Gamification in MOOCs: A systematic literature review

Abstract

Gamification has the potential to enhance learner motivation and increase participation, thereby improving MOOC’s retention rates. However, challenges exist in finding the balance between learning and gamification elements and ensuring effective implementation, as well as the limited availability of established gamification frameworks tailored for MOOCs. The purpose of this review is to shed light on the current state of research, identify research gaps and answer them. The findings underscore the importance of finding a balance in gamification design with game elements’ use, addressing implementation challenges, MOOC platforms, and developing tailored frameworks for MOOCs to optimize learner engagement and retention rates.

Keywords:

• gamification
• MOOC
• review
• SLR

1. Introduction

MOOCs often face challenges with low retention rates, as learners may struggle to stay engaged throughout the course (Goopio & Cheung, 2021). One potential solution to address this issue is the implementation of gamification. By incorporating game elements into the learning experience, gamification can enhance learner motivation and increase participation, thereby improving the retention rate (Deterding et al., 2011; Groh, 2012) and (Hamari et al., 2014).

However, implementing gamification in MOOCs comes with both benefits and challenges. On the positive side, gamification can boost learner engagement, create a sense of accomplishment, and promote a more interactive and enjoyable learning environment. However, challenges arise in terms of finding the right balance between learning and gamification elements, ensuring effective implementation, and limited availability of established gamification frameworks tailored specifically for MOOCs. This Systematic Literature Review, hereafter referred as SLR, aims to shed light on the current state of research and identify research gaps.

This paper is structured as follows. In section 2, the SLR methodology used will be explained. In section 3, the base concepts of this research are explained and some introduction on other SLRs read for this review. Sections 4, 5 and 6 cover the planning, conducting, and reporting phases of an SLR. Section 7 is the discussion of results covered in the Reporting phase. Section 8 presents the conclusion of this research and its limitations.

2. Research methodology

An SLR is a rigorous and structured approach to conducting a review of existing research literature on a specific topic. This SLR was conducted following the guidelines defined by (Keele, 2007; Kitchenham, 2004) and (Webster & Watson, 2002), showed in Figure 1. It contains the following phases:

Figure 1. Adapted SLR phases (Kitchenham, 2004).

• Planning - entails identifying the research problem and its motivation, formulating the research questions, defining exclusion and inclusion criteria, and developing a thorough search strategy to identify relevant literature;

• Conducting - entails data extraction from selected literature after a careful search, filtering, and selection based on previously defined criteria;

• Reporting - entails compiling a thorough overview of the selected literature, as well as synthesizing and interpreting the conclusions of the selected literature, discovering common themes, and presenting them.

3. Research background

This research background aims to explore the intersection of Massive Open Online Courses (MOOCs), Gamification and analyze other SLRs on these topics.

3.1. Massive Open Online Courses (MOOCs)

Massive Open Online Courses, or MOOCs, are a particular kind of online course that are created to be available to a wide range of students online (McAuley et al., 2010). MOOCs span a variety of areas, such as computer science, mathematics, humanities, social sciences, and more. They are often offered by universities, educational organizations, or online learning platforms.

The potential to accommodate tens of thousands of students from around the world is one of the distinguishing characteristics of MOOCs. Technology systems that enable the delivery of course content, interactive elements, and evaluation tools make this possible. The lack of teacher assistance, and reliance on automated techniques are among MOOC characteristics that also help the MOOC expand and reach a large audience while offering a distinctive learning experience for a variety of learners throughout the world (Pappano, 2012).

To enhance learning, MOOCs often include readings, quizzes, assignments, discussion forums, and video lectures. Participants may access the course materials and complete tasks at their own leisure, allowing for flexible learning schedules. On completion of specified requirements, some MOOCs additionally grant completion certificates or even academic credit.

Another benefit of a MOOC is that anybody with an internet connection may access it, regardless of their location, age, educational background, or level of experience (McAuley et al., 2010). This gives MOOCs the distinct characteristic of massiveness and heterogeneity of participants. They give people the chance to develop new skills, broaden their knowledge, and research topics of interest without having to formally enrol in a conventional educational institution.

3.2. Gamification

Gamification is the process of enhancing services that are non-game environments, with motivational elements in an effort to invoke gameful experiences and further behavioural outcomes (Hamari et al., 2014). It entails adding components like points, badges, leaderboards, challenges, levels, and prizes to processes or activities that aren’t by nature game-based (Groh, 2012).

Gamification uses people’s innate drive for competitiveness, success, and advancement to improve the fun, interactivity, and motivation of tasks or experiences. It aims to boost participation (Deterding et al., 2011), improve learning, encourage behaviour change, and promote engagement by using elements of games (Triantafyllou & Georgiadis, 2022).

Even while gamification has the potential to increase motivation and engagement, it must be applied carefully and wisely (Triantafyllou & Georgiadis, 2022). Since poorly designed or too simplified gamification can result in shallow involvement or even disengagement (Bakar et al., 2017), it is important that the design and execution of gamified systems match with the specific aims and target audience (Rohan et al., 2021). Table 1 details some environments in which gamification is or can be used and provides some examples.

Table 1. Gamification environments and examples

Environment	Example
Education	Duolingo uses gamification by incorporating elements such as levels, points, streaks, and leaderboards to motivate language learners and make the process of learning a new language engaging and fun.
Fitness	Strava uses gamification by encouraging users to compete with friends, earn achievements for personal records, and climb leaderboards based on their running and cycling activities, creating a sense of friendly competition and motivation.
Business	Slack uses gamification by awarding users with badges and points for active participation, encouraging engagement, and creating a sense of community and collaboration within the workplace.
Marketing	Moche Infinity, offered by a Portuguese telecommunications company, incorporates gamified elements such as challenges, points, and rewards for users who engage with the app and participate in various activities, enhancing customer interaction and loyalty.
Health	MyFitnessPal allows users to track their daily calorie intake, exercise, and weight goals while integrating gamified features like streaks, achievements, and progress milestones, motivating users to maintain healthy habits and stay committed to their fitness journey.
Social Media	TikTok utilizes gamified elements such as challenges, trends, and interactive filters to encourage users to create and share creative videos, engage with trending content, and earn virtual rewards and recognition through likes, comments, and follower growth.

3.3. MOOCs & gamification

The main goal of MOOCs is to offer free and open online courses. However, the high dropout rate has been a major concern among researchers and lecturers over the years (Goopio & Cheung, 2021; Romero-Rodriguez et al., 2019). As such, gamification may be utilized as a tactic to increase motivation and participation in those courses (Morales et al., 2016; Saraguro-Bravo et al., 2016), thus reducing this dropout rate, while adding a great number of additional benefits.

Learners can experience a feeling of success and competition by using gamified elements of a MOOCs, such as badges and leaderboards, which can increase their engagement and commitment to finishing the course (Triantafyllou & Georgiadis, 2022). Gamification may increase learner engagement and lower dropout rates by enhancing the learning process and making it more interactive, fun, and immersive (Hocine, 2021).

Gamification in MOOCs can also offer chances for individualized learning experiences (Fu et al., 2018). Learners may customize their learning experience to suit their requirements by choosing from a variety of pathways, unlocking new challenges or information based on their success, and receiving quick feedback.

Learners can also feel more connected to one another and more collaborative (Martínez-Núñez et al., 2015). Learners may interact with one another, share information, and aid each other’s learning processes through discussion forums, social sharing of accomplishments, and cooperative challenges (Navío-Marco & Solórzano-García, 2021; Romero-Rodriguez et al., 2019).

3.4. Systematic literature reviews

SLRs are frequently used in academic research to offer comprehensive insights into specific fields of study. This section aims to conduct a comparative analysis of three SLRs (Antonaci et al., 2019; Jarnac de Freitas & Mira da Silva, 2023) and (Khalil et al., 2018), each focused-on Gamification and MOOCs. By comparing them, this section aims to shed light on the current state of research and identify research gaps.

Table 2 offers an overview of the specific topics covered in the three SLRs. It not only lists these focused topics but also indicates the corresponding SLRs in which each topic is extensively discussed. By examining the table, it is easily identifiable the areas of research covered in each SLR and the distribution of topics across the reviews. Section 7 will compare their findings to the findings of this SLR.

Table 2. SLR’s focused topics

Focused topics	Antonaci et al. (2019)	Jarnac de Freitas and Mira da Silva (2023)	Khalil et al. (2018)
Considered factors in a successful gamification implementation	x
Gamification effects	x	x	x
Gamification elements’ implementation			x
Gamification elements used	x	x	x
Gamification challenges			x
Performance evaluation identifiers		x
Research methods used in previous studies			x
Theories used in Gamification Design		x	x
Types of MOOC		x

From the table we can see that the most focused topics are gamification effects and gamification elements used, mentioned in all three SLRs, as these two topics are a crucial part of the merge of gamification and MOOCs (Jarnac de Freitas & Mira da Silva, 2023) and (Khalil et al., 2018) both focus on the theories used in gamification design. Individually, the three SLRs each cover more topics. In particular (Antonaci et al., 2019), aims to provide insights into the crucial factors to consider for successful implementation in MOOCs (Jarnac de Freitas & Mira da Silva, 2023) aims to provide insights into the relationship between MOOC types and performance evaluation identifiers (Khalil et al., 2018) aims to provide insights into the research methods used in studies, game elements’ implementation strategies, and challenges in the current state of gamification in MOOCs.

4. Planning phase

The execution of the SLR’s Planning phase is shown in this subsection. We begin by outlining the motivation for this study, following with the research questions we hope to address, and then reveal our review protocol.

4.1. Motivation

As it was said previously in section 3.3, gamification may be utilized as a strategy to increase motivation and participation in those courses (Morales et al., 2016), thus reducing the high dropout rate MOOCs are facing, while adding a great number of additional benefits. However, there is still more work to be done in terms of demonstrating data about the impacts of gamification when used in MOOCs, including whether they are benefits or challenges, in terms of establishing and applying gamification frameworks, and in terms of which platforms to utilize them.

4.2. Research questions

The research questions below serve as a foundation for the conducted study and meticulous analysis done:

RQ1:

In what ways can gamification elements benefit MOOCs?

RQ2:

What challenges arise when including gamification elements in MOOCs?

RQ3:

What are the most used gamification elements/strategies for improving learning outcomes in

RQ4:

What effective existing gamification frameworks are used in MOOCs?

RQ5:

What MOOC platforms can be gamified?

4.3. Review protocol

The review protocol used is described in this section, including the search and filtering process of papers. Starting with the search process, we first need to define the search string, used in the selected dataset’s search. Since our two main themes are MOOCs and Gamification, the term “mooc*” (referring to “mooc*” and “moocs”) and the term “gamif*” (referring to “gamification”, “gamify”, “gamified”, “gamifying”, etc.) were used. This search string considers the abstract of the papers.

Search String AB mooc* AND AB gamif*

Dataset EBSCO Discovery Service

When using the chosen search string in EBSCO, we applied some filtering criteria right before searching, through the dataset built-in filters. These criteria are:

• Peer-reviewed papers;

• Integral text available;

• Papers from academic journals and conference materials;

• Written in English, Portuguese or Spanish.

After we obtain our results, that meet all criteria above, we must apply our remaining criteria, and these are:

• Mention of benefits of gamifying MOOCs;

• Mention of challenges when gamifying MOOCs;

• Mention of gamification elements, their use and results in MOOCs;

• Mention of gamification frameworks used in MOOCs;

• Mention of gamified/gamifiable MOOC platforms;

The results obtained after applying these filters must meet at least one of the above-mentioned criteria.

5. Conducting phase

The execution of the SLR’s Conducting phase is shown in this subsection. We begin by applying the review protocol designed for this study, following with the analysis of the extracted data.

5.1. Selection of studies

After applying the search string and research engine built-in criteria, EBSCO returned 207 results. Of these 207, 64 duplicates were automatically deleted, leaving us with 143, that were later exported to Rayyan, a web-tool designed to help researchers working on systematic reviews. From these 143 papers, 31 were duplicates and 5 were not in the desired languages, leaving us with 107 papers. To further iterate on these papers, the abstract was read, categorizing the papers into three categories: Included; Maybe; and Excluded. Out of these 107 papers, 49 were categorized as Excluded, 31 were categorized as Maybe, and 32 were categorized as Included. The papers categorized as Maybe were then read again and out of the 31 only 16 remained, that left us with 48 papers. The final screening was reading the full paper, leaving us with 35 papers. Out of 35 papers, 3 are SLRs, and were discussed in section 3. The other 32 were used to answer the research questions. Figure 2 represents the selection process iterations.

Figure 2. Flow diagram of the selection of studies.

5.2. Data extraction analysis

We start off with an analysis of authors, shown in Table 3. This table highlights the authors who wrote more than 1 paper selected in this review.

Table 3. Authors with more than 1 papers selected

Authors	Papers
Alejandra Martínez-Monés/Alejandro Ortega-Arranz	Ortega-Arranz et al. (2018, 2019a, 2019b, 2022)
Alessandra Antonaci/Roland Klemke	Antonaci et al. (2018), Klemke et al. (2020)
Álex Rodríguez/Anna Puig/Inmaculada Rodríguez	Puig et al. (2023), Rodríguez et al. (2022)
Debajyoti Pal/Rohani Rohan/Suree Funilkul	Rohan et al. (2021, 2021)
Jun He/Qing Qing Xu/Qiao Yan Fu	Fu et al. (2018, 2019)
Yung-Ming Cheng	Cheng (2021, 2023)

Looking at the type of publication of the selected papers, we can observe in Figure 3 that 28% of papers come from conferences (9 papers), and the rest 72% of papers come from journals (23 papers).

Figure 3. Publication type distribution.

The analysis for the years of publication is summarized in Figure 4. The concentration of papers examined in the last years may be attributed to the topic’s recent age and rise in popularity, as seen by the figure.

Figure 4. Publication date distribution.

6. Reporting phase

The execution of the last phase of the SLR methodology is shown in this section. The identified results from the careful analysis of each paper in the supporting literature will allow us to answer the previously defined research questions.

6.1. RQ1: In what ways can gamification elements benefit MOOCs?

The benefits of gamification elements in MOOCs identified in these articles are shown in Table 4, from the articles that mentioned them the most to the ones that mentioned them the least.

Table 4. Identified benefits in the supporting literature

Benefits	Papers
Increase learners’ motivation	Alves (2020), Bakar et al. (2017), Chang and Wei (2016), Cheng (2023), Hagedorn et al. (2022), Hocine (2021), Metwally and Yining (2017), Ortega-Arranz et al. (2019b), Panyajamorn et al. (2022), Rincón-Flores et al. (2020), Rohan et al. (2020, 2021), Saputro et al. (2019), Saraguro-Bravo et al. (2016)
Stimulate learners’ participation	Barrére et al. (2017), Chang and Wei (2016), Cheng (2023), Fu et al. (2019), Hocine (2021), Metwally and Yining (2017), Ortega-Arranz et al. (2019a, 2019b, 2022), Puig et al. (2023), Rincón-Flores et al. (2020), Wang et al. (2017)
Increase MOOC’s retention rate	Borrás-Gené et al. (2019), Cheng (2021), Cheng (2023), Dikcius et al. (2021), Metwally and Yining (2017), Panyajamorn et al. (2022), Puig et al. (2023), Saraguro-Bravo et al. (2016), Vaibhav and Gupta (2014)
Increase learners’ satisfaction	Cheng (2021), Cheng (2023), Dikcius et al. (2021), Hocine (2021), Puig et al. (2023), Rincón-Flores et al. (2020), Saraguro-Bravo et al. (2016), Topîrceanu (2017)
Increase learners’ engagement	Bakar et al. (2017), Chang and Wei (2016), Cheng (2023), Metwally and Yining (2017), Ortega-Arranz et al. (2019b, 2022), Puig et al. (2023)
Increase MOOC’s completion rates	Bakar et al. (2017), Borrás-Gené et al. (2019), Fu et al. (2019), Navío-Marco and Solórzano-García (2021), Vaibhav and Gupta (2014)
Increase learners’ enrollment	Cheng (2023), Fu et al. (2019), Metwally and Yining (2017), Vaibhav and Gupta (2014)
Increase learners’ performance	Chang and Wei (2016), Cheng (2023), Hocine (2021), Rincón-Flores et al. (2020)
Increase learners’ relatedness	Cheng (2023), Rohan et al. (2020), Saputro et al. (2019), Topîrceanu (2017)
Increase learning outcomes	Cheng (2023), Hagedorn et al. (2022), Ortega-Arranz et al. (2022), Panyajamorn et al. (2022)
Increase learners’ autonomy	Cheng (2023), Rohan et al. (2020), Saputro et al. (2019)
Personalized learning process	Fu et al. (2018), Hocine (2021), Metwally and Yining (2017)

The most identified benefit was the increase of learner’s motivation (Saraguro-Bravo et al., 2016), with 14 article mentions. Motivation may be determined by the learner’s eagerness and willingness to participate in MOOC activities and accomplish the learning objectives. The learner may still be motivated even if their only objectives are to obtain the MOOC materials or participate in a few of the assigned tasks. A MOOC’s design has the potential to alter a learner’s motivation and objectives.

The second most identified benefit was participation (Fu et al., 2019), with twelve articles mentions. Participation refers to the level of a learner’s interaction with the course’s activities and materials as well as with other learners and lecturers.

Of the thirty-two articles, nine reported the MOOC’s retention rate (Metwally & Yining, 2017). A MOOC’s retention rate usually refers to the percentage of learners who continue to engage with and participate in the course’s activities over time. Due to its similar meaning, it can be easily confused with a MOOC’s completion rate, that refers to the percentage of learners who successfully complete a MOOC, earning a certificate or a credential. Many learners can remain enrolled even if they haven’t finished the MOOC. The MOOC’s completion rate (Fu et al., 2019) was reported in 5 articles.

Another eight articles also mentioned the learner’s satisfaction (Topîrceanu, 2017). The term “satisfaction” speaks for itself; it describes how happy and satisfied a learner is with the overall MOOC design and its contents.

Learner’s engagement (Puig et al., 2023) was identified in seven articles. Engagement refers to the level to which a learner is active and involved in the learning process. Several indicators, including the amount of time spent on an activity, the level of the work produced, and the frequency of participation in forums and discussions, can be used to quantify the engagement.

Also in the articles, the learner’s enrolment (Metwally & Yining, 2017), performance (Chang & Wei, 2016), sense of relatedness (Rohan et al., 2020) and outcomes (Ortega-Arranz et al., 2022) were identified four times. Enrolment is easily defined by the number of learners who registered and showed interest in a MOOC. Performance refers to a learner’s overall success in the course in terms of their grades, completion of assignments, involvement in discussions, and other indicators that measure their progress and engagement with the course material. A learner’s sense of relatedness in a MOOC refers to their sense of social connection or belonging to the MOOC community. This sense of relatedness includes how strongly students identify with one another, the teacher, and the course subject. Outcome refers to the skills, competences, and knowledge the learner has gained from the MOOC, including the ability to apply them in real-world scenarios.

Lastly, we have the learner’s autonomy (Saputro et al., 2019) and the personalized learning process (Fu et al., 2018), identified three times in the articles. As MOOCs are created to give learners flexibility and opportunities for self-directed learning, autonomy is a key concept. The capacity of a learner in a MOOC to take charge of their own learning process and make choices about what, when, and how they study is referred to as autonomy. Personalized learning is regarded as advantageous because it can increase learner engagement with the MOOC’s materials and outcomes. MOOCs can assist in addressing the difficulty of providing effective education to a vast community of learners by offering learners individualized learning experiences that are suited to their unique requirements, interests, and prior knowledge.

6.2. RQ2: What challenges arise when including gamification components in MOOCs?

The challenges that arise when adding gamification elements in MOOCs identified in the supporting literature are shown in Table 5, from the articles that mentioned them the most to the ones that mentioned them the least.

Table 5. Identified challenges in the supporting literature

Challenges	Papers
Extra time and effort added by the lecturers to implement gamification strategies	Metwally and Yining (2017), Ortega-Arranz et al. (2018, 2019a), Panyajamorn et al. (2022), Rohan et al. (2021)
Finding the balance point for the combination between learning and gamification elements	Bakar et al. (2017), Chang and Wei (2016), Fu et al. (2019), Metwally and Yining (2017), Saputro et al. (2019)
Some gamification elements’ effectiveness depend on how they are implemented	Alves (2020), Ortega-Arranz et al. (2018, 2019b),; Saputro et al. (2019), Vaibhav and Gupta (2014)
Some gamification elements are not adequate for all MOOC participants	Ortega-Arranz et al. (2019b), Rodríguez et al. (2022), Rohan et al. (2020, 2021)
Gamification strategies must have in account MOOC characteristics	Ortega-Arranz et al. (2019b), Rodríguez et al. (2022), Rohan et al. (2021)
MOOC platforms can hinder the application of gamification elements	Metwally and Yining (2017), Ortega-Arranz et al. (2018, 2019b)

In the supporting literature, the most identified challenges with five article mentions were: Extra time and effort added by lecturers to implement gamification strategies—lecturers need to spend time researching gamification strategies, understanding how the tools and platforms work, and how to utilize them to their benefit (Panyajamorn et al., 2022); Finding the balance point for the combination between learning and gamification elements—overusing a game element may have the opposite effect, as a poor balance may lead to learner’s demotivation (Bakar et al., 2017); Some gamification elements’ effectiveness depend on how they are implemented, for example, if rewards are not used properly they may lead to problematic consequences of competition, which can result in unethical behaviour (Vaibhav & Gupta, 2014).

Additionally, with four article mentions, we have the challenge that some gamification elements are not adequate for all MOOC participants, as each learner has its own profile, based on the HEXAD questionnaire (Rodríguez et al., 2022), and they may lose interest if they get to the state of boredom (oversimplified) or to the state of anxiety (overchallenging) (Ortega-Arranz et al., 2019b). The effect gamification elements may have on learners could also depend on the learner’s age, gender, or ethnicity (Blunt, 2007).

Lastly, we identified that gamification strategies must have in account MOOC characteristics, e.g., massiveness of learners, reliance on automatic methods, lack of instructor facilitation, etc., and that MOOC platforms can hinder the application of gamification elements, for example, if the MOOC platform has limited access to its database, the automation of redeemable rewards is hindered (Ortega-Arranz et al., 2018), were the least identified challenges, with three article mentions.

6.3. RQ3: What are the most used gamification elements for improving learning outcomes in MOOCs?

The most used gamification elements for improving learning outcomes in MOOCs identified in the supporting literature are shown in Table 6, from the articles that mentioned them the most to the ones that mentioned them the least.

Table 6. Identified gamification elements in the supporting literature

Gamification Elements	Papers
Rewards	Alves (2020), Bakar et al. (2017), Barrére et al. (2017), Chang and Wei (2016), Hocine (2021), Metwally and Yining, (2017), Navío-Marco and Solórzano-García (2021), Ortega-Arranz et al. (2018, 2019a, 2022), Rodríguez et al. (2022), Rohan et al. (2020, 2021), Saputro et al. (2019), Wang et al. (2017)
Leaderboards	Alves (2020), Bakar et al. (2017), Barrére et al. (2017), Chang and Wei (2016), Hocine (2021), Metwally and Yining (2017), Rodríguez et al. (2022), Rohan et al. (2021), Saputro et al. (2019)
Avatars	Danka (2020), Hocine (2021), Rohan et al. (2020, 2021), Saputro et al. (2019)
Levels	Bakar et al. (2017), Fu et al. (2018), Metwally and Yining (2017), Rodríguez et al. (2022) Saputro et al. (2019)
Progress bar	Bakar et al. (2017), Hocine (2021), Metwally and Yining (2017), Rohan et al. (2021), Saputro et al. (2019)
Feedback	Fu et al. (2018), Hocine (2021), Metwally and Yining (2017), Wang et al. (2017)
Storytelling	Hagedorn et al. (2022), Rohan et al. (2021), Saputro et al. (2019), Saraguro-Bravo et al. (2016)
Peer-to-peer evaluation	Barrére et al. (2017), Chang and Wei (2016), Fu et al. (2019)
Points	Chang and Wei (2016), Danka (2020), Saputro et al. (2019)
Social tools	Navío-Marco and Solórzano-García (2021), Rodríguez et al. (2022), Rohan et al. (2020)
Quests	Rodríguez et al. (2022), Saputro et al. (2019)
Virtual map	Saputro et al. (2019), Topîrceanu (2017)
Lives	Saputro et al. (2019)

The most used gamification element that was identified in the support literature is rewards, with fifteen article mentions out of thirty-two. Rewards are also one of the most effective gamification elements (Ortega-Arranz et al., 2019b). Rewards refer to something given to a player in recognition of their achievements or progress. These rewards include but are not exclusive to badges, points, trophies, virtual currency, and virtual goods.

The second most used gamification element identified were leaderboards, with nine article mentions. Leaderboards are a tool that show and rate the performance, accomplishments, and scores of learners. They are a graphic representation of the top-scoring learners, sometimes shown as a list or a chart. Leaderboards can be separated for a block (a quiz) or for the whole course (Bakar et al., 2017).

With five article mentions, we have identified avatars, levels, and progress bar. In the digital environment of a MOOC, an avatar is a graphical depiction of a learner. Avatars can be altered to reflect a learner’s ideal appearance, personality attributes, or other aspects. Avatars can give a free choice for users and create stronger feelings of autonomy (Rohan et al., 2020). A level is a specific step or section of a MOOC that learners advance through. Levels are created to offer a planned and sequential experience, often getting harder or more sophisticated as learners move up the levels (Fu et al., 2018). A progress bar is a visual representation typically used in user interfaces to indicate the MOOC’s completion status or progress (Bakar et al., 2017).

With four article mentions, we have feedback and storytelling. Feedback refers to the information provided to learners regarding their performance, progress, or actions within the learning environment. It is a great element to provide results transparency (Metwally & Yining, 2017), and generates positive emotions of satisfaction in learners (Rincón-Flores et al., 2020). Storytelling is the art of immersing players in a narrative-driven experience. It makes learners immerse themselves more in the human-system interactions, that may lead to evoking emotional experiences such as excitement, passion, motivation and satisfaction (Cheng, 2023). In contrast to (Antonaci et al., 2019), we do not suggest that a character is the one telling the story when we use the term “storytelling”, but more of an equivalent to “narrative” (Triantafyllou & Georgiadis, 2022).

Peer-to-peer evaluation is a process where individuals assess and provide feedback on each other’s work or performance. It is a gamification element that may improve the quality of the students’ score (Fu et al., 2019), together with skill points, the numerical measure of a learner’s abilities or expertise in specific areas, and social tools, such as forums, blogs, chats, and karma (Navío-Marco & Solórzano-García, 2021), were identified in three articles in the supporting literature.

Quests, or missions, are specific objectives or tasks that players undertake within the course’s narrative or structure. Virtual maps are the digital representation of the game world or environment that helps learners navigate and explore the virtual space. These two elements were identified in two articles in the supporting literature. These elements may increase user immersion, with the potential to motivate MOOC learners (Rodríguez et al., 2022).

Lastly, we identified lives, that represent the number of chances or attempts a learner has before facing a game over or failure condition. This is an element that may increase learner autonomy (Saputro et al., 2019), with only one article mention. They can be used in a quiz for example, giving the learner multiple tries before failing.

6.4. RQ4: What existing gamification frameworks are used in MOOCs?

In the supporting literature, three existing gamification frameworks were identified. These gamification frameworks are shown in Table 7.

Table 7. Identified gamification frameworks in the supporting literature

Gamification Framework	Papers
MARC framework	Saputro et al. (2019)
PAGE model	Maher et al. (2020)
GaDeP framework	Klemke et al. (2020)

The MARC framework is a framework with the goal of increasing a learner’s intrinsic motivation. It consists of several essential stages that can help the MOOC design phase, providing a different learning experience than other MOOCs. These stages relate to observational learning, retention and context within forum discussion and collaboration, states of mind through task, quiz or exam, and challenge and progression within rewards and punishments (Saputro et al., 2019).

The PAGE (Personalized Adaptive Gamified E-learning) model is used to extend MOOCs by providing new levels of learning analytics and visualizations in the learning process, used to customize and adapt educational materials based on those understandings, as well as visualizing the process and adaptation decisions to the learners. It is divided in three modules: course design module; personalized gamified learning flow module; and learning analytics and personalized adaptation module (Maher et al., 2020).

The GaDeP framework (Gamification Design Process) is a framework designed to specifically address the lack of theoretical soundness and the missing support of empirical evaluation of the gamification design. It is comprised of six phases, these are: the analysis of the gamification design’s application scenario, like its requirements, and other parameters; the definition of a problem that the designer aims to address; the selection of a theoretical framework, applicable to the problem and application scenario; the selection of game elements that best address the problem; the practical implementation of the designed gamified solution; and the evaluation phase to measure the effects of the previously implemented design (Klemke et al., 2020).

6.5. RQ5: What MOOC platforms can be gamified?

The MOOC platforms that can be gamified identified in the supporting literature are shown in Table 8, from the articles that mentioned them the most to the ones that mentioned them the least.

Table 8. Identified MOOC platforms in the supporting literature

MOOC platform	Papers
Moodle	Barrére et al. (2017), Panyajamorn et al. (2022), Puig et al. (2023), Saraguro-Bravo et al. (2016), Saputro et al. (2019)
Coursera	Chang and Wei (2016), Puig et al. (2023)
edX	Hagedorn et al. (2022), Panyajamorn et al. (2022)
Canvas Network	Ortega-Arranz et al. (2018)
NanoMOOCs	Rodríguez et al. (2022)
Openlearning.com	Saputro et al. (2016)
openHPI	Hagedorn et al. (2022)
Udacity	Hagedorn et al. (2022)

The most identified MOOC platform in the supporting literature is Moodle, with five article mentions. Moodle is an online learning platform that offers educational institutions an extensive and adaptable environment to provide courses and support online learning. The most used gamification elements in Moodle are rewards and leaderboards (Saputro et al., 2019).

Following Moodle, we identified edX and Coursera, with two article mentions. The platforms EdX and Coursera provide a variety of courses from renowned colleges and institutes, making higher education accessible and affordable to students all around the world. These two platforms mainly use rewards and badges as gamification elements to attract and maintain learners (Chang & Wei, 2016).

Lastly, with one article mention, we have the following five platforms: Canvas Network; NanoMOOCs; Openlearning.com; openHPI; and Udacity. Canvas Network is an online learning platform that gives academic institutions and teachers a collaborative setting in which to provide courses and interact with students. NanoMOOCs focuses in providing brief, clear, and targeted MOOCs (Massive Open Online Courses) to provide students rapid bursts of concentrated information. Openlearning.com is an innovative online learning environment that prioritizes social and interactive learning opportunities, allowing students to connect with course materials and work with classmates. The Hasso Plattner Institute developed the openHPI platform, which provides MOOCs with an emphasis on computer science and information technology issues. Udacity is an e-learning platform that provides courses and nanodegree programs that are relevant to the business and were created in partnership with top IT firms.

7. Discussion

Five research questions were addressed in this SLR’s section 6, and the results associated with each will be discussed in the paragraph that follows. Afterwards, we will proceed in comparing our results with the results obtained in the SLRs previously mentioned in section 3.4.

We notice that the most cited benefit is increase learners’ motivation, followed by stimulate learners’ participation in second and increase the MOOC’s retention rate in third. Regarding RQ2, the most cited challenges are extra time and effort added by the lecturers to implement gamification strategies, finding the balance point for the combination between learning and gamification elements and some gamification elements’ effectiveness depend on how they are implemented. These challenges can be related to the fact that there are few gamification frameworks, supported by RQ4, where we only identified three frameworks (MARC framework, PAGE model, and GaDeP framework), and given these are papers, published on academic journals and conference materials, the difficulty to reach lecturers might be other reason for these obstacles.

Some of these challenges, for example the balance point between learning and gamification elements might be related as well to lack of lecturers’ effort and spending time researching gamification in MOOCs. The most identified MOOC platform that can be gamified is Moodle, as identified in RQ5, with rewards and leaderboards as the most game elements used in the platform, falling in line with the findings in RQ3. As these are easy to implement, and Moodle is a common platform in higher education, these can be overused in MOOCs created by lecturers, creating these challenges, where the effect obtained could be the opposite of the effect desired, e.g. a lecturer might want to motivate the learners by adding an unhealthy amount of rewards, demotivating the learners and possibly increasing the MOOC’s dropout rate.

Consistent with our RQ1 findings, increased motivation was likewise mentioned as the most frequent benefit in (Khalil et al., 2018). These findings are comparable to those in (Jarnac de Freitas & Mira da Silva, 2023), where increase learner’s engagement was the most cited benefit and increase learner’s motivation was the second-most cited benefit. Motivation is also the second most mentioned benefit in (Antonaci et al., 2019), with performance coming in top. In (Khalil et al., 2018) the most identified challenge was that gamification approaches were applied for a certain group and not generalized. This challenge wasn’t identified in our RQ2 findings. Consistent with our RQ3 findings, rewards were mentioned as the most identified game element in all SLRs (Antonaci et al., 2019; Jarnac de Freitas & Mira da Silva, 2023; Khalil et al., 2018) with leaderboards coming up in second place. Unlike our previous RQs, none of the previously SLRs address gamification frameworks like our RQ4, only theories used in gamification design, nor they address MOOC platforms that can be gamified like our RQ5.

8. Conclusion

In this SLR, we analysed the effects of gamification in MOOCs. For this goal, 32 papers and 3 SLRs were reviewed. The literature highlights increased learners’ motivation as the most cited benefit of gamification in MOOCs, followed by stimulated learners’ participation and increased retention rates. The challenges identified include the additional time and effort required by lecturers to implement gamification strategies, finding the right balance between learning and gamification elements, and the effectiveness of gamification elements depending on their implementation. We identified Moodle as the most gamifiable MOOC platform and that there was a limited availability of gamification frameworks, as we only found three.

The main limitations experienced so far are related to the SLR performed, as it was only performed with the EBSCO search engine, and there were some papers we could not use. Another limitation we found was the identification of some terms, as some authors used the same terms with slightly different meanings.

Acknowledgments

This research was developed in the scope of the project “Pacto de Inovação ECP - Ecocerâmica e Cristalaria de Portugal”, project number C627467067-00463548, co-financed by the Recovery and Resilience Plan, the Portuguese Republic, and NextGenerationEU.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Rodrigo Rodrigues Major

Rodrigo Rodrigues Major, a student pursuing a master’s in Computer Science and Engineering, is now writing his thesis on gamification frameworks for MOOCs.

Miguel Mira da Silva

Miguel Mira da Silva, Full Professor of Information Systems at Instituto Superior Técnico, he is also responsible for the research unit “Digital Transformation” at INOV. In addition to leading various scientific initiatives at the national and international levels, he has extensive professional experience, having founded five enterprises and working on the growth of several more. He earned an MSc in Management (Sloan Fellowship) from London Business School and a PhD in computer science from Glasgow University.