The effects of topic familiarity on college students' learning search process
| DOI | https://doi.org/10.1108/AJIM-09-2021-0252 |
| Published date | 16 May 2022 |
| Date | 16 May 2022 |
| Pages | 1151-1173 |
| Subject Matter | Library & information science,Information behaviour & retrieval,Information & knowledge management,Information management & governance,Information management |
| Author | Yijin Chen,Yue Qiu,Hanming Lin,Yiming Zhao |
The effects of topic familiarity on
college students’learning
search process
Yijin Chen
School of Economics and Management, South China Normal University,
Guangzhou, China
Yue Qiu
Faculty of Engineering, The Chinese University of Hong Kong,
Hong Kong, China, and
Hanming Lin and Yiming Zhao
Center for Studies of Information Resources, Wuhan University, Wuhan, China and
Big Data Institute, Wuhan University, Wuhan, China
Abstract
Purpose –This study aims to explore the influence of topic familiarity on the four stages of college students’
learning search process.
Design/methodology/approach –This study clarified the effects of topic familiarity on students’learning
search process by conducting a simulation experiment based on query formulation, information item selection,
information sources and learning output.
Findings –The results characterized users’interaction behaviors in increasing topic familiarity through their
use of more task descriptions as queries, increased reformulation of queries, construction of more purposeful
query formulation, reduced attention to a topic’s basic concept content and increased exploration of academic
platform contents.
Originality/value –This study proposed three innovative indicators which were proposed to evaluate the
effects of topic familiarity on college students’learningsearch process, and the adopted metrics were useful for
observing differences in college students’learning output as their topic familiarity increased. It contributes to
the understanding of a user’s search process and learning output to support the optimization function of
learning-related information search systems and improve their effect on the user’s search process for learning.
Keywords Learning search, Search as learning, Learning output, Topic familiarity, Search process,
Interactive information retrieval
Paper type Research paper
1. Introduction
College students are immersed in a rapidly changing knowledge economy (Van Laar et al.,
2017) with the Internet as their main source of information (Saad
eet al., 2012). As the first step
in their learning courses, they engage in online information searching activities and
homework (Reiso
glu et al., 2020). Their learning output –be it an assignment, a presentation,
or an argument –benefits from these searches. Meanwhile, scholars of both search as
learning (SAL) (Urgo et al., 2020;Eickhoff et al., 2017;Gwizdka et al., 2016;Rieh et al., 2014;
Allan et al., 2012;Agosti et al., 2014) and exploratory search (Marchionini, 2006) have
identified learning as an important function of search. Learning-related tasks constitute the
most typical type of search, namely learning search (Reih et al., 2016;Marchionini, 2006).
College
students’
learning search
process
1151
This work was supported by the National Social Science Foundation of China (20BTQ075), the National
Natural Science Foundation of China (71874130 and 71921002), the Ministry of Education of the People’s
Republic of China (18YJC870026), the Science Foundation of Hubei Province (2019CFA025) and the
Science Foundation of Guangdong Province (2020A1010020032).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2050-3806.htm
Received 1 September 2021
Revised 14 December 2021
13 April 2022
Accepted 23 April 2022
Aslib Journal of Information
Management
Vol. 74 No. 6, 2022
pp. 1151-1173
© Emerald Publishing Limited
2050-3806
DOI 10.1108/AJIM-09-2021-0252
College students typically perform learning search tasks when studying their courses and
participating in competitions, whose topics are initially unfamiliar to many of them. The
existing literature has designed learning-related tasks to determine how users search in
context with different learning-oriented goals, most of which were influenced by Anderson
and Krathwohl’s taxonomy of learning objectives (Anderson and Bloom, 2001).
Research has also investigated the relevant search behaviors and learning outcomes of
different learning-oriented goals (Urgo et al., 2020;Collins-Thompson et al., 2017), the
influence of characteristics (Yu et al., 2018) and users’domain knowledge (O’Brien et al., 2020;
Liu and Zhang, 2019;Bhattacharya and Gwizdka, 2018) on search behavior, and the effects of
search systems (Hu and Kando, 2017;Freund et al., 2016) and tasks (Song et al., 2018;Liu et al.,
2013,2014) on users’learning outcomes. Some studies attempted to measure the motivation
and intention to accomplish learning search tasks (Kim et al., 2012;Collins-Thompson and
Callan, 2005), as well as changes in users’domain expertise while completing learning search
(Zhang and Liu, 2020;Song et al., 2018;White et al., 2009;Wildemuth, 2004).
In learning search tasks, topic familiarity must be better understood, as it was found as a
critical variable that influences searching effects. Topic familiarity refers to a user’s
understanding of a search task. The effects of topic familiarity on search tasks have attracted
much research interest, which were mostly explored by comparing two user groups with
different topic familiarity or between nonexperts and domain experts (Liu and Zhang, 2019;
Liu et al., 2013,2014). Early studies on the effects of domain knowledge have reported that
such knowledge is a major predictor of the search process (e.g. Wildemuth, 2004;Kelly and
Cool, 2002;Marchionini and Maurer, 1995), finding that experts performed faster and more
successful searches than nonexperts. Meanwhile, recent research has observed differences
between experts and nonexperts in that expertise affects query reformulation strategies
(Dosso et al., 2022;Tamine and Chouquet, 2017;Ghosh, 2016;Monchaux et al., 2015) and
learning performance (O’Brien et al., 2020) during information search. These studies showed
that low topic familiarity was strongly associated with students’use of terms from the task
statement and production of fewer new words while reformulating queries and observed no
significant differences in learning outcomes between experts and nonexperts.
However, scholars have yet to thoroughly investigate how and to what extent topic
familiarity affects college students’learning search process. The interactive stages of the
learning search process include not only query reformulation and learning output but also the
selection of information sources and items (J€
arvelin et al., 2015). Furthermore, sense making is
a process in which a user reflects on information units, which then helps them understand
learning output in the learning search process (Marchionini, 2019). Each stage of learning
search must include more indicators to explore the effects of topic familiarity (Dosso et al.,
2022), some of which facilitate search success or failure (Tamine and Chouquet, 2017). Thus,
we argue that an ideal search engine must support each stage of the learning search process
and accurately identify a user’s topic familiarity level, which would require a better
understanding of the differences between interactive activities, while college students’topic
familiarity changes as they undergo the learning and searching process.
This paper aims to explore the influence of topic familiarity on the four stages of college
students’learning search process, that is, how topic familiarity affects their engagement in
the following interactive activities: query formulation, information item selection,
information sources and learning output.
The originality features in this study include the following. Indicators of information items
selection were designed and tested in this study; the indicator of knowledge points of learning
output were studied as a dependent variable, and the effect of topic familiarity on knowledge
points of learning output was explored. In prior studies, researchers have deemed the importance
of information items selection to learning search, but few analyses have tested it for operability;
moreover, studies on effects of topic familiarityonlearningoutputwereparticularlyminimal.
AJIM
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