1. First Monday, Volume 16, Number 4 - 4 April 2011
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This paper reports on college students‘ everyday life information–seeking behavior and is
based on findings from 8,353 survey respondents on 25 U.S. college campuses. A large
majority of respondents had looked for news and, to a slightly lesser extent, decision–making
information about purchases and health and wellness within the previous six months. Almost
all the respondents used search engines, though students planning to purchase something were
more likely to use search engines, and those looking for spiritual information were least likely
to use search engines. Despite the widespread use of search engines, the process of filtering
relevant from non–relevant search results was reportedly the most difficult part of everyday
life research. As a whole, these students used a hybrid information–seeking strategy for
meeting their everyday life information needs, turning to search engines almost as much as
they did to friends and family. A preliminary theory is introduced that describes the
relationship between students‘ evaluation practices and their risk–associated searches.
Contents
Introduction
Literature review
Research questions
Methods
Methodological issues
Results
Discussion

2. Conclusion
Opportunities
Introduction
Besides ―Googling it,‖ how do today‘s college students look for information to solve
problems in their daily lives?
As part of an ongoing research study, we investigated how college students conduct everyday
life research — what types of information needs they have, and what information sources and
practices they use to satisfy these needs.
Developmental psychologists have long identified the early 20s as a crucial time for learning
and applying problem solving skills (Arlin, 1975; Commons, et al., 1989) [1]. Ideally, the
college experience rapidly advances students‘ cognitive development. Students are often
asked about differences in viewpoint, what aspects of a topic may remain unexplored, and
how a piece of knowledge or an issue may serve as a call for individual action later in life.
At the same time, students must perform information–seeking tasks for school, work, and
their personal, daily lives, often for the first time. As a result, information–seeking activities
may be equally or more complex for students than those undertaken by full–fledged adults
who have already adjusted to life at large (Rieh and Hilligoss, 2008).
These factors make college students a unique cohort to study, especially today when an
unprecedented number of students were born digital [2]. A parade of new digital technologies
has been a constant feature in most of their lives. For this generation, information–seeking
strategies are being formed, practiced, and learned. These methods are put to the test in the
vast information landscape of their college years.
Overall, little is known about the everyday information worlds of today‘s college students.
What kinds of information do students frequently need in their daily lives? Which online and
off–line sources do they use for solving information problems? What makes everyday life
research difficult for them?
This paper presents findings from a survey of 8,353 students on 25 U.S. campuses in the
spring semester of 2010. We collected data about how students conceptualized and
operationalized research for personal use in their daily lives.
The primary contribution of this research is an inside view of the early adult‘s everyday life
research process. Specifically, we focus on students‘ blended usage of computer– and human–
mediated communication channels for solving information problems and evaluating sources
in everyday life.

3. Literature review
Scholars in library and information science have long been concerned about college students
and their information problem solving strategies. The concept of information literacy has been
formalized as an essential element of a library‘s mission, especially in college settings
(Maughan, 2001).
In 1989, the Association of College and Research Libraries (ACRL) defined information
literacy as a ―set of abilities requiring individuals to recognize when information is needed
and have the ability to locate, evaluate, and use effectively the needed information‖ [3].
ACRL updated its standards in 2000 in response to three characteristics of the digital age: (1)
a plethora of new information technologies and online information sources, (2) a professional
concern about the ―escalating complexity‖ of the information retrieval environment, and, (3)
the critical need to teach undergraduates skills for lifelong learning [4].
Numerous books and dozens of studies have been devoted to information literacy instruction
and assessment (Eisenberg and Berkowitz, 1990; Gavin, 2008; Gross and Latham, 2009;
Oakleaf, 2011, 2008; Radcliff, et al., 2007; Warner, 2008). Qualitative and quantitative
models for assessing the information problem–solving process have also been developed
(Head and Eisenberg, 2009, 2008; Kuhlthau, 2004).
Despite these efforts, at last count, only 13 percent of a sample of test–takers made up of high
school seniors and college students could be considered information literate [5].
Library and information science researchers have contended many college students have little
or no knowledge of the on–going scholarly research process (Leckie, 1996). Most students are
frustrated by the ambiguity of intellectual discovery (Kuhlthau, 2004).
Moreover, undergraduates struggle with finding different kinds of contexts (i.e., big picture,
language, situational, and information gathering) when conducting course–related research,
and to a lesser extent, everyday life research (Head and Eisenberg, 2009; 2008).
Regardless of the abundant online and off–line sources available to them, most students rely
on a small collection of ―tried and true‖ sources — course readings, search engines, and
Wikipedia for course–related research (Head and Eisenberg, 2010; 2009).
Everyday life research
While one critical gap in the library and information science research has been its
predominant confinement to information literacy in the context of formal learning
environments, there is a thin strand of research about how college students conduct research
for personal use in daily life.
In the mid–1990s, Reijo Savolainen, a Finnish scholar, first defined the research field of
everyday life research. Applying Pierre Bourdieu‘s concept of habitus, Savolainen developed
a framework for understanding information–seeking behavior in work and at home [6].
Notably, he claimed that individuals engaged in hobbies and sought practical information
shaped and solely driven by their personal values and attitudes (Savolainen, 1995).

4. Further studies in everyday life research introduced the concept of information grounds —
purposeful and temporary places where serendipitous and informal information sharing
occurs. These exchanges are a by–product of some intended activity, such as receiving
treatment at health clinics (Pettigrew, 1999).
One study has investigated the information grounds of college students (Fisher, et al., 2007).
Based on interviews (n=729), researchers found students frequently exchanged everyday life
information in bars, coffee shops, and/or in hallways outside of classrooms.
Most college students in the study (70 percent) visited some sort of information ground daily.
Nearly half the sample found the everyday life information they gathered useful, whether it
was about a class or a new idea about life that had not occurred to them before. Overall, the
research suggests college students frequently engage informal, serendipitous information
exchanges with other like minds.
Online activity studies
As a whole there is a relatively small group of studies about everyday life research (Chatman,
2000; Dervin, 1992; Fisher, et al., 2007; Meyers, et al., 2009). A majority of the literature
focuses on information sharing in conventional physically located places. The usage of
alternate networked information grounds, such as Facebook, has yet to be widely studied
(Savolainen, 2009).
The ongoing research from the Pew Internet & American Life Project is a bountiful ―fact
tank‖ about Internet usage. Based on telephone surveys of large U.S. samples, the Pew studies
have focused on individual online activities.
Over the years, several Pew studies have focused on college students and their Internet usage.
A 2002 study (n=2,501) found that 42 percent of college student sample used the Internet to
communicate socially with friends and only 10 percent of college students used the Internet
primarily for entertainment (Madden and Jones, 2002).
In a follow–up longitudinal study findings were compared with the 2002 Pew study and a
2005 replication study (n=7,421) (Jones, et al., 2009). Results from this study showed Internet
usage for entertainment almost tripled for students between 2005 (28 percent) and 2002 (10
percent). Researchers suggested that e–mailing, searching, and browsing habits might have
been replaced, within three years, by the use of Web 2.0 sites like Facebook and YouTube.
More recently, a 2010 Pew study reports how different generations use the Internet, including
millennials — those born between 1977 and 1992 (Zickuhr, 2010) [7]. All in all, the study
found millennials (n=676) frequently engage in a variety of information–seeking activities
using the Internet. They rely on search engines to do so; a majority of them search for health,
news, purchasing, and trip–planning information.
Taken together, studies such as these provide trend data about students‘ online activities. In
particular, the data have measured college students and their increased use of the Internet for
social communication. A large body of scholarly studies has also delved into college students
and their use of social network sites, specifically to acquire online social capital (boyd and
Ellison, 2007; Ellison, et al., 2007; Valenzuela, et al., 2009).

5. The purpose of our research is to provide data about the range of students‘ everyday life
information needs, the online and off–line sources they consult, their evaluation practices, and
the barriers and challenges they have with their processes. Findings such as these are
significant for understanding what kind of lifelong learners college students, who were born
digital, may eventually become.
Research questions
We investigated how college students apply their everyday life information literacy
competencies — independently of course work, professors‘ expectations, and grades.
The goals of this study were twofold: (1) to understand what information needs students have
in their daily lives; and, (2) to explore how students solve and satisfy their needs for personal
information by using online and off–line sources.
We studied how college students are conducting everyday life research in five related areas:
1. What personal information needs occur in the daily lives of students?
2. What sources do students consult for finding everyday life information?
3. What predictors reveal which type of students are more or less likely to use
search engines such as Google for solving information problems?
4. What evaluation criteria do students use to judge the quality of sources they
have found and whom do students ask for help with evaluating everyday life
information sources?
5. What is difficult about conducting everyday life research?
Methods
Our research was conducted as part of Project Information Literacy (PIL). PIL is a national
study in the University of Washington‘s Information School [8]. The ongoing research is a
large–scale study of college students and their research habits. In this study, we have used the
college student experience to study everyday life research behavior.
We collected data for this paper in two phases: (1) student focus groups in 2008, and (2) a
large–scale survey with follow–up interviews in 2010.
Phase one: Student focus groups
The PIL team conducted 11 student focus groups on seven campuses in the U.S. between
October and December 2008 [9]. On average, each session was 90 minutes long. A total of 86
students participated in the sessions.

6. We used the focus groups to find the consensus about participants‘ research habits,
approaches, and experiences. The qualitative data helped define response categories in our
2010 survey. A segment of the sessions focused on everyday life research. We discussed
information needs, behaviors, and sources that college students used.
Participants ranged from 20 to 30 years of age. They were full–time sophomores, juniors, and
seniors from four–year public and private colleges and universities, and full–time community
college students, who had completed at least one semester at the institution [10]. Seventy
percent of the students who participated in the focus groups were female [11].
The focus group sample consisted primarily of students in the humanities or social sciences
[12]. This group of students, we assumed, was likely to be acquainted with ―desk research‖
(i.e., secondary data that has been collected by someone else). The mean GPA for the total
student sample across all seven schools was 3.44, or just above a B+.
Phase two: Large–scale student survey
We also collected data through a large-scale survey we administered to 112,844 students on
25 U.S. campuses from 6 April 2010 through 18 May 2010 [13].
Our sample size was 8,353 responses. The overall response rate was 7.4 percent.
The 22–item survey was administered online and ran for two weeks on each campus. One e–
mail reminder was sent to non–respondents after the first week of the survey launch.
During our ongoing research, we have studied both course–related and everyday life research
processes. We define everyday life information research as the information seeking conducted
for personal reasons and not directly related to fulfillment of a course assignment. This
includes information for solving problems arising in the course of daily life and to satisfy
general inquisitiveness about a topic.
The data appearing in this paper is based on three survey topics about students‘ everyday life
information–seeking behavior. We asked respondents about their needs, approaches,
evaluation methods, and difficulties.
Survey sample
We collected data from a large voluntary sample of sophomores, juniors, and seniors during
the spring of 2010. Table 1 presents an overview of the demographic make–up of sample.
Table 1: Description of the survey sample.
Demographics N Frequency
Total 8,353 100%
Female 5,415 65%
Male 2,823 34%

7. Declined to state 57 1%
No response 58 —
Sophomore 2,255 27%
Junior 2,724 33%
Senior 3,374 40%
18 to 20 yearsold 3,046 37%
21 to 22 yearsold 3,684 44%
23 to 25 yearsold 675 8%
Over 25 yearsold 881 11%
Declined to state 28 —
No response 39 —
Arts and humanities 1,747 21%
Business administration 913 11%
Engineering 883 11%
Sciences 2,316 28%
Social sciences 2,366 28%
Double majors 73 1%
Undecided 48 —
No response 7 —
Private college or university (four–
1,236 15%
year)
Public college or university (four–
7,040 84%
year)
Communitycollege (two–year) 77 1%
More students who were 21 or 22 years old (44 percent) took the survey than students of any
other age group. In other words, the largest percentage of students in our sample were born in
1989 — the same year Timothy Berners–Lee, a researcher at CERN, wrote his initial proposal
describing the World Wide Web.
More of the students in the sample were studying social sciences (28 percent), and the
sciences (28 percent). Other respondents were studying arts and humanities (21 percent),
business administration (11 percent), and engineering (11 percent).

8. The most frequently reported GPA was in the category of 3.4 to 3.7. As a point of reference,
we calculated this grade point average as being between a B+ and an A- [14].
Follow–up interviews
Lastly, we conducted follow–up interviews with students in our sample who had volunteered
their time (n=25).
The sample was segmented along four lines: (1) respondents with high (4.0) vs. low GPA
(2.4), (2) disciplinary area of study, (3) frequent vs. infrequent use of librarians, and (4)
specific difficulties with research.
Each interview was conducted by telephone and lasted from 15 to 30 minutes. The interviews
were recorded and interviewees were asked for their permission to record. An audio file of
eight hours and 10 minutes was the end result.
We used a script with seven open–ended questions as a guideline for the conversational
interviews with participants. To ensure consistency, the same person conducted all of the
interviews.
Methodological issues
There are several challenges associated with using a survey methodology in any social science
research study.
It is one thing to limit conclusions to the sample of respondents who actually participate in the
study and quite another when an attempt is made to generalize from those responses to some
larger population.
The sampling strategy for descriptive studies relies upon the degree to which the sample is
representative of a larger population. The most common approach to this problem is by means
of a sampling design where there is a known probability of inclusion for every respondent
sampled from a larger population.
In our research, the sample for our 2008 focus groups and 2010 survey were both composed
of self–selected volunteers from a larger population. Such samples may be biased in unknown
ways. There is no basis for making inferences to the population from the sample responses.
Another frequent issue is response rate. A limitation of our study is the seven percent
response rate to the student survey. Clearly, a seven percent response rate is too low to be
generalizable to the entire college student population.
Instead, analytical studies such as ours test the robustness of relationships appearing in the
data. Thus, while it might be difficult to argue about the absolute level of utilization of a
specific information–seeking technique, for example, focusing on relationships allows us to

9. test the robustness of what has been found. It can be argued that these relationships do exist in
the larger population and could be seen in any sample used to describe them.
While fully acknowledging that further research is required to confirm our findings, especially
in terms of generalizing to the full college population, we assert that the relationships among
variables are consistent across samples and reflect relationships that do exist in the larger
population.
Clearly, response rate matters, but it matters more in descriptive than in analytical studies.
This issue has been raised and the importance of a high response rate has been questioned in
the last five or six years. The American Association of Public Opinion Research (AAPOR)
(and others) has published provocative studies claiming the relationship between response
rates and survey quality has become less clear [15].
Results
Unsurprisingly, we found different information needs arose in the daily lives of college
students.
Could a recent tick bite cause Lyme disease? What news is being reported in the hometown
newspaper? What does a diagnosis of breast cancer mean for the patient? What is the starting
salary for civil engineers? What are the values of a certain religious group? [16]
In our focus groups, participants identified three kinds of information needs. Participants
discussed searching for information to (1) satisfy curiosity, (2) find a fact quickly, and (3)
solve a specific information problem (Head and Eisenberg, 2008) [17].
Almost all of the participants described searches to satisfy their curiosity (e.g., the year in
which the Boer War ended) and information for fact–finding (e.g., movie times at a local
theater) as being quick one–offs.
Students also discussed searches for solving some information problems they considered
somewhat riskier and more complicated. These searches sometimes lasted for days, especially
since there was no deadline assigned by an instructor or a grade given as with course–related
research (e.g., what a diagnosis of cancer in a relative meant).
As one participant explained, ―Everyday research can be circuitous and time–consuming and
it does not involve the same type of research skills as course–related research does. Often a lot
is at stake with everyday research — the only way to find out if you are right is to go out into
the world and see if your answer works for you.‖
We heard similar comments about the connection between the importance of the problem and
search time and effort from survey respondents in the follow–up interviews. One respondent
said, ―Money is a big basis for how I research things in my life. The more expensive
something is, the more time I‘m going to research and determine whether I really want it.‖

10. Another survey respondent described a search for information requiring computer–mediated
along with human–mediated sources.
In the case of curing food, if you do it improperly you
can get sick and die. I went online and looked through a
couple of blogs but the comments sounded really corny,
so I blew those off and found a cookbook with basic
information online.
You need to be careful about what your sources are. I
looked online but I also went to the County Extension
Office and asked for credible sources, too. If you‘re just
writing a paper for class, it reflects on your knowledge,
skills, abilities and ethics. If you‘re curing a ham, the
knowledge, skills, ability and discernment you use
actually affect your health and your life. Bigdifference.
Taken together, nearly all of the participants agreed they were ―more caught up‖ and ―more
engaged‖ in everyday life research than with course–related research. This was especially true
when searches were meant to solve information problems with higher–stakes or real–life
consequences.
Information for making decisions
Students we studied had a strong need to know what is going on in the world beyond the
campus. More students in our survey sample (79 percent) had searched for news in the
previous six months than for anything else (see Figure 1).
Yet, as a whole, the majority of students‘ information needs were directly related to personal
decision–making in their daily lives. Nearly three–quarters of the sample reported looking for
information about a product and/or a service (74 percent) and/or health and wellness topics
(74 percent). Another two–thirds of the sample had searched for information about jobs or a
career (67 percent) and about travel and trip planning (61 percent).
Looking for information for making decisions trumped finding someone with similar
interests, (i.e., social communication). Slightly more than half of the respondents (51 percent)
reported searching for information for making social contacts. These findings suggest
respondents drew a distinction between needing information for solving everyday life
problems vs. communicating with others.
Further, less than half the sample reported that their recent search for information was related
to their domestic life (46 percent). About a third of the respondents (36 percent) had searched
for an answer to a work–related question and/or information about advocacy or causes (32
percent). Still, fewer students in the sample (24 percent) searched for spiritual information
about a group and/or beliefs or to find an expert, such as a physician, therapist, or attorney (20
percent).
Overall, the results reveal students‘ in our sample had an underlying hierarchy to their
information needs. While most respondents sought information for staying current, another
two–thirds of the sample looked for information about making decisions directly related to

11. their individual lives (e.g., purchasing something, health/wellness, finding a job, and trip
planning).
At the same time, few respondents appear to have searched for information that might lead to
community involvement or civic engagement (i.e., advocacy or spiritual/religious
information). These findings suggest students‘ more frequent information needs may be more
motivated by personal needs than community engagement.
Figure 1: Students‘ everyday life information needs.
This figure shows information needs arising for respondents within the previous
six months. Respondentswereasked to ―click all thatapply.‖
Finding information
Almost all the respondents relied on the same few information sources for finding everyday
life information. A large majority of respondents used the Web for everyday life information
needs. Nearly all of the respondents (95 percent) used Web search engines for gathering
everyday life information (see Figure 2).
Similarly, focus group participants also mentioned using search engines. Unsurprisingly, most
participants mentioned Google by name.
The combined familiarity of using Google and accessibility drove its use. As one focus group
participant put it: ―Google is always my first step, even though I know it may not be the best
first step, but it is my most accessible one.‖
In our student follow–up interviews, we also found that search engines serve up consensus,
which some value. As one interviewee said, ―typing something into Google and finding the

12. same information from different sites verifies information for me — most people agree; they
are thinking the same thing about a given subject — it works.‖
Another frequently used source was Wikipedia. Almost nine out of 10 in the survey sample
(87 percent) reported using it for everyday life research.
When talking with students, we found an inevitable relationship between Google and
Wikipedia. In other words, they students recognized that a Google search often returned a
Wikipedia entry on the first page of results.
As one participant in the focus groups explained: ―I don‘t really start with Wikipedia; I
Google something and then a Wikipedia entry usually comes up early on, so I guess I use both
in kind of a two–step process.‖
A survey respondent we interviewed reported going to Wikipedia because ―for the most part I
trust Wikipedia because it is something that is double–checked by its users pretty frequently.‖
Yet, we also found students surveyed did not solely rely on the Web when asked how often
they consulted a list of 13 computer–mediated and human–mediated sources. A large majority
of respondents also reported turning to friends/family, and classmates (see Figure 2).
Over four–fifths of the respondents (87 percent) turned to friends/family and classmates (81
percent) for everyday life information. To a far lesser extent, the sample turned to instructors
(53 percent), and librarians (14 percent).
Convenience was a trigger for prioritizing the use of certain sources — both computer– and
human–mediated. As one focus group participant explained, ―I know it sounds kind of bad,
but I‘ll only ask a person for everyday life information if they are closer than my computer.‖
In a follow–up interview, a survey respondent said, ―my parents are generally the first people
I ask because they are overall pretty intelligent and I can always get a hold of them.‖
A large percentage of respondents also relied on their own documentary collections (75
percent) to meet information needs in daily life. These were materials already had in hand
(e.g., notes, books, magazines, printouts of online materials).
A majority of the sample used other Web sites to find information. Almost two–thirds of the
sample (63 percent) reported turning to government Web sites. Half the sample (50 percent)
used blogs for everyday life information.
At the same time, seven out of 10 respondents (70 percent) used social network sites, such as
Facebook, for everyday life information. The finding suggests respondents used social
networks for solving information problems as well as for social communication.
We were struck by respondents‘ reported use of online research databases (e.g., JSTOR,
EBSCO, or ProQuest) for everyday life research. The sources are usually considered the
domain of course–related research and are available through the campus library.
Yet, well over a third of the respondents also reported using research databases (40 percent)
for finding everyday life information. Other campus materials used for personal searching by

13. students in the sample included online and print encyclopedias, such as Britannica (37
percent) and the campus library‘s shelves (28 percent).
Overall, findings confirm the conventional wisdom — the Web, and especially search
engines, are the go–to sources for finding information everyday life. At the same time,
respondents report, also relied heavily on friends, family, and classmates almost as much as
they relied on the Web for everyday life information.
These findings suggest respondents are driven by familiarity and habit. The use of convenient
nearby sources drives usage. Yet, to a lesser extent, respondents consulted materials in the
campus library, including scholarly research databases. This finding suggests students may
have also a need for authoritative fact–finding sources found through the library when
conducting everyday life research.

14. Figure 2: Sources students use for everyday life information.
Results are ranked from the most to the least frequent sources students used
for everyday life research within the previous six months. Responses of
―almost always,‖ ―often,‖ and ―sometimes‖ have been conflated into a new
category of ―use.‖
Ubiquitous search engine usage?

15. That nearly all of the respondents used search engines to find everyday life information is
unsurprising. What needs to be examined, however, are the circumstances in which search
engines were more likely to be used — and not used.
We used logistic regression analysis to investigate which members in our college student
sample were likely to use search engines to meet which kinds of information needs.
We examined the relationship of specific student characteristics (i.e., age, major, information
resource usage, and information needs) to the likelihood respondents would use search
engines for everyday life research (see Table 2).
The model contained 27 independent variables in three groups:
1. Information needs (i.e., health/wellness, news, purchasing, job–related
questions, domestic life, work/career planning, spiritual, travel, advocacy,
social contacts, and experts).
2. Information resource usage (i.e., Wikipedia, friends/family, classmates,
personal collection, government sites, scholarly research databases, social
networks, instructors, encyclopedias, blogs, library shelves, and librarians).
3. Major area of study (i.e., arts and humanities, business administration,
engineering, sciences, and social sciences).
The model‘s dependent variable was ―the use of search engines.‖ We determined use by
students‘ response to a survey questions about the use of search engines during the everyday
life research process.
The full model containing all predictors of search engine usage correctly classified 98.6
percent of the cases and had a (Nagelkerke) R–squared value of 28 percent. In other words, 28
percent of all the variance in the use of search engines can be accounted for by these
variables, using this model.
As shown in Table 2, although their effect was small, five independent variables were
associated with search engine usage with some substantive significance (.05 percent) level.
These variables appear bolded and asterisked in the first column of the Table below.
Table 2: Predicting the probability of using search
engines during everyday life research.
Odds 95% for C.I.
B S.E. P
ratio Odds ratio
Lower Upper
Health/wellness .260 .227 .253 1.297 .831 2.206
News .253 .226 .264 1.288 .827 2.006
*Purchasing .812 .239 .001 2.253 1.411 3.596
At–work question -.162 .254 .524 .851 .517 1.399

16. Domestic life .194 .257 .451 1.214 .734 2.007
Work/career .278 .227 .219 1.321 .847 2.060
*Spiritual -.641 .262 .014 .527 .315 .880
Travel .355 .248 .152 1.426 .877 2.318
Advocacy .017 .304 .954 1.018 .561 1.847
Social contacts .322 .271 .234 1.380 .812 2.347
Search for expert .733 .441 .097 2.081 .876 4.942
*Blogs .730 .164 .000 2.075 1.504 2.863
*Wikipedia .492 .086 .000 1.635 1.381 1.936
*Government
.513 .115 .000 1.670 1.332 2.093
sites
Scholarlydatabases .199 .122 .102 1.220 .961 1.548
Librarians -.305 .182 .094 .737 .516 1.053
Library shelves .017 .156 .915 1.017 .748 1.381
Instructors .089 .114 .434 1.094 .874 1.368
Encyclopedias .087 .130 .504 1.091 .845 1.408
Classmates .111 .126 .377 1.118 .873 1.430
Friends/family .080 .115 .486 1.084 .865 1.358
Social network
.129 .099 .192 1.138 .937 1.381
sites
Arts and
humanities majors .416
(default)
Business majors .539 .365 .140 1.714 .838 3.506
Engineering
-.117 .266 .660 .889 .528 1.498
majors
Social science
.199 .377 .598 1.220 .582 2.557
majors
Science majors -.111 .373 .765 .895 .430 1.860
-
Constant .504 .000 .085
2.465
Overall, the strongest predictor of using search engines was someone looking for information
about purchasing something, with an estimated odds ratio of 2.25 (controlling for all other
factors in the model). That is, the odds of someone using a search engine are 2.25 to one
compared to their election not to use a search engine.

17. There three other predictors of search engine usage were: (1) someone who also used blogs
for everyday life research, with an estimated odds ratio of 2.08 (controlling for all other
factors in the model); (2) someone who used government sites for everyday life research, with
an estimated odds ratio of 1.67 (controlling for all other factors in the model); and, (3)
someone who used Wikipedia for everyday life research, with an estimated odds ratio of 1.64
(controlling for all other factors in the model).
Findings suggest respondents were likely to use search engines in combination with a small
set of other information sources — blogs, government sites, and Wikipedia. Given the
interactive nature of blogs, this finding suggests blogs may be a frequented networked
information ground for search engine users.
Respondents who were looking for spiritual information about a group or beliefs were less
likely to use search engines for everyday life research, with an estimated odds ratio of .53
(controlling for all other factors in the model) [18].
In other words, about half as many respondents used search engines when searching for
spiritual information as when searching for other types of information.
Overall, the predictors from our model about the use of search engines are as follows:
1. Respondents planning to purchase something were twice as likely to use search
engines than those who were not (controlling for all other factors in our
model).
2. Blog readers were twice as likely to use search engines than respondents who
did not use blogs (controlling for factors in our model).
3. Respondents who used government sites and/or Wikipedia were one and half
times more likely to use search engines than respondents who did not
(controlling for all other factors in our model).
4. Those who looking for spiritual information about a group and/or beliefs were
less likely to use search engines than those who were not looking for spiritual
information.
Critical to a fault
Most searches for information involve sizing up the information quality of a source once it is
found. Is the source credible? Is the source up–to–date? Is the information accurate? Is the
source useful for the solving the information problem at hand?
We collected data about how frequently respondents judged sources using three criteria: (1)
self–taught criteria, (2) traditional standards from the print world, and (3) domain–specific
standards (see Figure 3).
Overall, we found most respondents were frequent evaluators of information for personal use.
More than any other criteria, respondents relied on self–taught criteria for assessing the
quality of everyday information they culled from the Web. More often than not, a site‘s
design received the most scrutiny (56 percent) [19].

18. As one participant in our focus groups explained, ―the design of a site does a lot for me, if the
color is bright pink, or lots of ads, or looks like it was made by a 15–year–old, then I think it
probably isn‘t worth my time.‖
Similarly, in a follow–up interview, a survey respondent said: ―When I‘m searching the Web,
one of the biggest things that I‘m going to look at is the ease of use and if there is a bunch of
broken links or ads for weird products then it‘s a site I generally won‘t trust.‖
Another deciding factor for respondents was a site‘s familiarity. More than half of the
students surveyed (54 percent) reported that whether they had used the site before was a
frequent criteria used for assessing the quality of Web content.
Yet, familiarity was clearly different than referrals, according to students sampled. Fewer
students (44 percent) relied on whether they had heard about a site before and even fewer (11
percent) considered whether a librarian referred a site to them to use.
At the same time, students relied on traditional and formal standards — timeliness and
authority — from the scholarly print world and librarianship. More than half of the
respondents (54 percent) considered the currency of Web content (e.g., checking the data in
footer details). They also relied on the authority of posted content, too, by judging the origin
of a site‘s URL (49 percent) and/or an author‘s credentials (49 percent).
The least applied standards were domain–specific standards. That is, criteria specific to the
Internet and often used for judging reliability, authority, and credibility of Web content (e.g.,
linkage, origins of a URL, footer details). Specifically, we found less than half of the
respondents (43 percent) checked for a site‘s external links whether an author had credited
sources used (32 percent), and/or whether there was a bibliography of some kind (23 percent).

19. Figure 3: Criteria for evaluating Web content.
Results are ranked from most frequent to least frequent evaluation techniques.
Responses of ―almost always‖ and ―often‖ have been conflated into a new
category of ―frequent use.‖
Ask a friend
Students in our sample not only turned to people as information sources — they also trusted
them when evaluating the quality of the sources they had found (see Figure 4). Almost two–
thirds of the sample (83 percent) turned to friends and/or family when they needed help
evaluating sources for personal use — more than any other people in their lives [20].
Respondents also asked classmates (74 percent) and instructors (45 percent) for help. Yet, far
fewer students asked licensed professionals (35 percent) or librarians (14 percent) for
assistance when evaluating information in their everyday lives.
Students in the follow–up interviews explained friends, family, and in some cases, professors
were both trusted and convenient sources for both recommending sources and discussing the
quality of information they found.
One student from the survey said, ―I will ask my friends or my parents or even some
professors about a Web site they would suggest, especially if I‘m making purchases. For sure,

20. I ask them for their knowledge and experiences so I don‘t have to learn the hard way by
having a bad experience.‖
A few students we interviewed also said they often searched and evaluated online content on
their own. However, if a search was important enough to them (e.g., making a purchase) they
turned to another person in their lives for assistance.
One student from the survey explained, ―sometimes I ask someone else, but it really depends
on what I‘m buying or how important something is to me but I usually wouldn‘t ask someone
about the reliability of a source because I feel I am pretty good at judging for myself what‘s
reliable and what I probably should stay away from.‖
Overall, we found evaluation rarely occurs in a vacuum for the majority of students. Students
tend to take little at face value when it comes to conducting everyday life research. Moreover,
the findings suggest evaluation of sources frequently occurs and it is far from being a solitary
task. Most students rely on friends and family when they need assistance — people in their
lives close at hand, available, and trusted.
Figure 4: Asking for help with evaluating everyday life sources.
Results are ranked from most frequent to least frequent used people students
turn to for evaluation guidance and help within the previous six months.
Responses of ―almost always,‖ ―often,‖ and ―sometimes‖ have been conflated
into a new category of ―use.‖
Difficulties: Sorting and sizing up

21. Lastly, we investigated the difficulties with the everyday life information–seeking process.
We collected data about 15 categories of research challenges.
We found respondents experienced the most problems during the later stages of the search
processes for personal use (see Figure 5).
As a student in the focus group sessions explained: ―What‘s hard is finding the ‗right‘ source
that is exactly what you are looking for — it‘s all there, but then how do I find that one source
that helps later on when I need it again?‖
Moreover, students surveyed struggled most with sorting through all they had found. Filtering
relevant from non–relevant results (41 percent) was more difficult than anything else, the
respondents reported.
To a lesser extent, students also reported being hobbled by being unable to locate information
that they knew existed (33 percent). A quarter of the sample had trouble deciding when their
search for an answer/information was actually finished (23 percent).
Evaluating sources for personal use (24 percent), and particularly, determining credibility (26
percent) also hampered a third or less of the sample of students.
The task of finding an information source — an early step in the search process for personal
use — was not as problematic for respondents (18 percent).
Likewise, few of the sample reported having problems finding Web content (11 percent),
creating search terms (17 percent), reading materials online (19 percent), finding current
sources (19 percent) or finding articles in databases (20 percent).
The findings suggest that students have the most difficulty with using information —
selecting from results they have searched and then netted — rather than the initial decision of
which information source to use for a search.
The widespread use of search engines may further explain why sorting through results was
difficult. Even the most poorly constructed search queries are likely to return results when
search engines are used. But, making sense of the results — deciding and prioritizing
relevance — is more complex and challenging.
Typing in a few search terms in the input box may be fairly easy, but deciding what use may
be far more difficult. If an inferior information source is selected and applied, it may have dire
personal and financial consequences, depending on the information need.

22. Figure 5: Difficulties with everyday life research.
Results are ranked from most to least agreed statements about student difficulties
with everyday life research. Responses for ―strongly agreed‖ and ―somewhat
agreed‖ have been conflated into a new category of ―agreed.‖
Discussion
Overall, our data present surprising findings that belie conventional wisdom about the
information–seeking habits of college students outside of the academic realm.
By far, not all of the searches college students conduct in their daily lives are one–offs to
satisfy a passing curiosity, settle a bar bet, or to find something to do that night.
Instead, our discussions with students revealed that many searches involve decision–making
to resolve a specific problem with real–life consequences. These searches were more time–
consuming, sometimes going on for days. Almost all of the participants in our focus groups
agreed that everyday life research was far more engaging than course–related research.

23. For many students surveyed, search engines such as Google were the go–to–source for
everyday life information. At the same time, it is significant that we found some exceptions to
the ubiquitous search engine rule.
Notably, when students in our sample were seeking spiritual information they were least
likely to use search engines — about half as many respondents used search engines when
searching for spiritual information as when searching for other types of information.
The data we present, though, does not explain why students use search engines less when
looking for spiritual information. One explanation for this finding — the 24 percent of the
sample who looked for spiritual information — is students found religious information (e.g.,
printed brochures) without using search engines [21].
In this sense, the data we collected from our questionnaire is limited. Our survey did discover
spiritual information was a topic least queried with search engines, but this finding raises
some interesting questions that are beyond the scope of our study and worthy of future
research. For instance, what other topics may not be ―search engine–first‖ topics? Why,
according to users?
At the same time, we found respondents were more than twice as likely to use search engines
when looking for purchase information [22]. This data suggests students do not use search
engines under the same information–seeking conditions. In short, the findings tell us not all
Google searches are created equal when it comes to information seeking in everyday life.
Moreover, we found a majority of our sample frequently used Wikipedia, social networks,
and government Web sites for finding everyday life information. This finding suggests
students use an information–seeking strategy that is not single–source driven. In other words,
students‘ searches for personal use do not automatically start and end by typing a few
keywords into Google — many go to site addresses they already know.
To that end, it is significant that respondents reported using friends and family in their
everyday life information–seeking process. The students we studied turned to friends and
family more than they did Wikipedia. More than four–fifths of the respondents asked friends
and/or family when they needed help evaluating sources for personal use. This finding
suggests students use a hybrid information–seeking strategy that blends online sources (e.g.,
Wikipedia) with off–line sources, such as people that they know.
In a larger sense, these results are striking if they are compared with data we collected from
the same sample about course–related research. We found fewer students in the sample turned
to someone else for help when evaluating materials for assignments (Head and Eisenberg,
2010).
These findings lead us to conclude that evaluating information for personal use is a critical
and highly collaborative process, perhaps, more than most may think. All in all, few students
appear to let Web content stand on its own. Many students appear to apply a multi–faceted
self–taught criterion for judging Web content, sizing up the design of a site, its familiarity to
them, and its timeliness. In many cases, students discuss the quality of the information they
have found online with a trusted friend or family member.
A preliminary theory

24. Our data lays the groundwork for a preliminary theory of the Web evaluation process used
during everyday life research by young adults. Our theory proposes college students use a
fairly involved process when evaluating — not just finding — certain kinds of Web content.
While researchers have found people initially use interpersonal sources (i.e., friends and
family) for finding information sources about recreational activities (Kayahara and Wellman,
2007) and music (Tepper, et al., 2008) and then go online for supplementary information, our
preliminary theory adds another piece to this puzzle. Our preliminary theory describes the
relationship between students‘ evaluation practices and their risk–associated searches.
Our student interviews, in particular, suggest students may be more likely to use a blended
evaluation process by employing both online with off–line sources when more is at risk (e.g.,
spending money). In other words, when students perceive the consequences to be greater, they
are more apt to go off–line to double–check the quality of information they have found with a
human–mediated source, or sources.
At the same time, we fully acknowledge these suggested outcomes are based on a small set
data in our study, derived from student interviews (n=25) or focus group comments (n=86).
We have no data from the survey sample (n=8,353) connecting the relationship between
associated risk and the likelihood of using a computer–mediated and human–mediated
evaluation process.
We therefore recommend further research to explore the relationship between evaluation
practices and risk associated searches in order to substantiate our preliminary theory. Results
from a large survey sample along with statistical testing may help to reveal useful results. In–
depth interviews may present other methodological options adding qualitative depth and
richness to the data collected.
In either case, if it holds true that students ―amp up‖ their evaluation efforts during risk
associated decision–making, the findings would add an important piece to a blended Web
evaluation theory. Future research may be able to answer additional questions about how
online channels may be interwoven with human–mediated ones, to what extent, in what order
of use, and under what information–seeking circumstances. What is the basis of a risk–
associated search for students, besides making purchases? How far do students go in their
evaluation process to offset their anticipated risks?
Depending on the findings, of course, the data may show today‘s students spend time, dig
deep, and double–check certain kinds of information well beyond what they find before them
on the screen — even when answers may not be as nearby and convenient as what they may
be able to find online.
In a larger sense, these findings provide further data that debunks the myth of ―digital
natives.‖ In other words, the findings would lend support that not all students who were born
digital go online for everything. Our findings suggest many of today‘s students may not think,
learn, and find information in profoundly different ways from prior generations [23].
Ironic twist
Lastly, we address an ironic twist in our data, which suggests a different research opportunity.
Despite their widespread use of search engines, our sample struggled with processing all that

25. the sites served up to them. Specifically, more respondents found it difficult to sort relevant
from irrelevant results than anything else when trying to find information for use in their daily
lives.
This finding leads us to conclude that making use of everyday life information — getting to
the most useful information — may be the information literacy skill students lack the most
when it comes to their everyday life information research process.
Future research in information literacy about the challenges students face beyond their
academic information–seeking activities is much needed. While our data tells us students
suffer from information overload, future research needs to investigate what solutions and
workarounds students may employ and to what end, as far as making them better informed in
daily life.
In the often–neglected area of everyday life research, such studies could help inform
librarians, educators, and administrators what happens to students the day after graduation —
once they enter the workplace, communities, and become full–fledged adults and lifelong
learners.
Conclusion
This study investigated how college students conduct their everyday life research. We studied
the information needs, sources, evaluation practices, and challenges arising when students
looked for information to use in their daily lives.
Overall, wefound:
1. Beyond the academic realm, college students frequently searched for
information about news, purchases, and health/wellness in their daily lives.
Respondents used search engines most often. Yet, they also turned to friends
and family nearly as much, and also asked them for help with evaluating the
quality of what they had found. These findings suggest students use a hybrid
information–seeking process for finding information for personal use,
combining computer–mediated sources with human–mediated ones in a fairly
complex evaluation process.
2. College students‘ reliance on search engines to meet any and all information
needs did not always prove to be true under any circumstances in our study.
Respondents were least likely to use search engines when looking for spiritual
information about a group and/or beliefs. In addition, they were twice as likely
to be used for finding information about a possible purchase — and for making
decisions with that had some level of financial risk (e.g., spending money).
These findings suggest search engines, despite their frequent use, are not used
for any and all kinds of searches in students‘ daily lives.
3. Ironically, students struggled with processing results and finding the good,
relevant stuff they need. These findings suggest when students are left to their
own — apart from course work, grades, and professors‘ expectations — they

26. may lack the skills for selecting the most relevant results they need for solving
information problems in their daily lives.
Opportunities
Findings from this paper may present opportunities for librarians, educators, information
resource vendors, who want to want to be proactive in training and transferring information
literacy competencies to students. Moreover, their may be opportunities for students, who
want to become more adept at finding information in their daily lives.
1. We have found throughout our ongoing research, as a whole, teaching students
how to develop effective information-seeking strategies for everyday life tends
to be more implicitly than explicitly taught to students on many college
campuses. Curriculum that teaches students how to craft more effective
searches may directly benefit students the most, by giving them the life–long
learning skills they can take into the workplace and their lives after graduation.
2. In particular, students searching for everyday life decision–making information
may benefit from more hands–on training and coaching from librarians and
instructors in developing effective methods for getting at the results they value
most. Also, students may benefit from learning hands–on critical thinking
strategies for asking the most useful questions when turning to friends and
family as information sources and co–evaluators.
3. Based on students‘ use of online database resources for everyday life research,
there may also be some entrepreneurial opportunities for information
publishers. There may be a market in developing everyday life online
information sources for college students, in addition to the part and parcel
sources already developed for course–related research and campus libraries.
4. Lastly, this study lays the preliminary groundwork for further research in four
areas: (1) how to teach and coach college students in finding everyday life
information for use in their lives, future workplaces, and for lifelong learning,
(2) what role blogs may play as networked information grounds in college
students‘ daily lives, (3) what the relationship may be among search engine
usage, decision–making, and associated risk, and (4) the usefulness of a Web
content evaluation theory for describing how students size up Web content
during everyday life research.
About the authors
Alison J. Head, Ph.D. and Michael B. Eisenberg, Ph.D. are the Co–Principal Investigators
and Co–Directors of Project Information Literacy (PIL), which is based in the Information
School at the University of Washington. In the Information School, Head is a Research
Scientist and Lead Researcher for PIL and Eisenberg is Dean Emeritus and Professor in the
Information School.

27. Web: The PIL Web site is located at http://projectinfolit [dot] org
E–mail: ajhead1 [at] u [dot] washington [dot ] edu and mbe [at] u [dot] washington [dot ] edu.
Acknowledgements
We are grateful to Susan Gilroy (Harvard College), David Nasatir (U.C. Berkeley), and Karen
Schneider (Holy Names University) who made useful suggestions for this paper. This
research was sponsored with contributing funds from the John D. and Catherine T. MacArthur
Foundation. A full report of the 2010 study is available at
http://projectinfolit.org/pdfs/PIL_Fall2010_Survey_FullReport1.pdf.
Notes
1. In an effort to expand Piagetian theories of formal thought about cognitive stages of
development, scholars have developed their own theories, based on the assumption that the
distinctive characteristic of adult thought, which often first appears during the ―late formal
stage‖ (ages 17–25), is the acceptance and integration of various, and at times incompatible,
truths that are highly dependent upon context and upon the way in which the individual
perceives them without the individual needing, as the adolescent does, to look for and to find
a single truth.
2. John Palfrey and Urs Gasser (Palfrey amd Gasser, 2008) first used the phrase ―born digital‖
to describe a growing segment of the population born in 1980 or beyond, who have grown up
―immersed in digital technologies, for whom a life fully integrated with digital devices is the
norm.‖ Quoted and retrieved from Berkman Center‘s ―Youth and Media Project‖ site, at
http://cyber.law.harvard.edu/research/youthandmedia/digitalnatives, accessed 1 December
2010.
3. The original definition of information literacy issued by ACRL in 1989 is cited in
―Information Literacy Competency Standards for Higher Education,‖ ACRL Standards
Committee and approved by the Board of Directors of the Association of College and
Research Libraries (ACRL) for American Library Association (2000), at
http://www.ala.org/ala/mgrps/divs/acrl/standards/informationliteracycompetency.cfm,
accessed 1 December 2010.
4.Ibid., p. 2.
5. The sample for this study was drawn from 800 high school students and 3,000 college
students in the U.S. For preliminary results from the study, see Educational Testing Services,
ICT Literacy Assessment Preliminary Findings, at
http://www.ets.org/Media/Products/ICT_Literacy/pdf/2006_Preliminary_Findings.pdf,
accessed 25 February 2011.
6. Pierre Bourdieu‘s concept of habitus is the set of dispositions (i.e., long–lasting habits,
beliefs, values, tastes, bodily postures, feelings, and thoughts) affecting an individual‘s

28. perception and actions in the world. Habitus is derived from the individual‘s personal history,
interaction with others, and surroundings of his/her everyday life (Bourdieu, 1984).
7. Though there is no set definition for describing the age range of millennials, we have used
Pew Internet & the American Life Project‘s definition which describes millennials as those
born between 1977 and 1992 (Zickuhr, 2010), accessed 26 January 2011.
8. For more background about our ongoing research project, see the Project Information
Literacy Web site at http://projectinfolit.org, accessed on 22 December 2010.
9. The student discussion groups were held on seven U.S. campuses with full–time
sophomores, juniors, and seniors at Harvard College, University of Illinois at Urbana–
Champaign, Mills College, University of Washington, and with students, who had completed
at least one semester at three community colleges: Diablo Valley College (Calif.), West
Valley College (Calif.), and Shoreline Community College (Wash.), during October,
November, and December 2008.
10. We intentionally excluded freshmen from our four–year institution sample, and students
who had taken fewer than 12 units from our community college sample. These students were
excluded because they were more likely to discuss the research strategies they had used in
high school, rather than those they had acquired (or were learning) and had begun using in
college.
11. For the discussion groups, we did not intentionally try to balance our sample for gender
(one of the institutions in the campus sample was a women‘s college). Without this campus in
the sample, more than half of the sample from co–ed campuses was female (63 percent).
12. In the discussion group sample, there was representation from students studying
anthropology, art history, communication, economics, education, English, gender studies,
global studies, health, history, international relations, languages, linguistics, music, political
science, psychology, social studies, and sociology. To a much lesser degree (nine percent of
the sample), some student ―walk ins‖ were studying computer science, nursing, engineering,
and business administration.
13. The survey was administered to full–time sophomores, juniors, and seniors at the
following 25 U.S. campuses: Boise State University, Cal Maritime (CSU), Colgate
University, College of William and Mary, Colorado State University, Corban College, Eastern
Michigan University, Felician College, Gettysburg College, Holy Names University, Linfield
College, New Mexico State University, Northern Kentucky University, Northern Michigan
University, Ohio State University, Purdue University, St. Mary‘s College of Maryland,
Southern Nazarene University, State College of Florida, Manatee–Sarasota, Temple
University, University of Arizona, University of Michigan, University of Minnesota, West
Virginia University, and Winston–Salem University. A Google map of the institutions
participating the sample is also available at: http://tinyurl.com/y4smquw.
14. For purposes of our analysis, we employ University of Washington‘s scale for translating
GPA to letter grades, courtesy of the Office of the Registrar, at
http://www.washington.edu/students/gencat/front/Grading_Sys.html, accessed on 1 December
2010.

29. 15. See ―Response Rates — An Overview,‖ American Association for Public Opinion
Research, at http://www.aapor.org/Response_Rates_An_Overview.htm, accessed 14 February
2011.
16. These are everyday life research questions participants in our 2008 focus groups discussed
having within the previous six months.
17. The explanation of everyday life information research we provide here is based on
students‘ perceptions of the process, through the lens of their experience. We fully
acknowledge that research in the library and information science field provides detailed
frameworks and models for understanding everyday information–seeking behavior (Chatman,
2000; Savolainen, 1995; Dervin, 1992).
18. The survey question (#13) defined spiritual information as a topic and included a
parenthetical example for clarification, as follows: (e.g., finding out about different religious
beliefs.).
19. It is interesting to note that while interface design (e.g., fonts, colors, and layout) was
reportedly used by over half of the sample (56 percent) as a cue for detecting credibility of a
Web site, few respondents reported judging the design of charts (39 percent), specifically, as a
criterion (assuming charts existed on sites).
20. The percentages are based on responses of ―almost always,‖ ―often‖ and ―sometimes‖ in
this paper. In our 2010 report, ―Truth Be Told: How College Students Evaluate and Use
Information in the Digital Age,‖ we conflated ―almost always‖ and ―often‖ into a new
category of ―frequently used‖ and the percentages, therefore, differ, p. 13.
21. Interestingly, a 2001 Pew survey about cyberfaith indicated many of those searching for
religious information on the Web tend to find sites by ―word of mouth,‖ not search engine
searches. Nearly half of Pew‘s study survey sample (46 percent) reported they learned of
religious Web content through family, friends, or a church brochure (or other print materials)
with a Web address printed on it (Larsen, 2001). Clearly, this earlier trend from Pew may still
hold true a decade later — few users rely on search engines for finding religious information
(Jansen, et al., 2010). The researchers conducted a large–scale analysis of over a million
search engine data sets occurring between 1997 and 2005 and searches for religious–related
information. The study used five data sets from Excite, Alta Vista, and Dogpile. Google
search engine results were not included in the data analysis. They found only 1 to 1.5 percent
of the sessions were searches for religious information.
22. Although more respondents reported looking for news (79 percent) rather than purchasing
information (74 percent), the use of search engines for finding news, an independent variable
in our logistic regression model, was not statistically significant. This finding suggests
respondents used a specified news site, such as the site for their hometown newspaper and/or
nytimes.com, rather than using a search engine to find news.
23. For discussions about the limitations of the phrase ―digital natives,‖ see ―The Net
Generation Unplugged,‖ Economist (4 March 2010), at
http://www.economist.com/node/15582279, accessed 26 January 2011 and Howard
Rheingold, 2011. ―Crap Detection 101: Required Coursework,‖ Project Information Literacy

30. Smart Talk, number 5 (3 January), at http://projectinfolit.org/st/rheingold.asp, accessed 4
January 2011.
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Editorial history
Received 8 February 2011; revised 8 March 2011; revised 14 March 2011; accepted 15 March
2011; revised 29 March 2011.
―How college students use the Web to conduct everyday life research‖ by Alison J. Head and
Michael B. Eisenberg is licensed under a Creative Commons Attribution–NoDerivs 3.0
Unported License.
How college students use the Web to conduct everyday life research
by Alison J. Head and Michael B. Eisenberg.
First Monday, Volume 16, Number 4 - 4 April 2011
http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/3484/2857