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

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.

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).

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).

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.

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%

Declined to state 57 1%

No response 58 —

Sophomore 2,255 27%

Junior 2,724 33%

Senior 3,374 40%

18 to 20 years old 3,046 37%

21 to 22 years old 3,684 44%

23 to 25 years old 675 8%

Over 25 years old 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–

year) 1,236 15%

Public college or university (four–

year) 7,040 84%

Community college (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).

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

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.”

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. Big difference.

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

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. Respondents were asked to “click all that apply.”

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

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

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.

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?

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.

B S.E. P Odds

ratio

95% for C.I.

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

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

sites .513 .115 .000 1.670 1.332 2.093

Scholarly

databases .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

sites .129 .099 .192 1.138 .937 1.381

Arts and

humanities

majors

(default)

.416

Business

majors .539 .365 .140 1.714 .838 3.506

Engineering

majors -.117 .266 .660 .889 .528 1.498

Social science

majors .199 .377 .598 1.220 .582 2.557

Science majors -.111 .373 .765 .895 .430 1.860

Constant -

2.465 .504 .000 .085

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.

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].

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).

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,

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

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.

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.

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

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

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, we found:

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

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.

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

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.

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

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

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