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Investigating the Impact of Gamication
Components on Online Learners’ Engagement
Chen Meng
Indiana University Bloomington
Mengyuan Zhao
Purdue CyberLab, Purdue University Indianapolis
Zilong Pan
Lehigh University
Qianqian Pan
Nanyang Technological University
Curtis J. Bonk
Indiana University Bloomington
Research Article
Keywords: Gamication, Points, Badge, Online learners, Engagement
Posted Date: May 31st, 2024
DOI: https://doi.org/10.21203/rs.3.rs-4499818/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Additional Declarations: The authors declare no competing interests.
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Abstract
As online learning and teaching are becoming an educational trend, online students’ engagement will
directly impact the learning and teaching effects and outcomes. A scientic application of gamication
in online learning, teaching, and online course design will improve online learners’ learning experience
and help build a better virtual learning context for online learners worldwide. This study focuses on how
gamication can engage online students from skills, emotional, participation, and performance
perspectives. A mixed method has been applied to further explore the relationships between
gamication components and online students’ engagement and how online students perceive the
impacts of gamication on their online learning experience. This study extended the research about the
gamication mechanics that foster online learner engagement and offered guidelines for future online
course design and development.
Introduction
Online learning is dened by Singh and Thurman (2019) as “Education being delivered in an online
environment through the use of the internet for teaching and learning. This includes online learning on
the part of the students that is not dependent on their physical or virtual co-location. The teaching
content is delivered online, and the instructors develop teaching modules that enhance learning and
interactivity in the synchronous or asynchronous environment” (p. 302). According to Seaman, Allen, and
Seaman (2018), online teaching and learning have risen steadily for the past decade in higher education
institutions. In 2016, approximately 31.6% of students took at least one online education course. In 2021,
11.2million college students (60%) took at least one class online, and about 8.9million students (47%)
took college classes exclusively online (NCES, 2022). After the pandemic, online learning has become
the new normal worldwide (Bozkurt, 2020; Theirworld, 2020; United Nations, 2020a).
As online learning trends continue, new questions have also arisen. People began to face the issue of
students’ satisfaction and whether online learning was as effective as face-to-face learning in terms of
learning outcomes (Robinson & Hullinger, 2008). Kucuk and Richardson (2019) claimed engagement to
be an additional predictor of satisfaction. Previous studies revealed that engagement positively affects
satisfaction in online education (Gray & DiLoreto, 2016), and students who engage in online courses
would experience more satisfaction.
Among various strategies for enhancing students’ learning experience, gamication has been considered
a growing education phenomenon due to its impact on students’ learning (da Rocha Seixas et al., 2016;
Göksün & Gürsoy 2019), and it also serves as an instructional method to improve teaching, increase
student engagement and interactivity, and encourage learners to grow their skills (Zainuddin et al.,
2020b). Based on prior research, this study will explore the potential impacts of gamication on online
students’ engagement based on a global social learning platform named “CourseNetworking” and aims
to shed light on future gamication design and development in other educational contexts.
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Literature Review
Engagement
Student engagement, also initially known as student involvement, learning involvement, or learning
participation, has been getting more attention, in part, due to Astin’s (1984) “Student involvement: A
developmental theory for higher education.” Student engagement, as a term, is not well dened. Kuh
(2003) views engagement as “the time and energy students devote to educationally sound activities” (p.
25), and Appleton, Christenson, and Furlong (2008) dened engagement as students’ psychological
investment and behavioral involvement in the learning activities.
Student engagement study went through a process from a single dimension to a multi-dimension (Hu &
Li, 2017). Earlier research on students’ engagement tended to only focus on the behavioral dimension,
but later it expanded to both the behavioral and emotional dimensions (Finn, 1989; Marks, 2000;
Newmann et al., 1992; Willms, 2003) and, nally, included the cognitive dimension (Fredricks et al., 2004;
Jimerson et al., 2003; Klem & Connell, 2004; Qiping Kong, 2000). Since none of the research specically
mentioned the dimensions concerning
online
students’ engagement, Dixson (2015) proposed his
engagement dimension specically for online students built upon the measurement of traditional
classroom student engagement conducted by Handelsman, Briggs, Sullivan, and Towler (2005). Dixson
claimed that online student engagement should be measured concerning what students do (actively and
in their thought processes) as well as how they feel about their learning and the connections they are
making with the content, the instructor, and other students in terms of skills, participation, performance,
and emotional engagement. From this perspective, an online student engagement study should be
conducted from four dimensions, namely, (1) skills engagement (i.e., keeping up with readings, putting
forth effort), (2) emotional engagement (i.e., making the course enjoyable, applying it to their own lives),
(3) participation/interaction engagement (i.e. having fun, participating actively in small group
discussions), and (4) performance engagement (i.e., doing well on tests, getting a good grade)
(Handelsman et al., 2005, p. 187).
Meyer (2014), Banna et al. (2015), and Britt (2015) asserted the importance of student engagement in
online learning because student engagement can be shown as “evidence of students’ considerable effort
required for their cognitive development and their given ability to create their knowledge, leading to a
high level of student success” (Martin & Bolliger, 2018, p. 206). Furthermore, according to Banna et al.
(2015), if content played a central focus in the past, engagement plays a vital role in stimulating online
learning today.
Gamication
Gamication has long been discussed as a practical strategy to engage students in learning. The
denition of the term gamication was rst introduced around the 2000s (Braga, 2022). Until now, a
formal and scientic denition for gamication has still not been agreed. Hamari et al. (2014) described
gamication as “a process of enhancing services with (motivational) affordances to invoke gameful
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experiences and further behavioral outcomes” (p. 3026). Werbach (2014) dened gamication as a
process of making activities more game-like or generating a game-like experience. The most widely
referenced denition of gamication thus far was put forth by Deterding et al. (2011), who claim
gamication is the use of game elements and game design techniques in non-game contexts.
Nowadays, gamication has been widely adopted in many elds, including business, marketing, health,
technology design, and education, and has been considered an important strategy to ensure student
involvement and engagement (Johnson et al., 2014).
Game Mechanics and Components
Gamication needs to be realized by integrating game mechanics and game dynamics into non-game
situations (Bunchball, 2010). Game mechanics refers to the elements that allow players to exhibit higher
engagement via motivation. According to Werbach and Hunter (2012), the most important mechanics
are challenge (e.g., puzzles or other tasks that require effort to solve), competition (i.e., one player or
group wins, and the other loses), chance (i.e., elements of randomness), cooperation (i.e., players must
work together to achieve a shared goal), resource acquisition (i.e., obtaining useful or collectible items),
feedback (i.e., information about how the player is doing), rewards (i.e., benets for some action or
achievement), turns (i.e., sequential participation by alternating players), transactions (i.e., trading
between players, directly or through intermediaries), win states (i.e., objectives that make one player or
group the winner—draw and loss states are related concepts).
To realize the game mechanics discussed above, learners need to interact with the “design objects” in
the foreground, which refers to the gamication components. Yılmaz (2015) discussed specic
examples of gamication components based on Werbach and Hunter’s (2012) “Gamication Toolbox”
and categorized these components into Avatar (i.e., the characterization of the players in the game),
Awards (i.e., an element of goal that should be achieved in a particular process, a promise to reach a
target and motivation for subsequent stages), Points (i.e., an expression of every measurable change
and behavior), Badges (i.e., visual designs that symbolize the achievements of a user after a completed
task), Leaderboard (i.e., a competitive environment that presents the latest ranking in a construct where
the users compete with each other), Level/Progress Bar (i.e., a progression indicator to differentiate
player’s knowledge and experiences and indicate what needs to be complete), and Quests (i.e., a
complete view of the goals and observation of where the player is in the big picture).
Schacht and Schacht (2012) talked about three main targets that gamication mechanics pursuing
optimal user experience focus on: (1) display progression, (2) provide feedback, and (3) engage in a
specic behavior. To fulll these targets, Points, Badges, and Leaderboards have been considered the
favorite gamication components concerning the gamication design in an online context (Antonaci et
al., 2019). However, the complexity of game mechanics does not guarantee that every game element has
the same impact on learner engagement in a given learning environment. Therefore, this study intends to
explore further whether specic gamication components can affect learners’ engagement and in what
ways they can make it.
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Gamication Theories
The most discussed theories for explaining gamication mechanics are the Self-Determination Theory
(SDT) and the Flow Theory (Krath & von Koresch, 2021).
According to the Self-Determination Theory mentioned by Ryan and Deci (2000), people’s inherent growth
tendencies and innate psychological needs are the basis for their self-motivation and personality
integration. They identied three types of needs: (1) competence (Harter, 1978; White, 1963) people need
to gain mastery of tasks and learn different skills, (2) relatedness (Baumeister & Leary, 1995; Reis, 1994)
people need to experience a sense of belonging and attachment to the others, and (3) autonomy
(deCharms & Carpenter, 1968; Deci, 1975) people need to feel in control of their own behaviors and
goals. These are essential factors for facilitating optimal functioning for human growth and integration.
Besides, inspired by the positive reinforcement mechanics of behaviorist theory (Skinner, 1953), Deci
(1975) also divided human motivation into two main types: intrinsic motivation and extrinsic motivation.
In this theory, he described the intrinsically motivated individual as those who engaged in an activity
because of their inherent interest but not due to an external source. In contrast, the extrinsically
motivated individual refers to those who perform a task for an external outcome different from the task
itself. The fulllment levels of the three psychological needs will affect people’s motivation status, help
transfer extrinsic motivation to intrinsic motivation, and increase engagement. Instructional designers
and educators often apply these theories as the designing principles to explain and support their
gamication design thinking in online contexts (Gené et al., 2016; Khalil et al., 2017; Ortega-Arranz et al.,
2017, 2019; Romero-Rodriguez et al., 2019; Tsay et al., 2018).
The Flow Theory was dened by Csikszentmihalyi (2000) as a state of human absorption characterized
by intense concentration, loss of self-awareness, and a feeling of being perfectly challenged. To maintain
this psychological state, designers need to be very careful in designing online gamied tasks that are
neither too hard for learners to be discouraged nor too easy for learners to feel bored. This theory has
been adopted by designers or educators when they need to decide the diculty levels of certain
gamication elements in online courses (Hansch et al., 2015; Ortega-Arranz et al., 2019).
Mixed Gamication Impacts on Education
According to Dicheva et al. (2015) and Hamari et al. (2014), as an academic topic of interest,
gamication is still relatively novel and lacks established theoretical frameworks and unied discourses.
About a decade ago, Dicheva et al. (2015) conducted an empirical study on gamication in education.
After analyzing 34 related studies, they found the most used gamication mechanics in education:
points, badges, leader boards, levels, virtual currency, progress bars, and avatars. Similarly, Hamari et al.
(2014) identied the ten most common motivational affordances: points, leader boards,
achievements/badges, levels, story/theme, clear goals, feedback, rewards, progress, and challenge.
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Coetzee et al. (2014) and Denny (2013) claimed that game mechanics such as badges, leader boards,
and points can signicantly affect students’ behavioral engagement, as they can be observed in the
number of messages posted or tags produced (Mekler et al., 2013). However, in 2013, Dominguez et al.
(2013) realized that the experimental (gamied) group performed better in practical application but had
poorer results in the nal written exam aiming to test the knowledge of concepts explained in the course.
Likewise, Hew et al. (2016) reported that gamication mechanics produced greater contributions in
student discussion forums, while no signicant difference was found in students’ recall of information.
On the other hand, in a longitudinal study of the effects of gamication in the classroom, Hanus and Fox
(2015) concluded that using game mechanics like badges, leaderboards, and competition does not
improve educational outcomes. As they stated, “Gamication in the classroom may be a double-edged
sword” (p. 160) because for students who are inherently interested in the subject and motivated to learn,
gamication can even diminish their intrinsic motivation. Similarly, Huang et al. (2020) pointed out that
educational researchers and practitioners have struggled with identifying when, where, and how to use
gamication design based on the meta-analysis they conducted.
Research questions like which gamication design elements are potentially more effective in facilitating
the learning process, why gamication appears to work in some disciplines but not others, and whether
there are confounding variables in these subjects (i.e., the nature of particular subject matters and/or the
nature of learning processes of these subject matters, the nature of the students or instructors, or the
culture of the domain that conict with the overall tenants of gamication) are still unanswered
questions that need further explorations from scholars that hopefully will lead to greater optimization of
people’s learning experiences.
Research Questions
Though studies have also shown that gamication can be used to improve students’ engagement
(Hanus & Fox, 2015; Sanmugam et al., 2016; Dixson, 2015), the research on gamication applications in
the online learning environment is still in its early stages, and studies of its impact on students’ online
learning experience need further exploration. Based on the above literature reviews and emerging
research gaps, this study explores the impacts of gamication on students’ engagement in an online
learning context and what theoretical and practical implications can facilitate future gamication design
and improvement. The research questions for this study are as follows:
RQ1: Does a specic gamication component correlate with online students’ engagement, or to be more
specic,
RQ1.1: Does the gamication component Points correlate with online students’ skills engagement,
emotional engagement, participation engagement, and performance engagement, separately?
RQ1.2: Does the gamication component Badges correlate with online students’ skills engagement
emotional engagement, participation engagement, and performance engagement, separately?
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RQ2: How do online students perceive the impacts of gamication on their learning engagement?
Methods
Online Learning Platform
The data was collected from the online course platform CourseNetworking (CN), developed based on the
concept of “academic social networking,” which is opposed to the typical learning management system
(LMS). Traditionally, the LMS focuses on course delivery and management, including informing and
guiding students on what to do next. In CN, students not only take online courses but also communicate
with each other through social discussion and create their own “ePortfolio” to demonstrate their latest
academic achievements to their peers. Students can share their learning interests and post to each other
or follow someone like they usually do on Facebook or Twitter. In effect, CN serves both as an LMS
platform for instructors to deliver online courses and as the “social media platform” for students from all
over the world to interact with each other. Two distinguishing gamication components of the CN
platform are introduced below.
Gamication Mechanics and Components on CN
Points Mechanics: Anar Seeds
On the CN platform, Anar Seeds (hereinafter referred to as Points) is a reward system that monitors
student activities and offers real-time points. Learners receive extrinsic rewards, Anar Seeds, in the form
of Points for participating in certain learning activities, such as making a post with a certain number of
words, reecting on a post, rating a peer’s post, and visiting the course. Course instructors may set up a
goal for students to complete and the system tracks and reminds students about their progress in
attaining the goal. Reward systems such as these provide incentives to students and recognition for their
participation, serving as positive reinforcers for learning (Kapp, 2012).
Badge Mechanics: CN digital badges
Badges are digital micro-certicates that can be used to motivate learners and recognize their
competencies and experiences. CN offers a series of ready-to-use to make the badge-issuing process as
simple as possible. Currently, there are 26 course-level ready-to-use badges, such as Critical Thinking,
Problem Solving, Best Post, Top 10%, Best Participant, and Outstanding Award. Online instructors can
modify the description and skills tags of these badges before awarding them to their students. Besides
these ready-to-use badges, instructors and institution admins can also create new badges. Badges
earned by a student are automatically added to their prole/ePortfolio, where they can share it to other
social media or download the baked badges with metadata.
Measurement
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This study adopted the Online Student Engagement Questionnaire (OSE), validated by Dixson (2015), to
measure online students’ engagement levels. The survey comprised 19 items that measure four
subscales of online students’ engagement regarding their online courses: (a) skills engagement
(questions 1, 3, 4, 5, 6, 7), (b) emotional engagement (questions 2, 8, 9, 10, 11), (c) participation
engagement (questions 12, 13, 14, 17, 18,19), and (d) performance engagement (questions 15, 16). The
OSE exhibited concurrent validity and strong reliability (α = 0.91) and could be applied to offer an easy,
valid, and reliable way to measure students’ engagement in online courses. The survey to measure online
students’ engagement on the CN platform in this study has been slightly modied based on Dixson’s OSE
to help online learners better understand the questions on the CN virtual contexts (see Appendix). The
modication was made under the supervision of one quantitative study consultant, one qualitative study
consultant, and one professor specializing in instructional design study to ensure its validity.
Conrmatory Factor Analysis (CFA) was conducted using Jamovi to test the validation of the modied
OSE scale. The CFI is 0.931, and the root mean square error of approximation (RMSEA) is 0.0510,
demonstrating an acceptable CFA model t. The Cronbach’s alpha of modied OSE in this study is 0.926,
indicating high inter-item reliability.
Data Collection
The survey was published on the CN platform on March 23, 2023, and was closed on April 10, 2023,
during which all active online students were invited to take the survey voluntarily. The survey will show up
once online students open their online courses, and they can choose whether to take the survey.
Participants
440 responses were collected from the online learners on CN who came from 19 countries around the
world; notably, the majority of the population was from Malaysia, Sri Lanka, and the United States. The
participants came from over 100 online courses on the CN platform, ranging from natural to social
science. Over half of the participants had been registered members on CN for at least one year (Table1),
and all participants had taken at least one online course and had collected either Points or Badges on
the CN platform. The gender distribution has not been included due to access limitations.
Table 1 Demographic information of the respondents (n=440)
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n %
Country
Malaysia
Sri Lanka
United States
France
Singapore
China
India
Finland
Indonesia
Iraq
Ireland
Jordan
Laos
Maldives
Myanmar
Oman
Russia
Rwanda
Yemen
Unknown
252
81
64
9
5
4
4
1
1
1
1
1
1
1
1
1
1
1
1
9
57.3
18.4
14.5
2.0
1.1
0.9
0.9
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
2.0
Registration on CN (years)
< 1
1-5
≥ 6
146
292
2
33.2
66.4
0.4
The survey also included three open-ended questions following the 19 items to collect qualitative data
from online learners’ voluntary responses regarding their perceptions of gamication’s impacts on their
engagement. Finally, 562 lines of perceptions were collected from 440 online students for qualitative
coding.
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CN also permitted data collection concerning online students’ achievement of Points and Badges. The
CN data team provided the number of points and badges achieved by each participant in the survey.
Data Analysis
For quantitative analysis, IBM SPSS Statistics 28 was used to run the correlation between Points
collected by online students and their skills, emotional, participation, and performance engagement
separately. The correlation was also run to check the relationship between the number of collected
Badges and online learners’ skills engagement, emotional engagement, participation engagement, and
performance engagement, respectively. As the normality assumption was not met, Spearman’s rho for
non-parametric tests was used to assess these correlations.
For qualitative analysis, Nvivo 14 was adopted to code and analyze the textual content of online learners’
responses regarding their perception of gamication impacts, aiming to provide methodological
triangulation of the quantitative data (Ivankova et al., 2006). Another scholar who studies game-based
learning and serious games assisted with coding, checking the major themes together, and triangulating
the code book with 100% agreement.
Results
Correlation Outcomes
For the rst research question, among the 440 survey responses, 234 Points achievers completed all 19
questions in the survey; therefore, their engagement scores have been sorted out for correlation
analysis. The mean (SD) skills engagement, emotional engagement, participation engagement, and
performance engagement scores for Points achievers were 23.94 (3.565), 19.62 (3.031), 20.74 (4.61),
7.77 (1.463), respectively (Table 2).
Table 2 Statistical analysis of mean OSE subscale (skills engagement, emotional engagement,
participation engagement, and performance engagement) scores for Points achievers (n=234)
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Mean (±SD) Minimum value Maximum value
Skills engagement (6–30)
Emotional engagement (5–25)
Participation engagement (6–30)
Performance engagement(2–10)
23.94
(3.565)
19.62
(3.031)
20.74
(4.61)
7.77
(1.463)
6.0
5.0
6.0
2.0
30.0
25.0
30.0
10.0
Of all 440 participants, only 86 who acquired at least one Badge have been sorted out for the correlation
study. The mean (SD) skills engagement, emotional engagement, participation engagement, and
performance engagement scores for Badge achievers were 19.62 (8.688), 15.47 (8.439), 15.98 (10.421),
5.79 (3.726), respectively (Table 3).
Table 3 Statistical analysis of mean OSE subscale (skills engagement, emotional engagement,
participation engagement, and performance engagement) scores for Badge achievers (n=86)
Mean (±SD) Minimum value Maximum value
Skills engagement (6–30)
Emotional engagement (5–25)
Participation engagement (6–30)
Performance engagement (2–10)
19.62
(8.688)
15.47
(8.439)
15.98
(10.421)
5.79
(3.726)
0
0
0
0
30.0
25.0
30.0
10.0
Signicant positive correlations between Points and the OSE score were detected (Table 4). As it shows,
the coecients between the score of Points and the four domains of the OSE (put in sequence: Skills
engagement, Emotional engagement, Participation engagement, and Performance engagement) were
0.146 (p<0.05), 0.274, 0.248, and 0.293 (p<0.01), respectively.
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Table 4 Spearman’s correlation coecients between Points and OSE subscale (skills engagement,
emotional engagement, participation engagement, and performance engagement) scores (n=234)
Skills
engagement Emotional
engagement Participation
engagement Performance
engagement
Average
Points 0.146* 0.274** 0.248** 0.293**
*Correlation is signicant at the .05 level (2-tailed)
**Correlation is signicant at the .01 level (2-tailed)
Meanwhile, only one signicant positive correlation between Badges and four domains of the OSE was
found. The coecient between the Badges and Participation engagement was 0.225 (p<0.05), and no
signicant correlations have been observed between the Badges and the rest of the SOE domains (Table
5). These results have answered RQ1.1 and RQ1.2.
Table 5 Spearman’s correlation coecients between Badges and OSE subscale (skills engagement,
emotional engagement, participation engagement, and performance engagement) scores (n=86)
Skills
engagement Emotional
engagement Participation
engagement Performance
engagement
Total
Badges
0.094 0.194 0.225* 0.054
*Correlation is signicant at the .05 level (2-tailed)
To answer RQ2, the impact of gamication on online students’ engagement was further explored by
conducting a textual analysis of online students’ perceptions of gamication, which were reected in
their responses to the three open-ended questions. Examples of evidence for coding have been
illustrated in Table 6. The textual analysis has triangulated the statistical results and cross-validated the
research ndings.
Table 6Examples of perception regarding gamication impacts
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Themes Codes Denitions Quotes
Positive
perceptions Skills
Engagement What students do (i.e., staying up
on readings, `listening/reading
carefully)
“seeing an increase in my
anar seeds give me
motivation to keep
studying and browsing
through study materials”
Emotional
Engagement How connected or applicable
students feel to the course/content
(i.e., applying course material to
their lives, really desiring to learn
the material)
“The Anar seeds force me
to think of new questions
to ask that haven't been
posed by other students”
Participation
Engagement Students interact with others to
enjoy the content/course ((i.e.,
participating actively in small-group
discussion forums, helping fellow
students)
“Anar seeds, competition
among learners, which can
encourage them to work
together and support one
another”
Performance
Engagement Students’ desire/goal to succeed in
the course ((i.e., getting a good
grade, doing well on tests/quizzes)
“i love anar seeds it gives
me extra credit in my
class”
Negative
perceptions Skills
Engagement What students do (i.e., staying up
on readings, listening/reading
carefully)
“Tbh.I don’t really care
about those things ,it’s all
about self discipline”
Emotional
Engagement How connected or applicable
students feel to the course/content
(i.e., applying course material to
their lives, really desiring to learn
the material)
“No, it just give me
pressure to add more
words when im submitting
assignment when i didnt
need to”
Participation
Engagement Students interact with others to
enjoy the content/course ((i.e.,
participating actively in small-group
discussion forums, helping fellow
students)
“While I compete with
myself, I am not a
competitive person in
relation to others”
Performance
Engagement Students’ desire/goal to succeed in
the course ((i.e., getting a good
grade, doing well on tests/quizzes)
“I feels like this do nothing
for me but if tis can be one
of the grade for the
certicate would be great”
Positive Perception of Points on Online Learners’ Engagement
Perception of Points on Skills Engagement
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Serving as the extrinsic reward for online learners’ desired behaviors, such as quality posting, reecting,
and contributing to the course dialogue, Points can be effective in providing positive reinforcers for
learning (Kapp, 2012). Students could accumulate Points by conducting or nishing specic online
activities. Consequently, their learning behaviors are inuenced or altered during the Points collection
process.
Some students responded that Points motivated them to study regularly or form an active learning habit
by reecting that “seeing an increase in my Points gives me motivation to keep studying,” “It gave me a
motivation to collect more therefore I’m more often on CN scrolling through notes,” and “Anar Seeds…
keeps one motivated to keep studying through CN.” The application of the rewarding mechanics of
Points proved to be effective in maintaining online students’ regular or consistent visits to either the
online platform or their learning material, thus helping keep their online course retention rate.
Notably, a regular visit to either the online platform to check on their status or a timely review of course-
related notes could be perceived as a form of self-regulation. Self-regulation, or is often thought to be the
same thing as self-control, has been dened by Vohs and Baumeister (2011) as the “overriding of one
action tendency in order to attain another goal” (page 3). It has been claimed that effective self-
regulation can foster health-promoting behaviors (Fuhrman & Kuhl, 1998), positive psychological well-
being (Baumann et al., 2005), and high job performance (Diefendorff et al., 2000). On the other hand, as
Kuhl et al. (2006) pointed out, it is not easy to put self-regulation theory (SRT) into practice. The
application of gamication (Anar Seeds) in promoting online students’ skills engagement, or to be more
specic, the construct of self-regulation, can be viewed as one practical strategy to put SRT into practice
in an online learning context.
Perception of Points on Emotional Engagement
Emotional engagement talks about online students’ endeavors about their studies, their willingness to
connect what they have learned to their lives, and their desire to learn. Based on these emotional
engagement indicators, specic responses have been identied as positive perceptions of Points
impacts on online learners’ emotional engagement. Some students replied that Points help them “work
hard” to get more seeds and increase their learning willingness, whereas they did not clarify what the
“work hard” behaviors look like or to what extent their learning willingness can be. One student
mentioned his desire by stating, “The Points force me to think of new questions to ask that have not
been posed by other students.” In other words, Points positively impacted students’ desire to learn more
by asking novel questions in their study.
One aspect that has appeared repetitively in almost one-third of all the responses concerning Points’
positive impacts on online students’ engagement is the “availability of tracking.” Nine out of 32 online
students who reected their positive perceptions about Points mentioned that Points are practical in
helping them keep on track of online learning endeavors, such as their study progress, effort spent on
each course, and estimation of the workload in the courses. Online students also appreciated the ease
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of tracking progress and the enjoyable process of tracking points accumulation; however, tracking
availability did not directly relate to the emotional engagement indicators.
The theoretical implications hidden beneath these responses cannot be ignored. Participants also
mentioned that seeing the accumulation of Points can help them “get an idea about my current position,”
“shows the work I have done…make me happy,” and “Anar Seeds…view my power.” Seen from these
perceptions, Points were found to elicit participants’ sense of accomplishment by showing them up-to-
date progress to strengthen their self-ecacy. They can also provide the condence to achieve learning
goals reected as their personal “power,” which can increase the participants’ emotional engagement
and overall desire to learn more.
Perception of Points on Participation Engagement
According to Dixon (2015), participation engagement refers to online learners’ active and diversied
involvement in different learning activities, including online chats, discussions, online conversations, and
forums, as well as their social interactions with their peers, including the willingness to know or to help
their peers. Although not many respondents mentioned specically the impact of gamication on their
participation engagement, several distinctive conrming viewpoints were revealed.
One agreed that collecting Points elicited their competitive motivation and monitored “how active I am
compared to others.” From this response, it’s interesting that the gamication mechanics impacted
online learners’ participation engagement not in cooperation but in competition, where the learner gained
self-fulllment by collecting enough Points to demonstrate his endeavor beyond his peers.
Of course, there are also responses mentioning both competition and cooperation. One response replied,
"Points (motivated) competition among learners, which can encourage them to work together and
support one another.” It seems that the collection of Points helped encourage cooperation among
learners to win certain forms of competition in online learning activities, and gamication can be utilized
to either motivate a personal sense of competitiveness or group efforts of active participation.
Also, one response mentioned, "When I need to increase my Anar Seeds, I always try to put a good post
or poll because it gives 10 and 5 Points for each.” This is a typical example of how Points can enhance
online students’ participation engagement by encouraging them to make active polls or posts to share
their thoughts with others. Similarly, another response conrmed that Points can motivate learners to
complete tasks and participate in activities as long as the Points are set to be a “tangible goal to work
towards.”
From the above, Points are proven effective in motivating online students’ participation engagement by
eliciting their sense of competition, willingness to cooperate, and desire to complete tangible tasks.
What needs to be taken care of is the potential harm to participation engagement caused by either the
over-indulged competitions on pure collections of Points or the inappropriate setting of Points goals,
which might sabotage learners’ participation engagement and learning motivation.
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Perception of Points on Performance Engagement
In OSE, only two indicators (i.e., a good grade/doing well on tests) have been used to reect online
students’ performance engagement. One response replied that she loved Points because they gave her
extra credit in her class. However, she did not detail whether the extra credits will be accumulated to her
grade or scores on tests and quizzes; therefore, further exploration is needed, such as semi-structured
interviews of participants’ perceptions of how the Points impact their performance engagement.
Negative Perception of Points on Online Learners’ Engagement and Suggestions on Gamication Design
Improvement
Only one response mentioned how negative perceptions of Points impacted their specic engagement:
“The gamication features do not help with my engagement. It feels like additive work since my
instructor requires a certain amount of Points to receive points in class.” Interestingly, the online learner’s
psychological resistance to nishing learning tasks was aroused by the instructor but not by the
gamication design or its mechanics. According to this perception, earning a certain amount of Points
seems to be compulsory work requested by the instructor but not a motivating reward for the learner to
earn on his or her willingness. This is a typical example when discussing gamication mechanics and
SDT theory (Ryan & Deci, 2000) where engagement is closely linked to satisfying the three psychological
needs: autonomy, competence, and relatedness. For this example, the learner’s autonomy has been
diminished by losing control over her actions; thus, the learner is less likely to engage willingly and
actively. Given this, it should be noted that the instructor can play a vital role in maximizing the
gamication mechanics in engaging online students by purposefully setting up reasonable goals and, at
the same time, offering students sucient autonomy so that they can feel a sense of control over their
behaviors and the tasks that are about to nish. Otherwise, the impact of gamication mechanics would
decrease.
Five respondents suggested improving Points design to facilitate online learners’ engagement in learning
activities. One person suggested that more Points should be awarded for high-quality content to
motivate students to
put forth effort on specic learning materials and enhance their emotional
engagement,
as indicated in Dixon’s (2015) OSE scale. Three showed their interest in getting a bonus gift
or claiming a “virtual currency” after their Points reached specic numbers, or they were willing to be
notied once their Points accumulation was updated. These gamication design changes might not
directly impact the online learners’ specic engagement. However, there is no doubt that they can help
maintain the positive attitudes of online learners toward their course retention and involvement in online
activities. Also, one respondent mentioned it would be “helpful if there was more detailed information on
what exactly each item is to better understand the Anar Seeds.” This response revealed the importance
of making game rules explicit and explaining to students how each gamication mechanic works, as
evidenced by Alomari et al.(2019) and Machajewski (2017).
Positive Perception of Badge on Online Learners’ Engagement
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Positive Perception of Badge on Participation Engagement
Participation engagement emphasizes social interactions among online students with their peers and
instructors during the online study, their interest and desire to know others, and their active involvement
in all online discussions. One respondent mentioned, “I do enjoy the badges… I was excited about the
content and meeting other like-minded individuals,” thereby showing his intention to reach out to other
online students that would promote his engagement to participate in different online activities.
Another reection conrmed the respondent’s preference for positive badge impacts on her online
learning by saying that “Badges, (it) can show to others how I’m active on cn (CourseNetworking).”
Interestingly, some online learners keep motivated or engaged in learning activities by showing their
achievements to their peers. In contrast to what has been discussed concerning “sense of achievement”
in the emotional engagement section, where online learners concentrate on their endeavors and self-
fulllment that does not necessarily rely on connection with other social members, this response
indicated the signicance of being “exposed” to others, a form of social connection or interaction to help
increase the intrinsic motivation which is a crucial driver of engagement—aligned with the Self-
Determination Theory (Ryan & Deci, 2000), which suggests that engagement is closely linked to the
satisfaction of the three critical psychological needs mentioned earlier: competence, autonomy, and
relatedness. Among these factors, relatedness can explain why the badge mechanics can be practical to
promote participation engagement as when learners are aware of their achievement being
acknowledged by the social community they are involved in, such positive social recognition can make
individuals feel encouraged and motivated to engage in their academic endeavors.
Though not many responses mentioned the badge impacts on their participation engagement, the
implication of badge impacts on online learners’ participation engagement is worth deeper discussion
and interpretation using related learning theories. Notably, badge earning reected the gamication
mechanic impacts on learners’ participation engagement. Of all the 440 responses, 86 reected that they
had earned at least one badge during their online course-taking. 181 badges in total have been earned.
The most earned badge types are: “Post of the week” (38 badges, 21% of all badges), “Great post” (27
badges, 14.9% of all badges), “Academic Integrity” (15 badges, 8% of all badges),“ePortfolio
Appreciation” (15 badges, 8% of all badges), “Course of the week” (11 badges, 6% of all badges), and
“Scavenger Hunt” (11 badges, 6% of all badges). Among these badges, “Post of the week” badge (this
badge recognizes CN members whose post received the highest ranking based on peer ratings over the
past seven days in their class), “Great post” badge (this badge recognizes CN members whose post was
selected as a high-quality post by course instructors), and “Scavenger Hunt” badge (This badge
recognizes a student’s participation and/or completion of the Scavenger Hunt activity) are representative
badges that record the endeavor of the online learners’ positive participation in online discussions, and
active interaction with peers for completing specic online tasks.
In addition, those badges that contribute to the promotion of online learners’ participation engagement,
such as the “Best Participant” badge (this badge recognizes active members of a class; seven badges
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have been earned), “Teamwork” (this badge recognizes learners’ collaboration experience and skills,
three badges have been earned) and “Community service” (this badge recognizes contributions to local
and global communities, one badge has been earned), though not too many of them have been obtained,
put together with badges of “Post of the week,” “Great post,” and “Scavenger Hunt,” have covered 48.1%
of all the badges (n=181) that have been earned. From this result and the positive correlation between
badges and online learners’ participation engagement, it can be proposed that badges designed to elicit
online learners’ involvement in online activities or social interactions can effectively enhance their
participation interests and engagement.
Suggestions on Gamication Design Improvement
No negative perceptions concerning badge impacts on specic learners’ engagement were received.
However, ten responses suggested how to improve the badge design, which might reect why badges
did not fully contribute to online learners’ engagement. Based on these responses, two major themes
have emerged regarding the learners’ expectations of badge design improvement to facilitate their
engagement.
Clear Description of Badge Rules
One learner mentioned, “I do not really notice badges, so maybe that feature should be emphasized
more,” indicating a lack of awareness toward the gamication elements on the CN platform. The limited
impacts of badges on his engagement were not caused by the design aw but by the ignorance of
gamication components that can be applied in learning activities. Likewise, another learner suggested
“include a list of all the ways you can earn badges or Points if there isn’t already,” implying that the
learners desire to know more about the gamication rules before applying them. Interestingly, this
suggestion echoed the suggestion about improving Points, where the learners hoped to better
understand how to accumulate Anar Seeds.
Sense of Control Over Earning Badges
Other responses demonstrated learner preferences for multiple or diversied choices of badge earning,
which would grant them a great sense of control over choosing specic badges to t their needs best.
For example, one learner expected to have more chances of earning badges once a week instead of
passively waiting for specic badges to be issued by the instructors or the system. Interestingly, another
learner wanted to be rewarded with specic badges as long as any tests or exams had been passed so
that her success could be noticed and appreciated. In addition, one learner was curious whether it is
possible to make the badge “redeemable” as Points, which means he could have the autonomy to “trade”
them for more tangible awards. Yet another learner suggested “make a higher tier badge” to make it
more engaging for competitive learners to choose from and meet their needs to obtain more challenging
badges.
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These suggestions can be summarized as online learners’ requests for a higher level of autonomy or a
greater sense of control over their behaviors on badge earning. Once again, the ndings are well in line
with the SDT theory (Ryan & Deci, 2000), where engagement is closely linked to the satisfaction of
autonomy, one of the three key psychological needs. The more that learners feel satised, the more
chances there are for them to engage willingly and actively in certain goals.
Research Implications
The outcomes from RQ1.1 revealed that the gamication element, Point (Anar Seeds), correlated with
four subscales of engagement (skills engagement, emotional engagement, participation engagement,
and performance engagement), signicantly correlated. However, for RQ1.1, only one positive correlation
between badges and participation engagement was captured.
Next, a textual analysis was conducted based on the voluntary responses of online learners’ perceptions
of gamication impacts on their learning to triangulate the quantitative data and seek possible reasons
for that correlation. The most representative quotes from online learners’ reections were selected and
analyzed to reveal the potential impacts of gamication. The follow-up coding analysis of the results
showed both positive and negative perceptions toward gamication on four engagement types, as well
as online learners’ suggestions about improving future gamication design that might help better
facilitate their learning engagement.
Theoretical Implications
Our ndings open the debate on using a series of theoretical lenses to understand certain gamication
components’ workings better. Each specic behavioral change triggered by gamication mechanics can
be well aligned with related psychological theories. To maximize the effects of gamication mechanics,
the results indicated that the implementation of gamication should fulll online learners’ psychological
needs to be autonomous in conducting the desired learning activities. At the same time, the lack of a
sense of control would diminish the learners’ engagement levels. In addition, relatedness, another critical
psychological need in SDT theory, explains why badge mechanics can effectively promote participation
engagement. When learners are aware of their achievement being acknowledged by the social
community, it will foster a sense of belonging and create an environment where individuals feel
encouraged and motivated to engage in learning activities.
We also realized that learners are demanding the diculty levels of specic gamication settings and
ask for “tangible goals in achieving Points” or the issue of “higher tier of Badges” to challenge
themselves with higher learning goals. The individual learner has specic demands for the challenge
levels to remain in a so-called “ow” status that proposes “intense concentration, loss of self-awareness,
and a feeling of being perfectly challenged” (ow theory) (Csikszentmihalyi (2000). To maintain this
psychological state, designers and instructors need to be careful in designing online gamied tasks that
are neither too hard for learners to be discouraged nor too easy for learners to feel bored.
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The mechanics of Points to drive learners’ behaviors or engagement levels can also be interpreted with
positive reinforcement, as described by Skinner in his theory of Operant Conditioning (1938). In positive
reinforcement, a response or behavior is strengthened by rewards that lead to the repetition of a desired
behavior, and the reward is usually seen as a reinforcing stimulus. In most gamication studies, Points
have played the role of encouraging targets to increase or repeat the desired behaviors by fullling their
motivational needs in the form of rewards, a stimulus that can be conducted promptly right after certain
desired behaviors have been observed. In other words, one crucial feature of gamication mechanics is
that it offers quick feedback to learners, thereby strengthening their sense of achievement or feeling of
control over their progress, promoting their autonomy and engagement behaviors in certain activities.
Several responses in the study mentioned that the collection of Points makes them want to “collect
more,” “earn more,” “do more work,” or “keep getting more,” a typical example showing the function of
positive reinforcement that can be realized through gamication mechanics to encourage the learners’
desired engagement behaviors. Interestingly, similar responses were not received in terms of earning
badges. Conceivably, part of the reason is that it would take learners a longer time and extra effort to
obtain certain types of badges, increasing the positive feedback timespan and reducing their sense of
control over their behaviors.
In addition, when analyzing learners’ preference for Anar Seeds’ “tracking” functions, updated records of
points accumulation grant learners a sense of accomplishment, which can contribute to eliciting “self-
ecacy” (Bandura, 1997), a concept that refers to an individual’s belief in their ability to perform specic
tasks or accomplish goals in various situations. Self-ecacy is one major component of Bandura’s
(1968) social cognitive theory, which claims that individuals with high self-ecacy are more likely to set
challenging goals, persevere through obstacles, and view failures as learning opportunities. In this study,
learners expressed their psychological satisfaction with what they had achieved, which can help
strengthen their self-ecacy to engage in more challenging tasks. Of course, the self-ecacy theory has
not yet been adequately investigated in explaining the effects of gamication (Krath et al., 2021), and
more empirical research is needed.
Practical Implications
This research presented the necessity of investigating the potential inuence of instructors’ application
strategies of specic gamication components in their online class design. As is reected in the
negative perceptions of Points and some suggestions on improving the badge design, we realized that
the inappropriate settings would affect learners’ motivation and engagement level and diminish the
benets of the gamication mechanics. Learners cannot take full advantage of gamication in
motivating their engagement if instructors fail to inform them of the availability of those gamication
components (“I do not really notice badges, so maybe that feature should be emphasized more”), clarify
the rules of earning rewards (“Maybe include a list of all the ways you can earn badges or Points if there
isn’t already”), and inappropriately set the earning goals so that it sabotages learners’ motivation (“It
feels like additive work since my instructor requires a certain amount of Points to receive points in
class”). Therefore, it is implied that the instructors have played an essential role in scientically
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implementing gamication components in the class activity design. Instructors are suggested to learn
how to integrate gamication components to maximize their mechanics for enhancing engagement by
constantly asking for learner feedback and adjusting accordingly. This can be considered a benecial
supplement to the TPACK (Technological Pedagogical Content Knowledge) skills (Koehler and Mishra,
2009), which educators rely on to effectively incorporate technology to enhance learning outcomes,
especially in an online learning context.
The research also found that the design of gamication components (i.e., points, badges) impacts their
functions and learners’ user experience. In our analysis of learners’ reections on gamication impacts,
some responses expressed their preference for certain features of the gamication components that
have not been embedded in the gamication design. As the effects of game elements are personal and
differ widely between different learners (Buckley & Doyle, 2017; Mekler et al., 2017; van Roy & Zaman,
2017), it is worth further exploring how instructional designers or HCI designers perceive the design
principles, and how their design thinking would inuence the implementation of gamication to impact
online learners’ engagement levels.
Methodological Implications
Unlike prior gamication research (Coetzee et al., 2014; Denny, 2013; Hew et al., 2016; Mekler et al.,
2013) that primarily examines the collective impact of multiple gamication components on student
learning, this study identies correlations between specic gamication components and particular
engagement subscales. This research elucidates the relationships between individual gamication
elements and distinct types of engagement, providing a more nuanced understanding of their effects.
Then, the correlation results were triangulated using the qualitative analysis of survey responses
regarding online students’ perceptions of gamication in their learning. This methodology design can
benet researchers by helping them gain a deeper understanding of whether the gamication mechanics
inuence each engagement type and a thorough interpretation of potential reasons why the
implementation of gamication would positively or negatively impact online learners’ engagement. In
addition, this methodology design also contributes to the methodological diversity regarding
gamication research with e-learning (Kamunya et al., 2022).
Limitations and Future Directions
There are several limitations in this study that must be pointed out. First, the survey of online learners’
engagement was self-reported. As a result, the results might be inuenced by respondents’ biases and a
lack of objective measurement. In addition, in the OSE (Dixson, 2015), the measurement of performance
engagement has only two constructs that would limit the measurement accuracy and
comprehensiveness of the results.
Second, not all respondents nished answering each question in the engagement survey, which lowered
the correlation’s accuracy rate.
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Third, some respondents’ reections on gamication perception were short, oversimplied, or unclear,
which might affect the researcher’s interpretation of their actual views and experiences.
Fourth, no respondents mentioned their perceptions of badge impacts on their skills performance,
emotional engagement, and performance engagement; therefore, more qualitative data for these
sections needs to be collected and further analyzed, and the gamication mechanics of badges in this
research must be suciently investigated.
Based on the current research ndings and limitations, we suggest that future research be conducted to
evaluate online learners’ engagement using objective psychological measurements instead of self-report
surveys. Psychological measurements should be conducted to assess online learners’ motivations since
this psychological construct is closely related to engagement and would impact the engagement level
changes. At the same time, semi-structured interviews or focus group interviews would help acquire
more thorough views and perceptions from online students, instructors, and gamication designers
about either their intentions to apply gamication components or design thinking for the gamication
mechanics, which would greatly help people better understand the gamication impacts and how to
optimize their effects in online learning contexts. In addition, as points, badges, and leaderboards are the
favorite gamication elements concerning the gamication design in an online context (Antonaci et al.,
2019), different game elements, such as leaderboards that have not been discussed in this research,
could also be included in future gamication studies of Course Networking or similar platforms to gain a
more precise comprehension for applying gamication. In addition, socio-demographic factors and their
potential effects on online learners’ gamication perceptions could also be discussed and contribute to
getting more reliable ndings for future gamication studies.
Conclusion
While gamication has garnered signicant attention in the twenty-rst century, the idea of using games
or playful elements in education is not new. Throughout history, educators have employed various game-
like techniques to enhance learning, from educational board games to interactive classroom activities.
As a result, more questions have arisen as gamication’s effectiveness in educational contexts is
scattered and varied from case to case. Given this background, we advocate a thorough understanding
of how specic gamication mechanics work and under what circumstances they will impact certain
learning activities.
This study initially explored this issue using a quantitative method in which 440 online learners’
engagement was measured to see its correlation with the number of Points and badges being collected
on a global social learning platform. After that, a qualitative analysis was conducted to triangulate the
quantitative research results and seek more insightful ndings on interpreting the reasons for the
signicant correlation. By doing this, we learned that the number of Points being collected was positively
correlated with online learners’ skills, emotional, participation, and performance engagement. We also
learned that the number of collected Badges positively correlated with online learners’ participation
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engagement. No correlation between Badges and skills, emotional, and performance engagement was
detected in this study. We also explored more deeply the gamication mechanics that impact each type
of engagement by textually analyzing the online learners’ perceptions about the impact on their learning
activities. We realized that gamication mechanics can inuence online learners’ psychological status.
For future studies, it is highly recommended that investigations be made from either the instructors’ or
the gamication designers’ perspective to seek any other factors that might contribute to the
implementation of gamication in the online learning context.
Abbreviations
CFA
conrmatory factor analysis
CN
CourseNetworking
LMS
learning management system
OSE scale
Online Student Engagement scale
RMSEA
root mean square error of approximation
SDT
Self-Determination Theory
Declarations
Ethics approval and consent to participate:
This study has been approved by Indiana University Bloomington Human Subjects & Institutional Review
Boards under protocol # 15406.
Consent for publication:
Not available.
Availability of data and materials:
The datasets generated and/or analyzed during the current study are not publicly available because they
are under the privacy protection of the CN platform, but they are available from the corresponding author
at reasonable request.
Competing interests:
The authors declare that they have no competing interests.
Page 24/30
Funding:
This study was not funded by any grants or contracts.
Authors' contributions:
CM generated the research ideas, designed the study framework, modied the Online Student
Engagement scale, collected and analyzed the data, and drafted the manuscript; MZ modied the Online
Student Engagement scale, distributed the survey, advised on data collection methods, accommodated
data collection, advised on data cleaning, proofread and revised the manuscript; ZP advised on data
cleaning and coding, proofread and revised the manuscript; QP advised on data cleaning and availability
check; CB introduced the research platform, offered writing feedback, proofread and revised the
manuscript, and supervised the research process.
Acknowledgements
We want to express our deep appreciation to Dr. Ali Jafari, the founder and co-developer of
CourseNetworking, for granting us access to CourseNetworking for survey distribution and data
collection.
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Appendix
Appendix is not available with this version.
Figures
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Figure 1
Anar Seeds (i.e., Points) Displayed on a Student’s CN Prole/ePortfolio
Figure 2
Badges Earned by a CN User
