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Academic Users’ Information Searching on Research Topics: Characteristics of
Research Tasks and Search Strategies
Jia Tina Du* and Nina Evans
School of Computer and Information Science
University of South Australia
GPO BOX 2471 Adelaide SA 5001 Australia
Email: tina.du@unisa.edu.au
* Corresponding author, Telephone: +61-8- 8302-5269 Fax: +61-8-8302-3381
ABSTRACT
Our research project investigated how academic users search for information on their real-life
research tasks. This article presents the findings of the first of two studies. The study data were
collected in the Queensland University of Technology (QUT) in Brisbane, Australia. Eleven PhD
students‘ searching behaviors on personal research topics were observed as they interacted with
information retrieval (IR) systems. The analysis of search logs uncovered the characteristics of
research tasks and the corresponding search strategies. Research tasks were found to be explorative,
uncertain, multifaceted, logical, variable, and successive in nature. The search strategies adopted for
research information included interaction with multiple search systems, exploration from popular
search engines, usage of basic search function, construction of multiple search queries, multi-tasking
reformulation, parallel reformulation, and recurrent reformulation. The implications for supporting
academic users‘ research activities in an end-user searching context and further research are also
discussed.
INTRODUCTION
Information seeking is an essential part of a scholar‘s work. Scholars need to ―find relevant
information, assess the quality of the information, and use information in the research process‖.1
The
collection of information is strategically important to a scholar‘s research work and, by nature,
requires complete interaction with the information. Understanding academic users‘ information
behavior—including both physical and online information seeking and searching behaviors—has

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become an increasingly important research issue.
Studies on academic users‘ information seeking/searching behavior can be divided into two separate
streams. One research stream has been conducted within the areas of information behavior and
interactive IR. This stream was initiated by information scientists with a focus on identifying and
understanding the micro-level characteristics of users‘ behavior. The studies within this stream have
investigated information seeking patterns of academic researchers, 2
associated affective and cognitive
behaviors,3
and interactions with digital scholarly journals, 4
et cetera. The other stream has been
conducted within the area of library service initiated by library researchers and
professionals/librarians with a focus on examining the impact of macro-level users‘ information
behavior on library information service provision and quality as well as promoting the role of libraries
in the scholarly activity. For example, research on understanding how students and faculty find
books,5
how libraries can create collections and design services in order to meet academic researchers'
information needs,6
and how to create user-centered information literacy instructions,7
et cetera. Their
discussions are more from the standpoint of library practice and rely more on indirect methodologies,
such as interviews, questionnaires, and surveys. Our research aims to connect the above two streams.
The research project was designed to compose of two studies. Firstly we examined the current mode
of academic users‘ information searching behavior on research topics, and secondly we explored the
role of the university library academic services in support of academic users‘ information searching
on research topics. We believe that library professionals must fully understand the nature of users‘
research and information searching behavior before they would be able to provide useful and related
services.8
This article reports the findings from the first study which examined academic users‘ information
searching behavior on research tasks when interacting with IR systems. Previous studies emphasize
users‘ behavior but usually ignore the context in which the behavior occurs. The searching tasks
provide a context for studying users‘ information behavior. For example, the behavior of information
searching on research tasks is different from fact-finding tasks. The latter is more straightforward.
Normally, the purpose of doing research is to explore something relatively new, even brand new, and

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to make contributions to the body of knowledge in the field. Just as research tasks are complex and
challenging, so are the processes of information searching. Scholars want more sophisticated search
assistances as much of the information obtained cannot be applied directly without processing into
more appropriate structures.9
The objective of the study reported in this article is to advance the
understanding of information searching behaviors of academic users. The major research problem is:
How do academic users search for research information in an online environment? The specific
research questions (RQ) to be addressed are: RQ1. What are the characteristics of a research task?
RQ2. What search strategies do academic users adopt for research tasks?
LITERATURE REVIEW
Academic Users’ Information Seeking and Searching Behavior
Abundant research has been done to study users‘ behavior as they interact with information and
different types of IR systems. Academic users are regarded as a significant part of user groups and
their information seeking and searching behavior have attracted much attention in recent decades.
Ellis developed models of information-seeking behavior of academics across a number of scientific
disciplines: social sciences, physical sciences, and engineering sciences.10
These studies identified six
common information seeking patterns including starting, chaining, browsing, differentiating,
monitoring, and extracting. Starting comprises the activities that are characteristic of the initial search
for information. Chaining refers to the activities of following chains of citations or other forms of
referential connection between materials or sources identified. Browsing not only includes scanning
of published journals and tables of contents but of references and abstracts. Differentiating is the
activity of using known differences between sources as a way of filtering the amount of information
obtained. Monitoring refers to keeping abreast of developments in an area by regularly following
particular sources. Extracting involves the activities associated with going through a particular source
or sources and selectively identifying relevant material from those sources.
Meho and Tibbo identified four additional behavioral features of the information seeking process of
social scientists, namely, accessing, networking, verifying, and information managing.11
Accessing

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involves scholars‘ activities when gaining access to the materials or sources of information they
identified and located. Networking is characterized by communicating and maintaining a close
relationship with a broad range of people who work on similar topics or are members of organizations.
Verifying is characterized by checking the accuracy of the information found. Information managing
covers scholars‘ activities of filing, archiving, and organizing the information they collect or use in
facilitating their research. For scholars, knowledge is not always immediately obtained or applied and
therefore needs to be gathered, digested, organized, and stored for future use.
Makri, Blandford and Cox‘s recent study on the information seeking behavior of academic lawyers 12
confirmed the information seeking behavioral characteristics originally found by Ellis and his
colleagues in scientific domains. Furthermore, they identified several other behaviors such as
‗updating‘ which was believed to be particularly pertinent to legal information-seeking. Jones
conducted observations on eight students and an instructor working in an academic Legal Aid clinic
and suggested the social nature of legal information-seeking behavior. 13
He highlighted the
importance of online repositories that facilitated the sharing, annotation and tagging of documents to
locate them more easily for re-use. Barrett studied information-seeking habits of graduate students in
the humanities whose behaviors involved browsing, citation chasing, and constantly reading within a
subject.14
Xie observed forty library users' information seeking strategies within an information seeking
episode. 15
The information seeking strategies were characterized by different integration and
combination of eight types of methods and six types of resources. The method related strategies
included acquiring, comparing, consulting, scanning, searching, selecting, tracking, and trial and error.
The resource related strategies included meta-information, part of item/specific information, whole
item, a series of items/one location, one system/multiple databases, and human.
The above studies provide us with insights of academic users‘ information seeking patterns and
searching behaviors by analyzing their searching processes. However, most of the findings are
concluded from the investigations of simulated searching tasks rather than real-life research topics.

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Few of the information searching behavior studies shed light on the doctoral students and their
searching process on research tasks. In addition, limited studies explicitly connect the characteristics
of research tasks to the search strategies.
Information Sources for Scholarly Information
Eelectronic resources including e-books and e-journals have become the most popular format among
researchers. 16
Smith explored the role of electronic journals in faculty‘s weekly scholarly reading
habits. Survey results indicated that electronic access to journals—particularly library-funded
access—is integral to research activities.17
Kibirige and DePalo recognized six basic elements which
were often required in the electronic resources that academic information seekers desired:
accessibility, timeliness, readability, relevance, authority, and full-text.18
It was found that scholars
allowed the direction of their research to be influenced by full-text availability online and became
dependent on the availability of full-text databases in their research and used them in some cases to
the exclusion of all other information sources. 19
Millions of dollars have been invested by university libraries to purchase or develop professional full-
text databases in order to improve scholars‘ access to high quality electronic research resources.
However, studies found that Google Scholar has been embraced by students, scholars and librarians
since its introduction in 2004. Howland and his colleagues 20
undertook a study to compare the
scholarliness of resources discovered using Google Scholar with resources found in library databases.
Their findings showed that Google Scholar was, on average, 17.6% more scholarly then materials
found only in library databases and that there was no statistically significant difference between the
scholarliness of materials found in Google Scholar across disciplines. Google Scholar includes a large
portion of the citations available in library databases. On its website, Google Inc. claims that Google
Scholar works with libraries to determine which journals and papers they have subscribed to
electronically, and then links to articles from those sources when they are available. Local library
resources can be accessed via special library links offered by Google Scholar within the search results.

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METHODOLOGY
The data were collected during a previous study in the Queensland University of Technology (QUT)
in Brisbane, Australia.21
Forty-two postgraduate students who sought various types of information
participated in the study. A wide range of 15 different topic areas were covered. The data mainly
consisted of transcribed think-aloud utterance and search logs during the study participants‘
interactions with IR systems. The searches were captured and recorded by Camtasia Studio software.
In addition, pre- and post-search questionnaires were administered to the study participants prior to
and after each search separately. Follow-up interviews were conducted to allow the study participants
to further clarify their behaviors and underlying thoughts. This data corpus has been used and reported
in part elsewhere.22
The present article reports the results of an analysis of a subset of these data.
Eleven of the 42 study participants‘ search logs were selected and analyzed in order to examine the
nature of academic users' information searching behavior on research tasks. The eleven study
participants were doctoral students from various disciplines in pursuit of some particular research goal.
The search tasks were the participatory doctoral students‘ own PhD thesis topics. There were no
restrictions on the selection of IR systems to be interacted with. The method of search logs analysis
was employed to reveal users‘ search strategies. Search logs recorded characteristics of actual
searching behaviors of the study participants. Search logs analysis has been employed successfully in
previous studies to reveal information about users‘ search strategies which are products of users‘
minds.23
RESULTS
Demographic Information of the Study Participants
Table 1 shows the demographic information of the eleven study participants collected for this study.

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Table 1
Demographic Information
Case of Study
Participant
Gender Age Discipline Web Use (years)
2 M 20-29 Engineering 6-10
6 F 30-39 Information Technology 6-10
7 F 20-29 Engineering 1-5
13 M 30-39 Engineering 6-10
14 M 20-29 Business 6-10
19 F 20-29 Creative Industries 6-10
20 M 20-29 Engineering 6-10
32 F 20-29 Business 6-10
33 M 20-29 Information Technology 6-10
37 F 40-49 Health 1-5
42 F 30-39 Health 6-10
The eleven doctoral students included six (55%) female students and five (45%) male students. Most
of them were in their 20s (64%) and 30s (27%). The study participants were distributed across diverse
discipline areas: Engineering (N=4), Business (N=2), Health (N=2), Information Technology (N=2),
and Creative Industries (N=1). Most participants (82%) had 6 to 10 years of Web use experiences.
RQ1. What are the characteristics of a research task?
The study participants‘ research topics were varied. The searching process and behavior may differ
according to the attributes of a certain research topic. Nevertheless, in this study we were mostly
concerned with common characteristics of research tasks which were different than fact-finding tasks.
A research task was defined as a search task for research-related information used for scientific
purposes. A research task was more complex than a fact-based task. The success and information
seeking behavior on the research task varied from the success and behavior demonstrated on the fact-
based task.24
Based on the examinations of the eleven study participants‘ research topics and search
logs, the following characteristics of research tasks were identified:
 Explorative: The topic of a research task was relatively new in the field.
As Voorbij suggested, when academics started a new research project or had to write a paper,
information was needed on a relatively new topic.25
All the study participants believed that their thesis
topics were novel/original and significant, and their research work would fill the gap in the field and
hence contribute to knowledge in a particular research discipline. The nature of exploration in a

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research task implies that scholars‘ information searching was for the purpose of discovery of
potential resources based on more than one trial.
 Uncertain: The topic of a research task lacked certainty.
Uncertainty was closely linked to the explorative nature. Based on the limited knowledge and existing
descriptions, academic users were not sure the path towards how information would be gathered and
what sort of information would be useful for the research project.
 Multifaceted: The topic of a research task had multiple facets.
A research topic could be divided into several sub-topics. For instance, study participant 14 performed
the searching on his/her PhD thesis topic ―Understanding the differences of regional Chinese
consumers' behavior associated with adopting new mobile technologies‖. In order to observe the
differences between regional Chinese consumers in adopting new mobile technologies, he/she
conducted the searching in the following three steps: (1) searching for information on Chinese
consumers‘ mobile phone adoption behaviors, (2) searching for information on the status quo of 3G
technology (new mobile technology) in the Chinese market, and (3) searching for information on
consumer behaviors toward new innovation in two Chinese regional markets, namely, North and East.
The research task required the study participant to recognize and understand the links between
multiple phenomena and to construct ―meaning‖ from the relevant information found via critical
thinking capabilities and other analytical skills.
 Logical: The topic of a research task was logical in nature.
Academic users critically analyzed and evaluated the gathered information. The sense-making process
required more logic and reasoning activities. More intellectual and mental efforts were needed in
order to achieve ―meaningful‖ constructions.
 Variable: The topics of research tasks varied.
Each of the study participants embarked on different research topics entailing various and specific
information needs. Different from searching on fact-finding tasks, information searching on research
tasks normally did not generate a common-accepted answer. Since the variations in information needs

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of researchers were recognized, the services of providing individual/personalized solutions were
needed. University libraries could tailor their information service to the distinctive needs of individual
researchers.26
 Successive: The topic of a research task was updated at times.
In the current searches, the study participants repeated the searching on the topics which they have
previously searched for as they believed that information was updated at intervals. The successive
property of a research task indicates that academic users‘ information searching is an ongoing activity.
Academic users recurrently tracked related information in order to ensure all the gathered information
was updated.
All the above characteristics of a research task made the academic participants‘ information searching
processes and behaviors more complicated and difficult than searching on fact-finding tasks. The
following sections present the corresponding search strategies for research tasks.
RQ2. What search strategies do academic users adopt for research tasks?
The total duration of eleven searches amounted to approximately 9 hours. Each search averaged
around 40 minutes. The longest session lasted almost 1 hour while the shortest session took less than
30 minutes. The analysis of search logs identified the following types of search strategies during the
academic participants‘ searches on research tasks.
 Interaction with Multiple Search Systems
The study participants adopted the search strategy of interacting with multiple search systems when
searching for information on research topics. Fourteen different types of search systems were
employed during the study participants‘ current searches, which were grouped into the following three
categories:
 Search engines, including Google, Google Scholar, Baidu, Live Search, and Yahoo;
 Library online databases, including ScienceDirect, EBSCO, Engineering Village, and
Willey InterScience;
 Specific Websites with searching features, including AllConferences.com, Local

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Government Directory, Sciencedirect.com, and Wikipedia.
An important strategy was the employment of multiple search systems. All the study participants
except one used several search systems to search for research topics, as illustrated in Figure 1.
Figure 1
Combo of the Search Systems Used by Study Participants
Search Systems Combo Used by Study Participants
Google Scholar &
Library Database
9%
Google & Google
Scholar
28%
Google & Google
Scholar & other
search engines &
other Web sites
18%
Google Scholar
9%
Google & Google
Scholar & Library
Database
9%
Google & Library
Database
27%
The majority (91%) did not limit their research to one information source but utilized multiple search
systems including both popular search engines and library online databases, with the number ranging
from 2 to 6. The users gave themselves a greater opportunity to find articles that were appropriate to
their research topic by using more than one source. 27
Forty-five percent of the study participants
chose both Google/Google Scholar and library databases when searching on research tasks; thirty-
seven percent of the study participants only chose Google/Google Scholar; eighteen percent of the
study participants opted for Google/Google Scholar together with other search engines and Websites
instead of using library databases. None of the study participants used library databases exclusively.
 Exploration from Popular Search Engines
The study participants preferred to explore their research topics from interacting with popular search
engines. Google was used most often for the research information seeking—eleven doctoral students
adopted Google ten times. This was a bit surprising as Google is a general search engine instead of

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research information convergence. Similar results were found in Barrett's study 28
where graduate
students in the humanities regularly used electronic information technology and often utilized generic
Internet search engines to find general information on a topic. The second most frequently used
system was Google Scholar which was employed seven times. QUT library online database
(ScienceDirect) was used twice across the eleven searches. The rest of other search systems were only
used once each. Kibirige and DePalo also concluded that there was predominant preference for search
engines when searching for academic research information.29
Academic users may use search engines
on an exploratory basis when beginning a relatively new subject. In terms of reasons for selections of
information sources, results show that the decisions were based not only on the particular research
topic, the discipline and the level of research required to meet, but also on the accessibility, accuracy,
objectivity and reliability of the information that the systems provided.
The behavior of selecting entrance search systems reflects users‘ searching preference. Figure 2
demonstrates where the study participants initiated a search for research information.
Figure 2
Entrance Search Systems Used by Study Participants
Entrance Web Search System for Reserch Information
Google
64%
Google Scholar
18%
QUT Library Quick
Article Search
9%
QUT Library
Database(ScienceD
irect)
9%
The figure showed that 64% of the study participants used Google as a starting point for research
information. As Study Participant 7 explained "It has been my habit for years." Another 18% of
participants listed Google Scholar as the entrance choice. Study Participant 6 believed that Google

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Scholar provided the ―full text‖ link of research papers to the library databases. The remaining 18% of
the participants used library databases as a starting point because they (e.g. Study Participant 2)
insisted that more high quality research papers were offered by databases than Google and Google
Scholar. In some cases, study participants started with Google just as navigation tool for locating a
specific Website. For example, Study Participant 42 entered the search query ―all conference‖ into
Google in order to find a corresponding URL. His/Her following search activities occurred on the
Website of Allconferences.com.
 Usage of Basic Search Function
The results show that most study participants (73%) preferred to use the basic search function
provided either by popular search engines or by library online databases. The frequency of utilization
of advanced search facilities was low, which only occasionally appeared in three of the eleven
interactions. Study Participants 2, 7 and 13 utilized advanced search features in Google Scholar and
library databases. All of the other participants seemed confident that they could manage on their own
via constructing the complex search query with Boolean (and, or, not) and/or other operators (*, +,
with, ―‖, ()), and entering the queries into the basic search box. For instance,
 "multi-channel" and "video retrieval" (Study Participant 6),
 query (formulation OR reformulation OR modification)(behavior or model*) (Study
Participant 33),
 "nutrition w5 transition" (Study Participant 37).
 Construction of Multiple Search Queries
The results show that the study participants constructed multiple search queries during the searching
processes. A query is viewed as an entire string of terms submitted by a searcher in a given instance.30
Table 2 shows the number of search queries that the eleven study participants submitted to the search
systems.

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Table 2
Number of submitted queries
Study Participant Number of Query Submitted
2 12
6 14
7 26
13 22
14 12
19 4
20 15
32 11
33 20
37 22
42 15
All but one participant (Study Participant 19) constructed over 10 search queries during the current
searches on their research topics, with a mean of 15 queries ranging from 4 to 26. The number was far
higher than the mean of 2.3 queries per user on daily topics.31
The findings demonstrated that
academic users were involved in the much more active information searching process as evidenced in
the selection of multiple search systems and an increased use of search queries. The search queries
included initial query, modified query, and expanded query.
Search queries were reformulated during the complex searching processes. Strategies were made to
solve an information problem during which users‘ intellectual and cognitive activities involved, from
rough understanding through problem solving and critical thinking to innovation and creativity, in
order to integrate discrete even conflicting entities. By nature these strategies were query
reformulations embedded within the information searching processes. The most notable strategies of
query reformulations were multi-tasking, parallel, and recurrent.
 Multi-tasking Reformulation
Multi-tasking reformulation was found to be a key query-formulation pattern for research information
searching. Multi-tasking reformulation refers to ―those sessions in which a user looks for two or more
topics simultaneously in the same search session‖.32
A research topic is normally complicated and the
searching cannot offer a targeted answer. As previously stated, a research task was multifaceted. One
research problem was broken down into several simpler and solvable research questions. Academic

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users explored each sub-topic/facet in order to achieve a comprehensive understanding of the
relationships embedded in the phenomenon. For example, Study Participant 14 sought to understand
the differences between regional Chinese consumers' behavior of adopting new mobile technologies.
He/She examined the research issue by searching on the following sub-research topics: mobile phone
adoption behavior, new mobile phone technology, and regional markets/consumers.
 Parallel Reformulation
Parallel reformulation was a frequent query reformulation strategy. Parallel reformulation refers to
―those sessions in which a user modifies the queries from one aspect of an entity to another or from
one thing to another, both of which share common characteristics‖.33
In this situation, the study
participants continuously modified queries, not necessarily because of the failure of the previous
query but because they needed to seek the associative and/or comparable aspects of a certain topic.
For example, Study Participant 14 tried the query "Chinese consumer adoption behavior" after the
search on "mobile phone Chinese consumer", then submitted the query "China north market",
followed by "China east market"; and submitted the query "Beijing consumer‖, followed by
"Shanghai consumer". Those were the instances of parallel reformulation.
 Recurrent Reformulation
The strategy of recurrent reformulation was noteworthy, which refers to the cases in which a user
enters exactly the same query that has already been used in two or more previous steps.34
The study
participants adhered to the same query several times because they considered the query valuable.
They believed that it was necessary to make a trial of using the same query to search across several
search systems because they presumed that different search systems would return distinct results. For
instance, Study Participant 19 entered the query "creative cluster" firstly into Google then Google
Scholar. As he/she explained during the retrospective interview, ―Google may offer me overview
information of the development of creative clusters; meanwhile, Google Scholar may give me some
academic papers/opinions.‖ Again, Study Participant 2 entered the query "evaporative cooling water
air" both into a library database and Google Scholar since "I cannot find exactly topical papers in the
professional database, I move to more general search engine to see what will happen there".

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DISCUSSION
Where do Academic Users Search for Research Information in Online Environment?
The results indicate that forty-five percent of the study participants utilized library databases along
with Google/Google Scholar, but the library databases were not used solely. Moreover, Google and/or
Google Scholar were considered as the first choice for most academic information seekers (82%).
Only 18% of the participants started their academic information searching journey from library
databases. Compared to the popular search engines, the usage rate of library databases was low.
Millions of dollars have been invested into the purchase/development and maintenance of
professional databases by university libraries. The findings, however, demonstrate that the library
databases were not used to their full potential as a primary search tool by the proposed users in
universities. Why did academic users prefer Google/Google Scholar to library databases for research
tasks? A couple of reasons were provided by the study participants, such as (highlighted in italics):
 Google/Google Scholar has stronger searching functions. (Study Participant 7)
 Authentic and scientific information can be found from Google Scholar. (Study Participant 19)
 Google Scholar is easy-to-use, and provides research papers‘ “full text” links to the professional
databases. (Study Participants 6, 13, 32 and 33)
Apparently, academic users need high quality articles in the format of full text. They used Google
Scholar as they were familiar with the interface which was ―easy to use‖. More importantly, Google
Scholar brings users into contact with resources including full-text and high-quality articles provided
by libraries. Google Scholar cooperates with the database vendors and publishers, which makes
Google Scholar a successful discovery tool for finding scholarly information.35
Libraries may provide
quality information resources in response to users‘ information searching by providing an interface
that is familiar to users.
Characteristics of Research Tasks and Certain Search Strategies
Figure 3 illustrates the matching between characteristics of research tasks and the corresponding

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search strategies.
Figure 3
Characteristics of Research Tasks and the Corresponding Search Strategies
Due to a research task‘s explorative and uncertain attributes, academic users follow a trial and error
strategy by exploring the information from search engines and interacting with multiple search
systems. The selection of search systems also varies between different research topics. The
multifaceted and logical attributes of a research topic determines that scholars normally break down a
complex/large problem into several simpler/smaller questions, then identify the links between the
questions, and construct and synthesize ―meaning‖ from the retrieved relevant information through
assembling multiple search queries and applying multi-tasking reformulation and parallel
reformulation techniques. Academic users dedicate themselves to active information searching by an
increasing use of multiple search systems and multiple search queries. Successive searching and
obtaining updated information are required for research activities. Recurrent reformulation is an
important and useful technique for continuing information collection.
Characteristics of Research Tasks
Explorative
Uncertain
Multifaceted
Logical
Variable
Successive
Search Strategies
Interaction with Multiple Search Systems
Exploration from Popular Search Engines
Construction of Multiple Search Queries
Multi-tasking Reformulation
Parallel Reformulation
Recurrent Reformulation

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How to Support Academic Users’ Research Activities under End-user Searching Context?
End-user searching, to some extent, alienates librarians from users. The relationship between
academics and librarians especially reference librarians under end-user searching context is not as
close as prior mediated IR interaction. The nature of research tasks identified in this study increases
the complexity of information searching processes and the difficulty of attaining comprehensive
information. As realized, academic users IR interaction is not without difficulty. Looking for useful
and high-quality information might become a mental burden to academics. For one thing, the
examining of information searching strategies for research topics shows that the academic users did
not resort to librarians to locate and find information. The only library-related service they used was
accessing the library-fund databases. For another, University libraries claim that they are developing
research-oriented service mechanisms and providing user-centered and individualized academic
information service. A gap may exist between users‘ perceptions and the library‘s provisions in terms
of academic information services support. How does the university library academic information
services play a more active role in the mediation of information by changing from providers of access
to information to participants of interaction with information and innovation still remains a strategic
issue and deserves further attention.
Information searching on research tasks involves huge mental processing on users‘ behalf. The
academic users‘ search strategies identified in this study—multiple search systems, multiple search
queries, query reformulation, and entailed intellectual activities including breaking down, linking and
synthesizing—call for some enhancements in the design of existing IR systems. The new search
technology may be designed to assist users in devising different search queries at different stages of
their information searching process. Many search systems do have a ―searches related to‖ feature, but
it is a different function from the support which is needed for multi-tasking or parallel reformulation
strategies. An IR system may also optimize its interface by providing tools for tagging, categorizing,
and annotating search results, as well as storing relevant information for further use. That would
simplify the processing of collected information and facilitate continuing or successive searches.

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CONCLUSIONS
This study observed eleven academic users‘ information searching behavior within research-task
searching scenarios in the online environment. Academic users‘ searching behavior was measured by
adoption of multiple search systems, construction of multiple search queries, use of basic search
function, and query reformulations. The results provide new knowledge of academic users‘
perceptions concerning research-based tasks and enhance our understanding of real-life information
searching and user behavior in a research environment. But the study limits its findings to users‘
interactions with IR systems. A further study may work on a broader picture of exploring and
modeling common patterns and stages of academic users‘ searching behavior embedded within their
research process.
ACKNOWLEDGEMENTS: The authors wish to thank Heather Brown and Jo Hanisch for their
valuable suggestions on the first draft of the manuscript. We also appreciate the thoughtful comments
from the anonymous reviewers.
NOTES AND REFERENCES
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2
David Ellis, ―Modeling the Information-seeking Patterns of Academic Researchers: A Grounded
Theory Approach‖, The Library Quarterly 63 (1993): 469–486.
3
N. Ford, T. D. Wilson, A. Foster, D. Ellis & A. Spink, ―Information Seeking and Mediated
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Information Science and Technology 53 (2002): 716–727; C. Tenopir, P. L. Wang, Y. Zhang, B.
Simmons & R. Pollard, ―Academic Users‘ Interactions with ScienceDirect in Search Tasks: Affective
and Cognitive Behaviors‖, Information Processing and Management 44 (2008): 105–121.
4
D. Nicholas, P. Huntington, H. R. Jamali & A. Watkinson, ―The Information Seeking Behavior of

19. 19
the Users of Digital Scholarly Journals‖, Information Processing & Management 42 (2006):1345–
1365; C. Tenopir, P. L. Wang, R. Pollard, et al., ―Use of Electronic Science Journals in the
Undergraduate Curriculum: An Observational Study‖, Proceedings of the ASIST 2004 Annual
Meeting (2004): 64–71.
5
Ian Rowlands & David Nicholas, "Understanding Information Behaviour: How do Students and
Faculty Find Books?", The Journal of Academic Librarianship 34 (2008): 3–15.
6
Lotta Haglund & Per Olsson, ―The Impact of University Libraries of Changes in Information
Behavior among Academic Researchers: A Multiple Case Study‖, The Journal of Academic
Librarianship 34 (2008): 52–59; Chern Li Liew & Siong Ngor Ng, ―Beyond the Notes: A Qualitative
Study of the Information-seeking Behavior of Ethnomusicologists‖, The Journal of Academic
Librarianship 32 (2006): 60–68.
7
Clarence Maybee, ―Undergraduate Perceptions of Information Use: The Basis for Creating User-
centered Student Information Literacy Instruction‖, The Journal of Academic Librarianship 32
(2006):79–85.
8
Sandra D. Payette & Oya Y. Rieger, ―Supporting Scholarly Inquiry: Incorporating Users in the
Design of the Digital Library‖, The Journal of Academic Librarianship 24 (1998): 121–129.
9
U.Kruschwitz & H. Al-Bakour, ―Users Want More Sophisticated Search Assistants: Results of a
Task-based Evaluation‖, Journal of the American Society for Information Science and Technology 56
(2005): 1377–1393.
10
Ellis, ―Modeling the Information-Seeking‖; D. Ellis, D. Cox & K. Hall, ―A Comparison of the
Information-seeking Patterns of Researchers in the Physical and Social Sciences‖, Journal of
Documentation 49 (1993): 356–369; D. Ellis & M. Haugan, ―Modeling the Information-seeking
Patterns of Engineers and Research Scientists in an Industrial Environment‖, Journal of
Documentation 53 (1997): 384–403.

20. 20
11
L. I. Meho & H. R.Tibbo, ―Modeling the Information-seeking Behavior of Social Scientists: Ellis‘s
Study Revisited‖, Journal of the American Society for Information Science and Technology 54 (2003):
570–587.
12
S. Makri, A. Blandford & A. L. Cox, ―Investigating the Information-seeking Behavior of Academic
Lawyers: From Ellis‘s Model to Design‖, Information Processing & Management 44 (2008): 613–634.
13
Y. P. Jones, ―Just the Facts Ma‘am? A Contextual Approach to the Legal Information Use
Environment‖, Proceedings of the 6th ACM Conference on Designing Interactive Systems (2006):
357–359.
14
Andy Barrett, ―The Information-seeking Habits of Graduate Student Researchers in the
Humanities‖, The Journal of Academic Librarianship 31 (2005): 324–331.
15
H. Xie, ―Shifts of Interactive Intentions and Information-seeking Strategies in Interactive
Information Retrieval‖, Journal of the American Society for Information Science 51 (2000):841–857.
16
M. Pinto, V. Fernandez-Marcial & C. Gomez-Camarero, ―The Impact of Information Behavior in
Academic Library Service Quality: A Case Study of the Science and Technology Area in Spain‖, The
Journal of Academic Librarianship 36 (2010):70–78.
17
Erin T. Smith, ―Changes in Faculty Reading Behaviors: The Impact of Electronic Journals on the
University of Georgia‖, The Journal of Academic Librarianship 29 (2003): 162–168.
18
H.M. Kibirige & L. DePalo, ―The Internet as a Source of Academic Research Information:
Findings of Two Pilot Studies‖, Information Technology and Libraries (2000): 11–16.
19
R. Pagell, ―Reaching for the Bottle, not the Glass: The End-user Factor of Electronic Full-text‖,
Database 16 (1993): 8–9; B. Macdonald & R. Dunkelberger, ―Full-text Database Dependency: An
Emerging Trend among Undergraduate Library Users?‖, Research Strategies 16 (2000): 301–307.
20
J. L. Howland, T. C. Wright, R. A. Boughan & B. C. Roberts, ―How Scholarly is Google Scholar?

21. 21
A Comparison to Library Databases‖, College & Research Libraries 70 (2009): 227–234.
21
Jia Tina Du, Multitasking, Cognitive Coordination and Cognitive Shifts during Web Searching
(Unpublished Ph.D., Queensland University of Technology, Australia – Queensland, 2010).
22
Ibid.
23
P. M. Hider, ―Constructing an Index of Search Goal Redefinition through Transaction Log
Analysis‖, Journal of Documentation 63 (2007): 175–187.
24
Dania Bilal, ―Children‘s Use of the Yahooligans! Web Search Engine: I. Cognitive, Physical, and
Affective Behaviors on Fact-based Search Tasks‖, Journal of the American Society for Information
Science 51 (2000): 646–665; Dania Bilal, ―Children‘s Use of the Yahooligans! Web Search Engine: II.
Cognitive and Physical Behaviors on Research Tasks‖, Journal of the American Society for
Information Science and Technology 52 (2001):118–136.
25
H. J. Voorbij, ―Searching Scientific Information on the Internet: A Dutch Academic User Survey‖,
Journal of the American Society for Information Science 50 (1999): 598–615.
26
Haglund & Olsson, ―The Impact of University‖.
27
Macdonald & Dunkelberger, ―Full-text Database Dependency‖.
28
Barrett, ―The Information-seeking Habits‖.
29
Kibirige & DePalo, ―The Internet as‖.
30
A. Spink, M. Park, B. J. Jansen & J. Pedersen, ―Multitasking during Web Search Sessions‖,
Information Processing & Management 42 (2006): 264–275.
31
A. Spink, B. J. Jansen & C. Ozmultu, “Use of Query Reformulation and Relevance Feedback by
Excite Users”, Internet Research 10 (2001): 317–328.
32
S. Y. Rieh & H. Xie, ―Analysis of Multiple Query Reformulations on the Web: The Interactive

22. 22
Information Retrieval Context‖, Information Processing and Management 42 (2006): 751–768, p. 761.
33
Ibid., p. 759.
34
Ibid., p. 761.
35
Howland, Wright, Boughan & Roberts, ―How Scholarly is‖.