two hours, 10.6 percent had
exposures of more than two hours daily, and 2.7 percent had missing values.
The survey measured newspaper use by asking respondents: "How often
do you read a newspaper: Every day, a few times a week, once a week or less than
once a week?" For the purposes of this analysis, the answers were recoded into
a dichotomous variable, distinguishing those who read newspapers daily (55.9
percent) from those who did not (43.9 percent). Respondents who said "don't
know" are considered as missing cases (0.3 percent).
For magazine use, the survey asked respondents: "Are there any
magazines that you read regularly, that is, most of the time? What magazines
would that be?" Interviewers then recorded the titles of as many as five
magazines. For this analysis, the answers were recoded into a dichotomous
variable, distinguishing those who read at least one magazine (66.8 percent)
from those who do not read any magazines (33.2 percent).
Education level was measured in the survey through a question that
asked respondents to provide "the highest level of education you completed." The
original data set includes a variable in which this education-level information
has been recoded into three levels: low (not a high school graduate, 20.1
percent), medium (high school graduate through some college, 60.1 percent), and
high (college graduate or more, 19.8 percent).
The survey also assessed respondents' interest in various issues. One
such issue was described as "issues about new scientific discoveries." Of the
respondents, 36.1 percent said they were "very interested," 49.1 percent said
they were "moderately interested," and 14.6 percent said they were "not at all
interested." The 0.3 percent of respondents who answered "don't know" were
considered missing cases in the current analysis.
Methods and results
The relationship between science knowledge and media exposure was
investigated using multiple classification analysis (MCA), a technique in
analysis of variance that estimates the differences in a dependent variable
after adjusting for other variables. Estimates of the dependent variable are
provided for every category of every independent variable (Nie, Hull, Jenkins,
Steinbrenner & Bent, 1975).
Results of an MCA analysis of the NSF data set are reported in Table
1. The top line of the table indicates that the mean science-knowledge score for
the entire sample was 12.5. The remainder of the table indicates knowledge-score
means for subgroups in the sample with specific levels of each independent
variable. The first column of numbers reports the number of respondents that
fall into each category of each independent variable. The second column of
numbers reports how that subgroup's raw mean knowledge score deviates from the
sample's overall mean. The third column reports how the subgroup's mean
knowledge score deviates from the overall sample mean, once MCA adjusts the
subgroup's raw mean to account for all other independent variables.
Education had the greatest influence of all the independent variables
on the knowledge scores: College graduates answered 4.0 more questions correctly
than respondents without a high-school diploma (p<.001). Interest in science was
the next most influential variable, with high-interest individuals scoring 1.5
higher than individuals with no interest in science (p<.001). Of the three
media-exposure variables, television news exposure had the greatest influence,
with heavy watchers scoring 1.4 lower than the least frequent viewers of
television news (p<.001). By contrast, print media exposure was associated with
higher scores: Magazine readers got 0.6 answer correct compared to non-readers
(p<.001), and daily newspaper readers scored 0.4 higher than non-readers
(p<.01).
Discussion
The results of the present study are consistent with those of
Robinson and Davis (1990) in that print media were more effective than
television in informing individuals. However, the results of the present suggest
a more fundamental difference in how science information is conveyed by print
and broadcast media. High-exposure television viewers did not simply learn less
about science than high-exposure newspaper readers; the high-exposure television
viewers had lower knowledge scores than low-exposure television viewers,
suggesting that in a sense they actually lost science knowledge by viewing
television news.
The NSF data can shed no light on the intriguing question of how this
knowledge loss might occur, because the data include no information on the
specific science content of the various media and only general measures of the
exposures to those media. One possibility is that the television content
contains more frequent scientific errors than did the news content, and that
viewers learned incorrect information which was reflected in lower science
scores. Another possibility is that the television content was no more incorrect
than the print content but that television viewers misunderstood the information
that was being conveyed. Jacoby and Hoyer (1982) found that televised
information is generally miscomprehended at a rate of 23 to 36 percent per
content unit. It may be that the characteristics of televised news, such as its
emphasis on drama and its fast visual pace, may foster miscomprehension of
scientific knowledge, but this is an area that requires further exploration.
The particular measure of science knowledge used in this study does
suffer from limitations as an index of an individual's scientific literacy. The
questions used in this study examine a particular type of scientific knowledge:
that of basic facts or definitions. It does not measure the respondent's grasp
of the scientific process, which might be more useful in equipping an individual
to understand scientific controversies of public impact, such as risk-benefit
issues.
Moreover, the particular measure of media exposure used in this study
also suffers from limitations. As is the case with all time-use questions
predicated on an "average day," the question about daily television usage may
not be accurately answered by respondents, because they may over- or
under-estimate their viewing time. Also, this measure does not reflect how
closely the respondent attended to the television programming; if the respondent
ignored the television -- by reading or working or doing housework, for example
-- the television programming could be expected to have little if any effect on
the respondent.
Further, the NSF data do not include any assessment of the science
content of the media to which respondents were exposed. If television
programming had less science content than print media, this alone could account
for the knowledge differences identified in this study. Finally, it should be
noted that the present study documents only an association; a study using one
year of national survey data cannot definitely distinguish cause from effect. It
is conceivable that individuals with lower levels of scientific knowledge
selectively watch more television news than do individuals with higher levels of
scientific knowledge.
Summary
High levels of exposure to television news are associated with lower
levels of knowledge about basic scientific facts, while high exposure to
magazines and newspapers is associated with higher levels of knowledge. These
associations exist even after accounting for the respondent's level of education
and level of interest in science. These results are consistent with the
hypothesis that television exposure causes lower levels of knowledge of
scientific facts in viewers. However, the present analysis cannot prove this
causation, because the available data do not permit identification of cause and
effect: It is conceivable that individuals with lower levels of scientific
knowledge selectively watch more television than do individuals with higher
levels of scientific knowledge.
References
Durant, J. R., Evans, G. A., & Thomas, G. P. (1989). The public
understanding of science. Nature, 340, 11-14.
Graber, D. (1988). Processing the News: How People Tame the
Information Tide. New York: Longman.
Hazen, R. M., & Trefil, J. (1991). Science Matters: Achieving
Scientific Literacy. New York: Doubleday.
Jacoby, J., & Hoyer, W. (1982). Viewer miscomprehension of televised
communication: Selected findings. Journal of Marketing, 46, 12-26.
Miller, J. D., Pifer, L., & Ressmeyer, T. (1994). Public Attitudes
Toward Science and Technology, 1979-1992: Integrated Codebook. Chicago: Chicago
Academy of Sciences.
Miller, J. D., Suchner, R. W., & Voelker, A. M. (1980). Citizenship
in an Age of Science. New York: Pergamon.
National Science Board. (1985). Science Indicators -- 1985.
Washington, DC: U.S. Government Printing Office.
National Science Board. (1987). Science & Engineering Indicators --
1987. Washington, DC: U.S. Government Printing Office.
National Science Board. (1989). Science & Engineering Indicators --
1989. Washington, DC: U.S. Government Printing Office.
National Science Board. (1991). Science & Engineering Indicators --
1991. Washington, DC: U.S. Government Printing Office.
National Science Board. (1993). Science & Engineering Indicators --
1993. Washington, DC: U.S. Government Printing Office.
Nie, N., Hull, C., Jenkins, J., Steinbrenner, K., & Bent, D. (1975).
Statistical Package for the Social Sciences. New York: McGraw-Hill.
Robinson, J. P., & Davis, D. K. (1990). Television news and the
informed public: An information-processing approach. Journal of Communication,
40(3), 106-119.
Robinson, J. P., & Levy, M. R. (1986). The Main Source: Learning from
Television News. Beverly Hills, CA: Sage.
Wade, S., & Schramm, W. (1969). The mass media as sources of public
affairs, science and health knowledge. Public Opinion Quarterly, 33(1), 197-209.
Appendix
The following survey questions were used to construct respondents'
science knowledge scores. Correct responses are marked with an asterisk (*).
"Finally, I would like to ask you a few short quiz type questions.
This will take about 3 minutes and we will be finished. OK? For each statement
that I read, please tell me if it is true or false. If you don't know or aren't
sure, just tell me and we will skip to the next question. Remember: true, false,
or don't know."
Statement
True
False
DK
"First, the center of the Earth is very hot."
1622 (81%)*
119 (6%)
259 (13%)
"Radioactivity is man-made."
281 (14%)
1458 (73%)*
262 (13%)
"The oxygen we breathe comes from plants."
1712 (86%)*
219 (11%)
70 (3%)
"The father's gene decides the sex of a baby."
1298 (65%)*
418 (21%)
285 (14%)
"Lasers work by focusing sound waves."
529 (26%)
743 (37%)*
728 (36%)
"Electrons are smaller than atoms."
924 (46%)*
460 (23%)
617 (31%)
"Antibiotics kill viruses as well as bacteria."
1100 (55%)
696 (35%)*
205 (10%)
"The universe began with a huge explosion."
753 (38%)*
687 (34%)
561 (28%)
"The continents on which we live have been moving their location for
millions of years and will continue to move in the future."
1583 (79%)*
204 (10%)
214 (11%)
"Human beings, as we know them today, developed from earlier species
of animals."
902 (45%)*
829 (41%)
269 (13%)
"Cigarette smoking causes lung cancer."
1883 (94%)*
84 (4%)
33 (2%)
"The earliest humans lived at the same time as the dinosaurs."
769 (38%)
901 (45%)*
331 (17%)
"Radioactive milk can be made safe by boiling it."
184 (9%)
1332 (67%)*
484 (24%)
"Which travels faster: light or sound?"
Light: 1493 (75%)*
Sound: 400 (20%)
Both the same: 7 (0%)
Don't know: 101 (5%)
"Does the Earth go around the Sun, or does the Sun go around the
Earth?"
Earth around Sun: 1423 (71%)*
Sun around Earth: 436 (22%)
Don't know: 412 (7%)
"Now think about this situation. A doctor tells a couple that their
genetic makeup means that they've got one in four chances of having a child with
an inherited illness."
Statement
Yes
No
Not sure
"Does this mean that if their first three children are healthy, the
fourth will have the illness?"
256 (13%)
1609 (80%)*
136 (7%)
"Does this mean that if their first child has the illness, the next
three will not?"
185 (9%)
1663 (83%)*
152 (8%)
"Does this mean that each of the couple's children will have the same
risk of suffering from the illness?"
1429 (71%)*
426 (21%)
145 (7%)
"Does this mean that if they have only three children, none will have
the illness?"
175 (9%)
1666 (83%)*
159 (8%)
Author Note
I would like to thank Jon D. Miller for providing the data that were
used in this secondary analysis and John P. Robinson for guidance in the
execution of the analysis.
Table 1. Multiple classification analysis of science-knowledge
scores.
N
Unadjusted deviation
Adjusted deviation
All
1936
12.53
Educationa
1 < High school grad
387
-2.25
-1.96
2 HS graduate
1170
-.03
-.03
3 College grad
379
2.39
2.08
TV news exposurea
0 < 1 hr/day
470
.72
.58
1 1-2 hr/day
1257
-.05
-.08
2 >2 hr/day
209
-1.30
-.84
Daily newspaper useb
0 No
851
-.37
-.21
1 Yes
1084
.29
.16
Magazine readinga
0 No
649
-.76
-.38
1 Yes
1292
.38
.19
Science interesta
1 Very interested
698
.61
.49
2 Moderately int
955
.01
-.06
3 Not interested
283
-1.55
-1.01
Note: The superscript a indicates that the difference between
adjusted means for the highest and lowest categories is significant at p<.001.
The superscript b indicates that the difference between adjusted means for the
highest and lowest values of the variable is significant at p<.01.
[--- ??? Graphic Goes Here ---]
Figure 1. Distribution of science knowledge scores, with a minimum
possible score of 0 and a maximum possible score of 19.
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