Relationship between Demographic Factors and Metacognition in Digital
Library Interaction
Heesop Kim
, Aluko Ademola
and Yumi Kim
Department of Library and Information Science, Kyungpook National University, Daehak-ro 80, Daegu, South Korea
Metacognition Awareness, Digital Library Interaction, Information Searching, University Students, Demo-
graphic Factors.
This paper aims to investigate the relationships between the university students’ demographic factors and their
metacognition in digital library interaction. To achieve the objectives of this study, the demographic factors
were divided into six variables (i.e., gender, age, qualification, academic backgrounds, searching skills, and
experience with the digital library) and the metacognition was classified into nine variables (i.e., schema-
training, planning, monitoring, evaluation, transfer, memory, comprehension, task, technology). A total of
112 students participated in the online questionnaire. The collected data were analyzed using SPSS version
26, and a significant correlation between demographic elements and metacognition was found in digital library
interactions. Interestingly, the experience with digital libraries has shown the strongest factor to be considered
as the most important variable in the design of digital library interactions.
Over the years, the storage and preservation of phys-
ical materials and notable books have been the hall-
mark of a conventional library. Users would have to
go to the library to learn and search for detailed infor-
mation. This trend gradually changed with the intro-
duction of computers in the processing and searching
of information some decades ago. The rapid devel-
opment of Information Communication and Technol-
ogy (ICT) has brought about unprecedented changes.
Present developments in ICT have brought positive
change to how we store, generate, access, and use in-
formation (Chowdhury and Chowdhury, 2003). Due
to the role of ICT, libraries are undergoing fundamen-
tal changes from the traditional library to the dig-
ital library. Digital library searches become faster
than traditional libraries and provide easy access, fast-
tracking, and many electronic resources, although one
can’t neglect the feel of holding books which means
we can’t denigrate the importance of traditional li-
braries. (Case, 2002) describes information searching
as a deliberate endeavor to obtain information to elim-
inate a deficiency of knowledge or meet a knowledge
demand. However, due to the significant changes
in the libraries, studies show that during informa-
tion searching in the digital library, users experience
less optimal search results or suffer cognitive over-
head. This is due to a lack of information tailored to
the users’ interests, preferences, needs, and context.
For instance, users in traditional libraries can learn
how to find information from librarians if assistance
is needed.
However, that may not be the case in the modern
digital library, where information professionals’ help
is not always available, and users are left alone to ac-
cess, search, and use information. Generally, when
students looking for information, they prefer to in-
formation, students prefer to look at online sources
rather than practice in a methodical and organized
manner, making learning information sources in the
digital library difficult. In this regard, one could argue
that self-knowledge may drive successful information
searching in the digital library environment with the
help of ”metacognition. The term metacognition is
most commonly connected with (Flavell, 1976), who
is credited as being the first scholar to use the no-
tion of metacognition, a term he coined from the word
”metamemory” and first used in his early 1970s publi-
cations. According to (Flavell, 1979), metacognition
is the act of a thinker reflecting on their mental pro-
cess. It involves people comprehending both them-
Kim, H., Ademola, A. and Kim, Y.
Relationship between Demographic Factors and Metacognition in Digital Library Interaction.
DOI: 10.5220/0011371000003323
In Proceedings of the 6th International Conference on Computer-Human Interaction Research and Applications (CHIRA 2022), pages 89-96
ISBN: 978-989-758-609-5; ISSN: 2184-3244
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
selves and the nature of the activity and understanding
the specification of the task.
Metacognition is defined by (Swanson, 1990)
as an individual awareness of their ability to mon-
itor, regulate and manage their learning activities.
Metacognition refers to higher-level planning for han-
dling a learning activity and mechanisms for observ-
ing and evaluating comprehension. At times, indi-
viduals utilize the expression ”going meta” when dis-
cussing metacognition, alluding to the interaction of
reviewing a sort of flashback to see what you are
doing, as though you were another person noticing
it. Sternberg refers to these executive processes as
meta-components in his triarchic theory of intelli-
gence (Sternberg, 1984). According to (Sternberg,
1986) meta-components are in charge of ”determin-
ing how to perform a certain task or set of activities,
and then ensuring that the job or set of tasks is com-
pleted correctly and the ability to organize cognitive
resources effectively, such as selecting how and when
a task should be completed is centered to intelligence.
Metacognition is a fundamental human trait (Muhali,
2018) that is defined as thinking about thinking by go-
ing through a process of review (McCormick, 2003).
Having metacognition awareness assists individ-
uals in taking a more active role in planning, ana-
lyzing, evaluating, and monitoring their learning pro-
cesses (Akyol and Garrison, 2011). Individuals’
metacognition awareness is assumed to play an es-
sential part in the online information searching pro-
cess by structuring the searching process, monitor-
ing, and assessing much as it is in the learning pro-
cess. Resources on the relationship between metacog-
nition and the search process and its applications are
needed (Bowler, 2009). So much research has been
done in the academic field, but much research has not
been done in the digital library interaction regarding
metacognitive skills.
This research examines the relationship between
demographic factors and metacognition in digital li-
brary interaction. The study conducted for this pur-
pose attempts to find answers to the following ques-
tions below:
(a) Is there a significant relationship between demo-
graphic factors and metacognition when interact-
ing with digital libraries?
(b) What metacognitive skills do students have when
interacting with digital libraries?
Through the reviewing the previous research, we un-
derstood how various techniques of analysis have spe-
cific strengths and weaknesses. (Gorrell et al., 2009)
conducted a research on metacognitively aware IR
systems. They classified metacognitive components
into five categories: schema-training, planning, mon-
itoring, evaluation, and transfer. They used metacog-
nition information Likert-based knowledge generator,
so called MILK, to offer the coverage of the sub-
areas in the taxonomy. They found that metacognitive
uses vary greatly depending on gender, age, and aca-
demic discipline and that older adults, in particular,
use metacognitive skills more than younger adults.
(Madden et al., 2012) revealed whether the appli-
cation of user evaluation standards provides Metacog-
nitive evidence for web reliability, a total of 48 grad-
uate students from various disciplines participated in
the study. It was observed that some students encoun-
tered some difficulties because of an overly simplis-
tic approach to assessing sites. The students were
given different evaluation criteria such as websites
(name, description, appearance, references) and con-
tents such as authorship, quality of writing, evidence
of research, and contacts. According to the find-
ings, some participants reported dissatisfaction with
the lack of information about the author’s identity. It
was also noted that the students in the study appeared
to have received little formal assistance on the eval-
uation, which provides the most direct indication of
metacognition behavior, according to (Bonds et al.,
1992), will not only hold information in ways that
vary depending on the task. In this study, some vol-
unteers engaged in such conduct.
(Cadamuro et al., 2019) investigated the rela-
tionship between metacognition and information and
communication technology (ICT) in undergraduate
students. Metacognitive reflection during an on-
line course was found to build advanced epistemic
agency in students and increase decision-making
skills through metacognitive tips in the e-learning en-
vironment. Another observation during the research
is that metacognition self-regulation and organiza-
tion predicted students’ performance and information
searching behavior. The ICT and Metacognition are
likely in a bi-directional relationship. On the other
hand, working in technology-mediated contexts sup-
ports the development of metacognitive skills, leading
to better learning outcomes. However, metacognitive
skills are necessary to take advantage of web-based
training. The use of metacognitive skills In ICT has
contributed to creating powerful learning and infor-
mation search.
Another previous research is the think-aloud pro-
cedure focusing on comparing the use of these strate-
gies by people with different levels of critical think-
ing in searching behavior; participants were asked to
CHIRA 2022 - 6th International Conference on Computer-Human Interaction Research and Applications
think aloud everything they thought of when complet-
ing the task that attracted favorable attention. (Erics-
son and Simon, 1984) argue that it reflects the think-
ing process more directly than other oral reports that
require participants to express their ideas in words
during the task. It is also considered to be a straight-
forward method to gain insight into human knowl-
edge and techniques of problem-solving, similarly
to (Crain-Thoreson et al., 1997). The study exam-
ines think-aloud procedures to check the reading com-
prehension process and found that only the conver-
sion response represents after modifying the coding
scheme. The variance in comprehension score ac-
counted for by the usage of comprehension strategy
increased from 20% to 40% after adjusting the cod-
ing system to include only transformed responses that
demonstrated active and correct integration of pas-
sage content.
glu et al., 2020) analyzed 20 university stu-
dents on online information searching and metacog-
nitive abilities during argumentation activities, focus-
ing on three phenomena: argumentation activities,
metacognitive skills, and the link between them. By
examining screen recordings and the online informa-
tion searching strategy inventory (OISSI) created by
(Tsai, 2009), different results were obtained in terms
of metacognition awareness and online information
searching methods. The findings of the interviews
demonstrated a link between participants’ online in-
formation searching tactics used in argumentation ac-
tivities and all dimensions of metacognition. Further-
more, the data shows that metacognition skills are fre-
quently linked to multiple sub-dimensions in (Tsai,
2009) framework and might readily encompass a va-
riety of techniques. Again, online argumentation ac-
tivities can be argued to allow for extensive use of
metacognitive abilities in planning, monitoring the in-
formation gathering process, and applying appropri-
ate strategies. According to (van Geel et al., 2015)
metacognition is essential in solving complicated in-
formation problems.
However, given that information search is a
problem-solving process, metacognition has always
been a missing piece in the puzzle to understanding
users better. The current study used a metacognitive
paradigm from educational psychology to illuminate
the research problem. However, further research is
needed to categorize users’ difficulties during infor-
mation searching through digital libraries and develop
adequate taxonomy, which are five core metacogni-
tion skills to address these challenges.
This section will present the study design, instrument,
participants, and data analysis information.
3.1 Research Design
The quantitative research approach was employed to
identify the demographic differences in metacogni-
tion in digital library interaction. This strategy was
used to gather data on the subject and contribute to a
more comprehensive understanding.
3.2 Participants
The study was conducted to gather adequate infor-
mation from Kyungpook National University students
(Koreans and international students) and Nigerian
university students. This research tends to employ a
simple random sampling technique in selecting one
hundred and twelve (112) respondents for this re-
search. This includes 20 Knu-Korea students,35 Knu-
International students, and 57 Nigeria university stu-
dents. The bulk of the 112 participants was male
(57%) and female (43%) respectively. The partici-
pant’s ages range from 18 to 43 years above. Partici-
pants have different qualifications ranging from bach-
elor’s degrees, master’s degrees, doctorate degrees
(Ph.D.), and post-doc.
3.3 Metacognition Components
The existing concept of ve metacognitive skills used
in the study Schema-training, planning, monitoring,
evaluation, and transfer were developed by (Brown,
1975). Schema-training: This involves the devel-
opment of cognitive structures that provides a con-
ceptual framework for comprehension (Gordon and
Braijn, 1985). Planning: This refers to carefully
evaluating the current situation in order to determine
potential causes of action to implement solutions to
achieve results and make efficient use of the time
and resources (Erenler and Cetin, 2019). Monitor-
ing: This is about the person’s awareness of how
she performed in relation to the process that was
planned. (Schraw, 1998) Evaluation: This refers to
how the person evaluates both the organization pro-
cess and the outcomes of her own learning (Schraw
and Moshman, 1995) Transfer: It refers to the pro-
cess of moving one’s skills and knowledge from one
problem-solving scenario to another. The low and
high-road theory on learning transfer, developed by
(Perkins et al., 1992) However, (Wallace and Kup-
perman, 1997), who also explores web searching,
Relationship between Demographic Factors and Metacognition in Digital Library Interaction
Table 1: Metacognition components.
Memory Comprehension Task Technology
Schema-training [S-M] [S-C] [S-Ta] [S-Te]
Planning [P-M] [P-C] [P-Ta] [P-Te]
Monitoring [M-M] [M-C] [M-Ta] [M-Te]
Evaluation [E-M] [E-C] [E-Ta] [E-Te]
Transfer [T-M] [T-C] [T-Ta] [T-Te]
recommends breaking down the rest of the required
skills into two parts task and technology. In addition,
metamemory and meta-comprehension are subareas
of Metacognition (Brown, 1975). All these make it
four elements applied to five components of the task.
As shown in Table 1, there are twenty subareas.
Based on the subareas of Table 1, a 32-item ques-
tionnaire was developed by the researcher using the
Google forms feature. The questionnaire aims to
cover all the domains outlined in the taxonomy and
explore participants’ perceptions of their usage of se-
lected metacognitive skills while searching on the
web and digital libraries. The measurement used is
a 5-point Likert type scale range and was set out and
scored in the following way 5= Strongly agreed, 4=
Agree, 3=Neutral, 2= Disagree, 1= Strongly disagree.
3.4 Data Analysis
The data collected was coded organized and pro-
cessed by the researcher using the statistical package
for the social sciences (SPSS version 26). Descrip-
tive statistics of frequency count were used to pro-
vide information on the number of males and females
that participated in the research. It was also used to
analyze the age, qualification, academic background,
searching skills, and experience with a digital library.
The mean and standard deviation were used to an-
alyze the research question to determine the metacog-
nitive skills possessed when searching through the
digital library. Bivariate correlation was used to an-
alyze the relationships between demographics and
metacognition awareness.
The results of descriptive statistical analyses were
used to determine the university student’s metacog-
nitive competence scores. The overall mean score is
( ¯x = 3.62) and the criterion mean is 3.0 on a ve-
point scale of metacognitive skills which was divided
into five dimensions namely: schema-training, plan-
ning, monitoring, evaluation, and transfer. The group
means for each metacognitive skills dimension was
also calculated. The result revealed that schema train-
ing ( ¯x = 3.48), planning ( ¯x = 3.64), monitoring ( ¯x =
3.63), evaluation ( ¯x = 3.54) and transfer ( ¯x = 3.81).
Full results are listed in Table 3.
Bivariate correlation analyses were conducted to
discover relationships between demographic informa-
tion (gender, age, qualification, discipline, searching
skills, and experience with digital library) and scores
for the various metacognitive components. A further
correlation analysis sought relationships between de-
mographic information and metacognition. The find-
ing revealed the Pearson correlation analysis which
shows that there is negative significant relationship
between gender and task (r = 0.265, p > 0.05) as
well as on schema (r = 0.235, p > 0.05) and plan-
ning (r = 0.256, p > 0.05). It also showed that there
is negative significant relationship between age and
comprehensive (r = 0.190, p > 0.05) as well as on
schema (r = 0.198, p > 0.05). Furthermore, there
is negative significant relationship between academic
background and comprehensive (r = 0.224, p >
0.05) as well as on planning (r = 0.270, p > 0.05).
Finally, there is negative significant relationship be-
tween experience with digital library and memory
(r = 0.249, p > 0.05) as well as on comprehen-
sion (r = 0.199, p > 0.05), task (r = 0.279, p >
0.05), technology (r = 0.234, p > 0.05), schema
(r = 0.395, p > 0.05) and planning (r = 0.242,
p > 0.05).
Table 2 shows that there is a negative significant re-
lationship between task, schema, and planning based
on gender. This implies that males have a strong neg-
ative significance in the metacognitive skills in the
main component of schema training p = 0.013 and
planning p = 0.006 and subareas task p = 0.005 than
females to a greater extent. Furthermore, age has a
negative significance with older people having bet-
ter metacognition skills in schema training p = 0.037
and comprehension p = 0.045. This implies that older
CHIRA 2022 - 6th International Conference on Computer-Human Interaction Research and Applications
Table 2: Pearson correlation coefficient (Pearson’s r) and p-value between Demographics and Metacognition awareness.
Pearson’s r (p-value)
Gender Age Qualification Academic
Experience with
digital library
-0.021 -0.137 0.143 -0.395
( < 0.013) (< 0.037) (< 0.825) (< 0.149) (< 0.133) (< 0.000)
-0.112 -0.055 -0.270
0.063 -0.242
( < 0.006) (< 0.239) (< 0.563) (< 0.004) (< 0.509) (< 0.010)
-0.032 -0.064 -0.012 -0.172 -0.031 -0.077
( < 0.739) (< 0.501) (< 0.904) (< 0.070) (< 0.744) (< 0.419)
-0.089 -0.076 -0.134 0.169 0.017 -0.139
( < 0.353) (< 0.426) (< 0.159) (< 0.075) (< 0.861) (< 0.143)
-0.126 0.076 -0.062 0.044 0.095 -0.149
( < 0.186) (< 0.424) (< 0.515) (< 0.646) (< 0.320) (< 0.116)
-0.146 -0.074 -0.070 0.064 0.119 -0.249
( < 0.125) (< 0.437) (< 0.463) (< 0.506) (< 0.210) (< 0.008)
-0.111 -0.190
-0.080 -0.224
-0.009 -0.199
( < 0.243) (< 0.045) (< 0.404) (< 0.018) (< 0.923) (< 0.036)
-0.100 -0.040 -0.123 0.110 -0.279
( < 0.005) (< 0.296) (< 0.678) (< 0.198) (< 0.248) (< 0.003)
-0.150 0.004 0.003 -0.033 -0.024 -0.234
( < 0.114) (< 0.967) (< 0.975) (< 0.726) (< 0.798) (< 0.013)
Correlation is significant at the 0.05 level (2-tailed).
Correlation is significant at the 0.01 level (2-tailed).
people have metacognitive accuracy for their capacity
and older adults can accurately assess their ability to
selectively remember high-value information. There
is a negative significant relationship between the main
component of planning p = 0.004 and sub-areas com-
prehension p = 0.010 based on the academic back-
ground which indicates that information technology
students possessed high metacognition skills which
comprise the highest percentage of students that par-
ticipated in the research. Experience with the digital
library is very much influenced and an important fac-
tor in both schema training, p = 0.000 planning, p
= 0.010 memory, p = 0.008 comprehension p = 0.036
task, p = 0.033 technology p = 0.013. Therefore, gen-
der, age, academic background, and experience with
the digital are compelling factors that determine the
level of the metacognitive skills of the students.
Table 3 shows that University students reported
higher use of metacognition in general, with the high-
est score of ( ¯x = 3.81) in transfer and in most of the
subareas of metacognition skills. Under schema train-
ing majority of the students possessed high metacog-
nitive skills in schema training-memory. This shows
that a higher percentage of university students have a
number of techniques at their disposal to help them
remember what they learned and where they found it.
It was observed that 52% of respondents lack tech-
niques that can help them understand the information
they find while using a digital library.
Under planning, it could be concluded that plan-
ning comprehension is significantly high, this shows
that the majority of the students possessed skills in
planning to summarize in order to monitor and im-
prove their comprehension. While they lack plan
search task strategies such as verifying how trustwor-
thy the information from digital libraries is from dif-
ferent academic journals. Importantly, a lack of plan-
ning doesn’t necessarily mean an ineffective search.
In other words, the high potential in planning which
in some cases inhibits efficient retrieval.
A higher percentage of students under monitoring
show strong metacognition skills in the monitoring
search task which indicates when using the digital li-
brary for a learning task, they ask themselves ques-
Relationship between Demographic Factors and Metacognition in Digital Library Interaction
Table 3: Types of metacognitive skill.
S/n Types of metacognitive skills ¯x σ
[S-M] I have techniques that help me remember any information I come across on digital
3.84 0.94
[S-C] I have techniques that help me understand the information I find while using digital
3.21 1.19
[S-Ta] I have developed ways of identifying the type of information I need for my learning
tasks while using digital library.
3.33 1.24
[S-Te] I am good at choosing keywords on user interface of digital library to get optimized
3.52 1.18
Average mean 3.48 1.14
[P-M] I plan ways to remember the information I find in the digital library. 3.88 0.84
[P-C] I may use the digital library to start a search task to increase my understanding on
a subject area.
3.87 1.02
[P-Ta] I decide in advance exactly what type of information I am looking for on digital
3.17 1.33
[P-Te] I tend to work out my search skills before using a digital library. 3.65 1.02
Average mean 3.64 1.05
[M-M] Sometimes when using the digital library, I am aware that I might for get the
information I find.
3.68 1.01
[M-C] Sometimes when using the digital library, I may have misunderstood information
I read earlier in my search.
3.04 1.14
[M-Ta] When using the digital library for a learning task, I find myself asking questions
along the lines of: “Is this search providing the type of in formation I need?”.
3.94 0.80
[M-Te] At times I am cautions as I search (e.g. the words I put into the search box) in the
digital library.
3.85 0.91
Average mean 3.63 0.97
[E-M] It is clear to me when I am failing to remember what I learned in the digital library. 3.49 0.93
[E-C] While using the digital libraries I get convinced that the feedback of my search is
3.18 1.15
[E-Ta] I spend a lot of time judging how well the information I find in digital libraries
matches my learning needs.
3.70 1.02
[E-Te] It is usually obvious to me whether I am using a good search strategy on a digital
library or not.
3.80 0.92
Average mean 3.54 1.01
[T-M] I use different approaches to recall the information that I learned in other domains
of digital library.
3.77 0.96
[T-C] My experience with different learning tasks has helped me monitor how well I am
understanding what I read in the digital library.
3.79 0.83
[T-Ta] My experience in other areas helps me to work out exactly what type of informa-
tion I need for my learning task in the digital library.
3.99 0.93
[T-Te] The skills I apply when using a digital library are useful in other areas of my
information searching.
3.70 0.94
Average mean 3.81 0.92
Overall mean = 3.62
CHIRA 2022 - 6th International Conference on Computer-Human Interaction Research and Applications
tions along the line if the search provides the type
of information they need. It shows that 74% of the
participants are aware of their progress towards com-
pleting the task and the reliability of the information
they found. But possessed weak metacognition skills
in monitoring comprehension which shows that when
using a digital library they must have misunderstood
information they read in the past when searching.
Under evaluation, it could be concluded that users
possessed strong metacognition skills in evaluation
technology which implies that it is usually obvious to
the majority of university students whether they are
using a good searching strategy in a digital library or
not. It shows that participants critically evaluate their
search method and use of technology and draw con-
clusions about the use. However, they lack evaluation
comprehension skills while using digital libraries they
get convinced if the feedback of their search is valid.
Under transfer, it shows that users possessed a
higher level of metacognition skills in the transfer
search task with 74% of participants who have ex-
perience from other areas helping them to work out
precisely what type of information they need for their
learning task. On the contrary, there is low metacog-
nition awareness in transfer technology which indi-
cates that the use of carrying learning from other tasks
into their use of sources and technology is low.
This study’s findings imply that, regarding the issue
with digital libraries, metacognition awareness is es-
sential where it is lacking. Based on the conclusions
of this paper, metacognitive skills were observed from
different components and subareas of the taxonomy.
The result shows that students demonstrated strong
metacognition skills on transfer which is a result
of metacognitive knowledge that helps them to se-
lect previously learned strategies to achieve searching
goals or to deal with problems encountered during the
task. According to (Groteluschen et al., 1990), if the
chosen strategy is effective and searchers believe it
improves learning quality and their specific strategy
is stronger. The nature of this study cannot be con-
sidered indicative of the entire student body. Given
the fact that there are 122 participants in the study, it
seems reasonable that it doesn’t cover larger numbers
of students with different academic backgrounds. It
is possible to argue that teaching students how to ap-
ply metacognitive methods improves their academic
performance (1988). Students with advanced skills in
metacognition may keep track of their own learning,
express their opinions on it, keep up to speed on their
knowledge, and develop and implement new learn-
ing procedures. Students that effectively use their
metacognitive skills are more aware of their strengths
and weakness and seek to develop their skills further
than other students (Bransford et al., 2000). The re-
sults show improvement in planning which shows that
majority of the students demonstrate the use of imple-
menting metacognitive strategies that require careful
planning and a better understanding of metacognitive
skills should provide students with potential strategies
to use when searching for information in digital li-
According to (Jones et al., 1995) the greater a
student’s understanding of metacognition, the greater
his or her efficiency. In the twenty-first century,
metacognition strategies are needed. This will al-
low students to successfully cope with new situa-
tions when searching, and school library media spe-
cialists to capitalize on their skills and gain ac-
cess to a wealth of resources, fostering the develop-
ment of good thinkers who are successfully problem-
solvers, searching skills, and information retrieval ex-
perts. Additionally, students with good metacognitive
skills are better critical thinkers, problem solvers, or
decision-makers than students without metacognitive
skills, and also metacognitive training can increase
students’ self-confidence and personal responsibility
for their own development.
The implication is that metacognition skills help
individuals process and retain information through
self-recognition and reflection. Metacognition skills
are essential because they help students understand
their learning process and how they learn effectively,
and it also assists users in learning to control their
searching by defining search goals and tracking their
progress towards them. The taxonomy used in this re-
search to identify the metacognition awareness from
different nationalities can be used for future research
on information searching through a web search. Its
feature can be used not just for digital libraries.
This Research was supported by Kyungpook National
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