Motivational Factors that Influence the use of MOOCs:
Learners’ Perspectives
A Systematic Literature Review
Nada Hakami, Su White and Sepi Chakaveh
Electronics and Computer Science, University of Southampton, University Road, Southampton, U.K.
Keywords: Learner’s Motivations, MOOC Acceptance, MOOC Adoption, MOOC Retention, MOOC Completion,
Learner’s Engagement, Literature Synthesis, MOOCs.
Abstract: Massive Open Online Courses (MOOCs) have become an important environment for technology-enhanced
learning (TEL) where massive numbers of users from around the world access free, online-based, open
content generated by the world-class institutions. Understanding learner’s motivations for using MOOCs is
essential for providing successful MOOC environments. This paper presents a comprehensive picture of the
literature published between 2011-2016 and pertaining to the motivations that drive individuals to use
MOOCs as learners. We examined the classifications of papers, theories used, data collection methods,
motivational factors proposed and geographic distribution of participants. Findings demonstrate that the
related literature is limited. Several papers adopted technology acceptance theories. Quantitative survey was
the favoured method
for researchers. Key motivational factors were learner-related (which are divided into
personal, social and educational / professional development), institution and instructor-related, platform and
course-related and perception of external control/facilitating conditions-related. The identified studies
focused only on few geographic regions. Such findings are important for uncovering the directions in the
literature and determining the current gaps that can be addressed in the future.
1 INTRODUCTION
Massive Open Online Courses (MOOCs) offer
people worldwide the chance to improve their
education free of charge with no commitment or
prior requirements. MOOCs are gaining wide-spread
attention and are rapidly changing the attitude
towards TEL. Since 2008, the number of higher
education institutions that provide MOOCs has
increased rapidly. It is reported that in 2015 there
were around 4,200 courses offered by 500
institutions while the total number of learners who
registered in MOOCs reached 35 million (Shah,
2015).
Barak et al. (2016, p.50) defined motivation as “a
reason or a goal a person has for behaving in a given
manner in a given situation”. In MOOCs, there is a
diversity in motivations among learners to use
MOOCs as a result of the open nature of MOOCs,
which allows anyone to participate (Kizilcec et al.,
2013; Bayeck, 2016). Investigating such motivations
offers insights for MOOCs providers into the
possible solutions for improving their services in
order to increase learners’ engagement, satisfaction,
completion rate, as well as meet their needs and
requirements.
There is a lack of systematic synthesis of
literature pertaining to factors motivating learners to
use MOOCs. The purpose of this paper is to present
a comprehensive and systematic review of the
literature related to this topic so as to highlight the
current research directions and gaps that can be
addressed in the future. To address the gaps in the
literature, we pose the following research questions
(RQ):
RQ1: What are related papers? How can the papers
be classified?
RQ2: What theoretical frameworks and reference
theories have been applied to study the topic?
RQ3: What data collection methods have been used
by related papers?
RQ4: What key motivational factors were proposed
in existing studies?
RQ5: What is the participants’ geographic
distribution in the related studies?
Hakami, N., White, S. and Chakaveh, S.
Motivational Factors that Influence the use of MOOCs: Learners’ Perspectives - A Systematic Literature Review.
DOI: 10.5220/0006259503230331
In Proceedings of the 9th International Conference on Computer Supported Education (CSEDU 2017) - Volume 2, pages 323-331
ISBN: 978-989-758-240-0
Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
323

The reminder of this paper is structured as
follows: Section two highlights the related work.
Section three outlines the research method. Section
four describes the findings while section five
illustrates the discussion. Finally, conclusion is
presented in section six.
2 RELATED WORK
This section summarizes prior literature synthesis
that were focused on identifying the motivational
factors affecting learner’s intention to use MOOCs.
Only two literature synthesis pertaining to the
topic were found. Hew and Cheung (2014) aimed to
identify the learners’ and instructors’ motivations
and challenges of using MOOCs. They also
suggested future issues that need to be resolved. This
work is similar to our study. However, their study
was published in 2014 and many related studies
have emerged after this year. The goal of a study led
by Latha and Malarmathi (2016) is examining the
factors influencing the learners to complete MOOCs.
This study differs from ours in terms of that its focus
is only on MOOCs completion and not motivations
for using MOOCs.
We examined the literature based on different
research questions that are not addressed before. To
the best of our knowledge, this paper represents the
first effort to review the literature on motivations for
using MOOCs from learners’ viewpoints for a
particular time period (2011 to 2016) to make better
sense of various research trends and provide
proposal for further research.
3 METHODS
To accomplish our objective, we used the systematic
literature review strategy suggested by Kitchenham
(2004). The approach consists of five activities
which are: (A) Define research question, (B) Define
search keywords, (C) Select electronic resources,
(D) Search process, (E) Match inclusion and
exclusion criteria.
The search keywords used were “MOOCs
Learner Motivations”, “MOOCs Completion OR
MOOCs Retention”, and “MOOCs Learner
Engagement”. The papers were identified through
searching six educational technology journals and
six academic databases namely, British Journal of
Educational Technology, American Journal of
Distance Education, Distance Education, Open
Learning: The Journal of Open, Distance and e-
Learning, European Journal of Open, Distance and
E-Learning, Computer Assisted Learning, Google
Scholar, IEEE Xplore, Elsevier’s ScienceDirect,
Wiley Online Library, SpringerLink and Scopus.
Tables 1,2 and 3 illustrate the ratio of search results
to relevant papers using the identified search
keywords. A number of search results from
journal/database are similar to other journal/database
results.
In order to be included in the corpus, each
identified paper ought to focus on the motivations
for using MOOCs from learner’s perspective. This
criterion was given the highest priority. However,
due to the limited number of related papers, further
criteria, with lower priority than the previous
criterion, were specified to choose appropriate
papers for inclusion in the review which are as
follows: the paper ought to focus either on (A) the
factors that influence the acceptance of MOOCs
(why people accept or reject the use of MOOCs) , or
(B) the learner’s motivations for MOOCs
completion / retention, or (C) the factors influencing
the success of MOOCs, or (D) addressing the
learners’ motivations for using MOOCs as a part of
other different objectives. We expect that these
additional papers might present factors that are
applicable to the motivations of using MOOCs.
Moreover, papers ought to be published between
January 2011 and October 2016 and written in
English. The reason of selecting year 2011 is that it
was the date when MOOCs have been used
extensively in online learning (Sunar et al., 2015).
Table 1: The results of the search by the keyword
“MOOCs Learner Motivations”.
Journal /Data Base *SR:RP
British Journal of Educational
Technology
39:2
American Journal of Distance
Education
7:0
Distance Education 28:0
Open Learning: The Journal of Open,
Distance and e-Learning
23:0
European Journal of Open, Distance
and E-Learning
0:0
Computer Assisted Learning 9:0
Google Scholar 6,880:27
IEEE Xplore 247:0
Elsevier’s ScienceDirect 178:4
Wiley Online Library 125:3
SpringerLink 434:4
Scopus 259:14
*SR:RP Ratio of search results to relevant papers
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Table 2: The results of the search by the keyword
“MOOCs Completion OR MOOCs Retention”.
Journal /Data Base *SR:RP
British Journal of Educational
Technology
18:1
American Journal of Distance
Education
4:0
Distance Education 15:0
Open Learning: The Journal of Open,
Distance and e-Learning
16:0
European Journal of Open, Distance
and E-Learning
0:0
Computer Assisted Learning 7:0
Google Scholar 4,240:21
IEEE Xplore 304:0
Elsevier’s ScienceDirect 242:5
Wiley Online Library 183:2
SpringerLink 197:1
Scopus 35:5
*SR:RP Ratio of search results to relevant papers
Table 3: The results of the search by the keyword
“MOOCs Learner Engagement”.
Journal /Data Base *SR:RP
British Journal of Educational
Technology
29:1
American Journal of Distance
Education
9:0
Distance Education 37:0
Open Learning: The Journal of Open,
Distance and e-Learning
32:0
European Journal of Open, Distance
and E-Learning
0:0
Computer Assisted Learning 8:0
Google Scholar 9,800: 23
IEEE Xplore 199:0
Elsevier’s ScienceDirect 168:7
Wiley Online Library 143:3
SpringerLink 489:3
Scopus 32:1
*SR:RP Ratio of search results to relevant papers
In the data analysis phase, we used the constant-
comparative method suggested by Glaser (1965) to
classify the identified papers.
4 FINDINGS
This section presents the findings from the analysis
of the related studies as well as provides the answers
to our research questions.
4.1 What Are Related Papers? How
Can the Papers Be Classified?
The results of our analysis revealed that a total of
forty-two papers were related to the topic. It can be
observed that certain papers intended to develop a
model based on identifying explanatory variables
that are used to predict the use of MOOCs. In
contrast, other papers applied empirical methods
such as quantitative and qualitative data collection
methods in order to explore the learners’ motivations
behind enrolling on MOOCs without modelling the
motivational factors. Consequently, we clustered the
relevant papers into two main categories:
1. Modelling the motivational factors that
influence the use of MOOCs
2. Not modelling the motivational factors that
influence the use of MOOCs
The classification of the identified papers is shown
in Table 4. In this Table, all eleven identified papers
in the first category focused on modelling the factors
influencing learners’ intention to use MOOCs while
all seventeen identified papers of the second
category sought primarily to identify learners’
motivations for taking MOOCs.
Table 4: Classification of the identified papers.
Category Author(s) (year)
1
Xiong et al. (2014); Xu (2015); Chu et al.
(2015); Huanhuan and Xu (2015); Gao
and Yang (2015); Chaiyajit and
Jeerungsuwan (2015); Nordin et al.
(2015); Aharony and Bar-Ilan (2016);
Zhou (2016); Sa et al. (2016); Alraimi et
al. (2015)
2
Belanger and Thornton (2013);
Christensen et al (2013); Norman (2014);
Hew and Cheung (2014); Davis et al.
(2014); Gütl et al. (2014); Kizilcec and
Schneider (2015); Zheng et al. (2015); Liu
et al. (2015); Cupitt and Golshan (2015);
Li (2015); Salmon et al. (2016); Bayeck
(2016); Howarth et al. (2016); Uchidiuno
et al. (2016); Zhong et al. (2016); Garrido
et al. (2016)
We assigned additional three papers to the first
category. However, they established different
objectives from those of the previous papers in the
first category. Hone and El-Said (2016), Xiong et al.
(2015) and Adamopoulos (2013) aimed to develop a
model of the factors contributing to the MOOCs
completion and retention. The factors identified in
these papers can be tested in the context of the
intention to use MOOCs.
Motivational Factors that Influence the use of MOOCs: Learners’ Perspectives - A Systematic Literature Review
325

Further eleven papers, which have been assigned
to the second category, indirectly addressed the
motivations of learners for using MOOCs or
investigated the factors influencing learners’
retention or the success of MOOCs. Such papers are
as follows: Shrader et al. (2016), Chang et al.
(2015), Littlejohn et al. (2016), Rai and Chunrao
(2016), Gamage et al. (2015), Wang and Baker
(2015), Latha and Malarmathi (2016), Bakki et al.
(2015), Khalil and Ebner (2014), Greene et al.
(2015) and Barak et al. (2016).
4.2 What Theoretical Frameworks and
Reference Theories Have Been
Applied to Study the Topic?
Technology acceptance theories are the dominant in
the related publications in the first category. The
goal of these theories is to “specify a pathway of
technology acceptance from external variables to
beliefs, intentions, adoption and actual usage” (Van
Biljon and Kotzé, 2007, p.152). According to Louho
et al. (2006, p.15), “technology acceptance is mostly
about how people accept and adopt some technology
to use”. It was found that most of the studies
included into the first category group (11 papers)
used technology acceptance theories.
Technology Acceptance Model (TAM) has
emerged as the most popular theory with 6
publications employing it. Other used theories
included the Unified Theory of Acceptance and Use
of Technology (UTAUT) (2 papers), TAM3(1
paper), Theory of Planned Behaviour (TPB) plus
Self-Determination Theory (SDT) which is one of
the leading motivation theories (1 paper) and
Information Systems Continuance Expectation
Confirmation (1 paper).
4.3 What Data Collection Methods
Have Been Used by Related
Papers?
Orlikowski and Baroudi (1991) classified research
into conceptual and empirical. Conceptual research
refers to studies that are based on formulating
concepts and models without using empirically
collected data. Literature review is an example of
this type of research. On the other hand, empirical
research refers to studies that are based on data
collection methods to generate and test hypotheses,
such as surveys, interviews, multi-method research,
case studies and experiments.
All previous studies falling under the first
category are empirical research. Survey quantitative
method has been used by all the related research
except for one research which is based on
observation, interview and analysing students’
textual reviews.
Researches falling under the second category are
classified into conceptual and empirical research.
Four publications are conceptual research using
literature review. With regards to empirical
quantitative studies, there is a large volume of
published studies using the survey method (13
papers) with one publication that applied survey and
activity data analysis methods. Empirical qualitative
studies utilized the interview (1 paper), literature
review and observation (1 paper), and observation
and interview (1 paper). Studies based on mixed-
methods approach used survey and interview (3
papers); survey, clickstream and event data analysis
(1 paper); survey and forum posts and email
messages analysis (1 paper). The data collection
method used in the study by Rai and Chunrao (2016)
was based on general opinions that were derived
from the perspectives of MOOCs learners but was
not clearly identified in the paper. Overall, it turned
out that the quantitative approach based on a survey
method was the most frequently applied research
strategy in both categories, with 26 papers (61.90%).
4.4 What Key Motivational Factors
Were Proposed in Existing Studies?
We identified forty-three motivational factors
reported in the related publications. Having
identified the proposed motivational factors that
drive individuals to the use of MOOCs, we classified
those factors into four main dimensions: learner-
related factors, institution and instructor-related
factors, platform and course-related factors, and
perception of external control/ facilitating
conditions-related factors. The factors identified
under each main dimension can be listed as follows:
1. Learner-related factors
This dimension includes the factors related to
the learners themselves. The factors are divided
as following:
1.1. Personal factors: including curiosity,
perceived enjoyment, learner’s attitude,
computer playfulness, computer anxiety,
satisfaction, extrinsic motivation, intrinsic
motivation, challenge, human capital (being
able to behave in new ways) and awareness.
1.2. Social factors: including subjective norm
(social influence), interaction with learners,
image (social status) and mimetic pressure.
1.3. Educational/Professional development
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factors: including job/academic relevance,
extend knowledge and skills, earn a
certificate, get learning opportunities not
otherwise available, prepare for future,
improve English ability and special project
requirements.
2. Institution and instructor-related factors
This dimension consists of two factors related to
the characteristics of institutions and instructors
namely, perceived reputation and interaction
with instructor.
3. Platform and course-related factors
This dimension includes the factors that
describe the characteristics of the platforms and
courses. Such factors include: perceived
usefulness, perceived ease of use, perceived
openness (open access to MOOCs without
restrictions), course’s content quality, course
characteristics (such as the course’s discipline
and the duration of a course), ubiquity
(flexibility or convenience), perceived
utilitarian value (tradeoff between received and
given things), objective usability, output quality,
trust, perceived effectiveness, MOOC
popularity, information richness (the amount of
details used to convey the information),
personalization and gamification.
4. Perception of external control/Facilitating
conditions
The perception of external control/facilitating
conditions is defined as “the degree to which an
individual believes that organizational and
technical resources exist to support the use of
the system” (Venkatesh and Bala, 2008, p.279).
This dimension encompasses learner’s skills
and technology-related factors.
4.1. Learner’s skill-related factors: including
computer self-efficacy, experience in
MOOCs and self-determination (self-
regulated learning).
4.2. Technology-related factors: including
technology compatibility.
One obvious finding to emerge from the analysis
is that the most frequently proposed factors in the
studies in the first category were: perceived
usefulness (10 papers), perceived ease of use (10
papers), and perception of external control/
facilitating conditions (4 papers). In the studies
assigned to the second category, the most frequently
suggested factors were: extend knowledge and skills
(25 papers), curiosity and earn a certificate (16
papers) and interaction with learners (14 papers).
4.5 What Is the Participants’
Geographic Distribution in the
Related Studies?
Participants in the related studies are the users who
have been selected during the data collection stage
for reporting their motivations for using MOOCs.
The results obtained from the analysis shows that 10
papers in the first category reported the participants’
geographic distribution. All these studies examined
the perspectives of users from specific countries
except for one study by Alraimi et al. (2015) which
employed users from different countries. As can be
seen from Figure 1, most of these studies focused on
exploring the factors driving users from China to use
MOOCs (4 papers). Other reported countries were:
Israel, USA, India, Greece, Azerbaijan, Egypt,
Thailand, Korea and Malaysia.
Figure 1: Geographic distribution of participants in the
studies in the first category.
On the other hand, 13 papers assigned to the second
category stated the geographic distribution of the
participants. Conversely, these publications did not
focus on the perspectives of users from a specific
country or culture. Each of these studies employed
participants originating from different countries. As
Figure 2 shows, the most frequently mentioned
countries were the USA (7 papers), India (7 papers),
Spain (6 papers), and then four papers for each of
the following countries: Australia, Brazil, Canada,
China, and Germany.
Motivational Factors that Influence the use of MOOCs: Learners’ Perspectives - A Systematic Literature Review
327

Figure 2: Geographic distribution of participants in the
studies in the second category.
5 DISCUSSION
Our analysis of forty-two related papers revealed
important findings. One interesting finding is that
the amount of research on MOOCs acceptance and
the factors influencing their use is limited.
Moreover, only few papers adopt the technology
acceptance theories.
Another important finding was that 61.90% of
papers used solely a survey as a method for data
collection. The finding of this study also shows that
the main factors driving learners to MOOCs
enrolment were learner-related (divided into
personal, social and educational / professional
development), institution and instructor-related,
platform and course-related and perception of
external control/facilitating conditions-related.
Unlike the studies assigned to the first category,
most of the studies from the second category did not
examine the motivations of users from specific
countries or cultures. With regards to the geographic
distribution of participants in related studies falling
under the first category, the most frequently
mentioned country was China whereas in the studies
in the second category the main focus was on the
USA, India, Spain, Australia, Brazil, Canada, China,
and Germany.
These findings help us to understand current
research directions in the motivations for using
MOOCs from learners’ perceptions, identify
research gaps and provide suggestions for further
research. Based on our findings, it can be concluded
that substantial efforts are needed to investigate the
topic from different perspectives and angles. There
are numerous motivation and technology acceptance
theories which have been tested in various contexts.
Testing the applicability of these theories within the
context of MOOCs is a rich area for future research.
Because technology acceptance model (TAM) was
built from a quantitative survey study, it is not
surprising that survey quantitative methodology is
the only method used by the papers that adopted
technology acceptance theories. Likewise, most
papers of the second category also used the survey
method. One recommended method for future
research is applying mixed-methods. The reason for
mixing both quantitative and qualitative data within
one study is that neither quantitative nor qualitative
methods are adequate to understand the problem and
the details of a situation, hence integrating both
methods can complement each other (Ivankova et
al., 2006).
Related studies addressed many motivational
factors leading to the usage of MOOCs.
Nevertheless, there is abundant room for further
progress in determining other influential factors
affecting MOOCs use. For example, further study
may be undertaken to investigate the influence of
intercultural exchange within MOOCs on the
MOOC acceptance. In addition, a further study with
more focus on understanding the influence of self-
regulated learning capabilities on the learner’s
intention to use MOOCs is also
suggested. Investigating the influence of earning
certificate of course completion on MOOC
acceptance is also useful research.
The related literature concentrated on the
perspectives of users from few geographic regions.
Christensen et al. (2013) reported that the reasons
for enrolling in MOOC courses varied by country.
Similarly, Davis et al. (2014) found that learners’
motivations to participate in MOOCs can vary
significantly across cultures. No published studies
have been conducted so far to determine the
motivations of Arabic individuals to accept MOOCs
except for two papers by Davis et al. (2014) and
Hone and El-Said (2016) which examined the
viewpoints of Syrian and Egyptian individuals
respectively. In light of these findings, in future
investigations, it might be useful to identify the
motivational factors influencing users from different
countries and cultures such as Arabic or developing
countries. In general, in order to develop a full
picture of MOOCs acceptance, additional studies
will be needed.
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6 CONCLUSIONS
Prior literature that focused on the learners’
motivations to use MOOCs have been examined.
We reported the classifications of papers, theories
used, data collection methods, motivational factors
proposed and geographic distribution of participants.
This systematic analysis enables researchers to
understand the related literature on motivations for
using MOOCs from learners’ viewpoints and its
directions and limitations.
Based on our findings, there are many
suggestions for future research. First, it would be
interesting to investigate the motivations of learners
from Arabic countries to accept MOOCs and
compare the findings with motivations of learners
from other countries. Second, it is suggested that the
correlation between learners’ motivations and course
completion is investigated in future studies. Third, a
further study could validate the technology
acceptance and motivation theories within the
context of MOOCs. Finally, further investigation
into influence of self-regulated learning capabilities
on the learners’ intention to accept MOOCs is
recommended. We expect that this research will
serve as a base for future studies.
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