Learning engagement in massive open online courses: A systematic review

Massive Open Online Courses (MOOCs) attract thousands of participants who each exercise autonomy by engaging with resources and with other participants to whatever degree they wish. When analyzing participants’ patterns of engagement in MOOCs it is possible to notice that certain participants exhibit high levels of participation, actively engaging with others in forums. This study focuses on characterizing these highly active participants, and understanding their contributions back to the network in a MOOC designed for teachers’ professional development. Connectivism is used as theoretical lens to describe super-posters’ engagement in forums. Data from participants’ demographics, click-data, and forum posts are used to identify these highly active users. Qualitative content analysis is used to categorize the content of their posts, and social network analysis is used to represent their patterns of engagement. Results show that super-posters are generators of engagement, repurposing the content learned from the MOOC and feeding-forward new resources to the network. Super-posters can be seen as representatives of participation inequality in forums. They position themselves as the most prestigious and most influential nodes in the networks created by participants as they engage in forums. In some networks super-posters served as bridges, connecting people from different discussion threads and helping information to flow through the network. This study provides to MOOC designers and MOOC instructors an affordable method to identify and classify super-posters in any MOOC. Findings of this study could be used by MOOC designers and MOOC instructors to develop pedagogical interventions to give these participants a special role in the next MOOC cohort, which may foster engagement in MOOC forums and nurture the cyclical process of learning described in Connectivism. Regarding implications for research, this study attends the need for qualitative methods when analyzing participants’ engagement in MOOC forums and contributes to our knowledge of participation inequality. It also extends the literature of super-posters by showing their characterization in a MOOC focused on teachers’ professional development.

This chapter analyzes the instructional quality and learning design of different categories of online courses and their history, with a special focus on massive open online courses (MOOCs). Online courses have a long tradition that has gained public attention, broad interest, and huge numbers of participants thanks to the introduction of free MOOCs accessible online for all interested learners worldwide. In this chapter, we first define MOOCs, their characteristics, and history. Afterward, theoretical frameworks and practical instruments and tools based on scientific research are presented. From the beginning, the quality of MOOCs (and of online courses in general) has been debated. That led to discussions about the learning design and outcomes of MOOCs, which we introduce in the next section. Key research findings and practical validated instruments for designing and evaluating MOOCs (and online courses in general) are presented. Then following, the key benefits of MOOCs and the main arguments and scenarios for their usage are summarized. Based on our analysis of the research results, practices, and standards, a framework for categories and types of (massive open) online courses is proposed, called the typologies of online courses (TOC) framework. As part of the global community for open educational resources (OER) and in combination with the UNESCO recommendation on OER, MOOCs can play a significant role in achieving the SDG4 of the United Nations: inclusive and equitable quality education for all. This is true in particular during times of public lockdowns, such as during the ongoing COVID-19 pandemic.

The running security and stability of massive open online course's teaching network directly affect the implementation process of massive open online course's teaching tasks. In order to provide valuable reference data for the management and maintenance of the network, this paper puts forward an analysis method of abnormal traffic of higher vocational massive open online course's teaching network based on deep convolution neural network. According to the structure of the teaching network of massive open online course in higher vocational colleges, a network model is built. Under this model, the flow data is collected, and the preprocessing of the initial flow data is completed through data cleaning, standardized conversion and clustering. The deep convolution neural network is established, and the characteristics of network traffic data are extracted through back propagation iteration. After discrete detection and feature matching, the abnormal traffic in the teaching network of higher vocational massive open online course is detected, and the visual analysis results are obtained. Compared with the traditional network abnormal traffic analysis method, it is found that the detection error and missed detection rate of the optimized design method are reduced by 3.75MB and 1.02% respectively, the accuracy of traffic abnormal type analysis is increased by 1%, and the analysis speed is obviously improved.KeywordsDeep Convolution Neural NetworkTeaching in Massive Open Online CourseTeaching NetworkAbnormal Flow Analysis

Massive open online courses (MOOCs) continue to remain in the spotlight as a promising future education environment. However, more than 80% of learners stop learning before attending one-third of the course. Despite a continuous spread of MOOC and high dropout rate, little has examined the antecedent factors that influence student engagement in technology enhanced MOOC learning environment from the Job Demand-Resources (JD-R) model. The purpose of this study was to empirically identify the effects of individuals’ basic psychological needs and the task–technology fit on MOOC learners’ continuance intention to use, as well as the mediating effect of student engagement in MOOCs. Based on survey data from 201 Korean-MOOC learners, structural equation modeling was employed to assess the model. The findings are as follows: The basic psychological needs in MOOCs did not directly affect continuance intention to use, but did affect student engagement; the task–technology fit of MOOCs directly affected continuance intention to use and student engagement; and student engagement in MOOCs mediated between the basic psychological needs and task–technology fit, and continuance intention to use. It directly affected continuance intention to use. Implications were suggested for designing courses in MOOCs to increase student engagement for continuance intention to use.

This systematic literature review examines the barriers, strategies, and accessibility issues affecting the engagement and retention of learners with disabilities in Massive Open Online Courses (MOOCs). Employing the PRISMA procedures, this study systematically identifies and analyzes relevant literature from five prestigious databases: (a) Scopus, (b) ScienceDirect, (c) Emerald, (d) SpringerLink, and (e) EBSCOhost in order to identify (1) the common barriers experienced by learners with disabilities in MOOCs, (2) the strategies that can be employed to improve the engagement and participation of special needs students in MOOCs and (3) influence of accessibility on engagement and retention rates of learners with disabilities in MOOCs. After conducting the screening and eligibility analysis according to the pre-defined criteria, 19 studies of out 624 sources were finally selected between 2014–2024. The review underscores the necessity for comprehensive policy frameworks and institutional commitment to inclusivity. It emphasizes the adoption of universal design principles are essential in bridging the accessibility gap. These measures are pivotal in fostering an inclusive learning environment in MOOCs, significantly enhancing engagement and retention rates among learners with disabilities. The insights from this review provide a solid foundation for educators, policymakers, and platform developers to create more inclusive and supportive online learning experiences for students with disabilities.

PurposeThe purpose of this study is to propose a research model based on the stimulus–organism–response (S–O–R) model to examine whether network externality, personalization and sociability as environmental feature antecedents to learners’ learning engagement (LE) can influence their learning persistence (LP) in massive open online courses (MOOCs).Design/methodology/approachSample data for this study were collected from learners who had experience in taking MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 371 usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study proved that learners’ perceived network externality, personalization and sociability in MOOCs positively affected their cognitive LE, psychological LE and social LE elicited by MOOCs, which jointly led to their LP in MOOCs. The results support all proposed hypotheses, and the research model accounts for 76.2% of the variance in learners’ LP in MOOCs.Originality/valueThis study uses the S–O–R model as a theoretical base to construct learners’ LP in MOOCs as a series of the inner process, which is affected by network externality, personalization and sociability. It is worth noting that three psychological constructs including cognitive LE, psychological LE and social LE are used to represent learners’ organismic states of MOOCs usage. To date, hedonic/utilitarian concepts are more often adopted as organisms in previous studies using the S–O–R model, and psychological constructs have received lesser attention. Hence, this study’ contribution on the application of capturing psychological constructs for completely expounding three types of environmental features as antecedents to learners’ LP in MOOCs is well documented.

A massive open online course on the laws of thermodynamics has been designed using the 5Es (Engage, Explore, Explain, Elaborate, Evaluate) lesson planning methodology and delivered using everyday engineering examples to provide familiar contexts for both a global cohort of more than 3000 learners ranging in age from teenagers to septuagenarians in 137 different countries plus a large class of 355 university undergraduates. In addition to the structured pedagogy, the massive open online course included innovations in the use of practical exercises, that could be performed in the learner’s kitchen, and worked examples to enhance the learning experience. The massive open online course was provided in parallel with an introductory undergraduate course and as an additional learning resource for the undergraduate students. A little less than one-fifth of the undergraduates participated in the massive open online course and just over half of these responded that it would be an acceptable substitute for traditional lectures. The percentage completing the massive open online course was relatively high at 28% compared to 21% for other massive open online courses on the same platform, which is attributed to the pedagogy and strong support for social learning based on a survey of fully participating learners in the last week of the five-week course.

Purpose The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether interactivity (INT) and virtual rewards giving (VRG) as environmental stimuli to learners’ learning engagement (LE) elicited by massive open online courses (MOOCs) affect their learning persistence (LP) and learning outcome (LO) in MOOCs. This study further examines whether usage experience (UE) moderates the path relationships within the research model. Design/methodology/approach Sample data for this study were collected from learners who had experience in taking VR-based MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 313 useable questionnaires were analyzed using structural equation modeling. Findings This study proved that learners’ perceived INT and VRG in MOOCs positively influenced their psychological LE and social LE elicited by MOOCs, which concurrently expounded their LP in MOOCs, and in turn uplifted their LO in MOOCs. Besides, this study showed that learners’ UE partially moderated the path relationships in the research model. The research model respectively explains 71.8 and 56.6% of the variance (R2) in learners’ LP and LO in MOOCs. This study first reveals that learners’ perceived INT in MOOCs is the largest antecedent that can maximize their LP and LO in MOOCs via their PLE elicited by MOOCs. Next, learners’ perceived VRG in MOOCs is the strongest antecedent that can maximize their LP and LO in MOOCs via their SLE elicited by MOOCs. Originality/value This study utilizes the S-O-R model as a theoretical groundwork to construct learners’ LO in MOOCs as a series of the psychological process, which is affected by INT and VRG. Noteworthily, while the S-O-R model has been extensively employed in previous literature, little research uses the S-O-R model to explain the impacts of INT and VRG on learners’ LP and LO in MOOCs and examine whether learners’ UE can moderate the model relationships. Hence, this study enriches the research for understanding how learners value their learning gains via INT and VRG to support them in MOOCs.

Massive Open Online Courses (MOOC) allows teaching and learning for everyone. This means that people from any learning background can join any of the courses offered through MOOC platforms. Although learning materials are offered for free, learning retention and learning engagement were found to be consistently low alt-hough some MOOC are offered by well-known instructors. Many recent studies tried to understand the suitable instructional design in MOOC to improve learning en-gagement and retention. This study is an exploratory study to evaluate the potential of using learning analytics to improve instructional design in MOOC. Data were col-lected from a MOOC offered for two consequent years in a public university in Ma-laysia. The impact of learning analytics on MOOC instructional design was also dis-cussed.

Massive Open Online Courses (MOOCs) represent a transformative shift in global education, yet learner satisfaction and engagement remain precarious—often subject to tipping points caused by usability flaws, content mismatches, or insufficient interactivity. This study investigates such critical thresholds in the “Introduction to Cyber Security” MOOC offered via India’s SWAYAM platform by analysing five years of learner feedback using AI-driven sentiment analysis and Topic Modeling. Drawing on 468 qualitative reviews from Class Central, our analysis identifies content relevance, technical reliability, and interactivity as key factors correlated with learner sentiment, with recurring technical issues and limited interactivity posing potential tipping points that could trigger sudden declines in learner engagement. While 73.5% of responses are positive, neutral and negative feedback clusters around system instability, lack of advanced content, and limited peer engagement—revealing vulnerability to disengagement. This work proposes a framework for real-time, adaptive course improvement using accessible NLP tools and highlights the potential for early warning indicators of learner dissatisfaction. The findings offer actionable guidance for MOOC designers, platform developers, and policymakers to sustainably enhance quality and resilience in digital learning ecosystems through AI-based feedback systems.

MOOC(Massive Open Online Course)란 대단위로 누구나 무료로 수강할 수 있는 온라인 강좌이다. 이러한 MOOC가 기존 대학체계를 무너뜨리고, 교육의 새 지평을 열 것이라는 전망이 있었다. 그러나 MOOC는 기존의 고등교육기관을 위협할 것이라는 최초의 전망과는 다른 양상으로 진행되고 있다. 그래서 본 연구는 MOOC의 허와 실을 드러냄으로써 MOOC를 우리 고등교육의 실정에 맞게 제작하고 활용할 수 있는 논의의 시발점을 마련하고자 한다. MOOC는 기본적으로 온라인 교육이므로 기존 온라인 교육의 본질적인 문제점인 '상호작용, 감독 및 평가'의 문제를 그대로 계승할 수밖에 없다. 그리고 새로이 추가된 'Massive' 개념은 교육 현장에서 가장 민감한 부분인 강좌당 학생 수 문제를 불러일으키며, 'Open' 개념은 MOOC가 불특정 다수를 염두에 둔 강좌이므로 맞춤형 교육에 역행된다. 결론적으로 MOOC는 자기 주도적 학습 능력이 매우 탁월한 학습자들과 전통적인 온라인 고등교육기관에도 접근할 수 없는 사람들을 위한 교육 서비스로 자리매김 되고, 대학에서는 Flipped Learning의 수단으로 사용될 가능성이 매우 높다. 그러므로 향후 MOOC에서는 이 점이 고려되어 강좌의 대상에 맞게 차별화되어 개발될 필요가 있다. MOOC (Massive Open Online Course) is an online course aimed at limited participation and open access via the web. There is even the prospect that MOOC may break down the existing university system and open a new horizon of education. However, MOOC is going differently from the first prospect that it would threat the existing higher education institutions. So this study wishes to provide a starting point of discussion that we can produce and utilize MOOC to fit our situation of higher education by revealing the inherent problems of MOOC. MOOC is a basically online education, so that it cannot help inheriting the essential weakness of the existing one: the interaction, supervision and evaluation. The newly added concept 'massive' raises the problem of class size which is the most sensitive part in the field of education. The concept 'open' reverses a customized education because MOOC is a kind of video clips of a lecture for unspecific massive learners. As a conclusion, we predicts that MOOC will be positioned as a higher education service for very prominent learners in self-led learning ability and people who cannot access even traditional online higher education institutions. Also MOOC is highly likely to be used as a means of Flipped Learning in universities. Therefore, considering these points in the future, we need to develop MOOC to suit these targets.

BackgroundMassive open online courses (MOOCs) have become immensely popular in a short span of time. However, there is very little research exploring MOOCs in the discipline of health and medicine.ObjectiveWe aim to provide a review of MOOCs related to health and medicine offered by various MOOC platforms in 2013, by analyzing and comparing the various offerings, their target audience, typical length of course, and credentials offered. We also discuss opportunities and challenges presented by MOOCs in health and medicine.MethodsHealth and medicine–related MOOCs were gathered using several methods to ensure the richness and completeness of data. Identified MOOC platform websites were used to gather the lists of offerings. In parallel, these MOOC platforms were contacted to access official data on their offerings. Two MOOC aggregator sites (Class Central and MOOC List) were also consulted to gather data on MOOC offerings. Eligibility criteria were defined to concentrate on the courses that were offered in 2013 and primarily on the subject of health and medicine. All language translations in this paper were done using Google Translate.ResultsThe search identified 225 courses, of which 98 were eligible for the review. Over half (58%, 57/98) of the MOOCs considered were offered on the Coursera platform, and 94% (92/98) of all the MOOCs were offered in English. Universities offered 90 MOOCs, and the John Hopkins University offered the largest number of MOOCs (12/90). Only three MOOCs were offered by developing countries (China, West Indies, and Saudi Arabia). The duration of MOOCs varied from 3-20 weeks with an average length of 6.7 weeks. On average, MOOCs expected a participant to work on the material for 4.2 hours a week. Verified certificates were offered by 14 MOOCs, while three others offered other professional recognition.ConclusionsThe review presents evidence to suggest that MOOCs can be used as a way to provide continuous medical education. It also shows the potential of MOOCs as a means of increasing health literacy among the public.

What knowledge is available on massive open online courses in nursing and academic healthcare sciences education? A rapid review

Problem and purpose. The article analyzes the development of massive open online courses (MOOC), their structure and application in the practice of higher education, the introduction of new experience and strategy of distance learning at the Department of Physical Culture of the Siberian Federal University. The purpose of the article is to analyze the stages of the emergence and development of one of the areas of distance learning – massive open online courses (MOOC) and to analyze their application in the educational process of the University. The methodology of the research is based on the analysis of theoretical materials and research works of foreign and domestic scientists on the development of massive open online courses and the experience in the implementation of massive open online courses. Results. The article is devoted to the theory and experience of using MOОС in the world and in the educational process of the University. The authors describe the main intermediate results of the massive open online courses introduction in the educational process at the Department of Physical Culture of the Siberian Federal University. The problems, errors in the work with the MOОС and the aspects correcting the errors in future are analyzed. Conclusion. The results obtained so far allow us to conclude that the possible option of using distance learning technologies in the form of MOОС in teaching the discipline of „Physical Culture” is effective but requires additional research and further considerations.

The dominant direction in the development of online education, actively discussed by the pedagogical community, is training using massive open online courses (MOOCs). The key factor in the effectiveness of the implementation of MOOCs in the practice of educational organizations is primarily the availability of elite education. In modern conditions, which determine the priority of lifelong education (lifelong learning), it is particularly relevant to form schoolchildrens readiness for self-education, which can be facilitated by training on MOOC platforms. The broad discussion of MOOC implementation in educational practice is more concerned with university education, additional education and the system of advanced training. The use of MOOCs in school education in the publications of teachers-researchers is not considered fully enough and is mostly related to natural sciences. The paper analyzes the MOOC on the example of humanities and the features of the implementation of mixed learning models (inverted learning, autonomous group, individual trajectory) based on the use of online courses. This analysis suggests that there should be a need for more in-depth research in this area and the need to introduce elements of learning into school practice through massive open online courses. This will resolve the contradiction between the need for differentiation and individualization of training and the potential of existing unused massive open online courses.