Engagement In Massive Open Online Courses Research Articles

Learner Engagement and Demographic Influences in Brazilian Massive Open Online Courses: Aprenda Mais Platform Case Study

This paper explores the dynamics of student engagement and demographic influences in Massive Open Online Courses (MOOCs). The study analyzes multiple facets of Brazilian MOOC participation, including re-enrollment patterns, course completion rates, and the impact of demographic characteristics on learning outcomes. Using survey data and statistical analyses from the public Aprenda Mais Platform, this study reveals that MOOC learners exhibit a strong tendency toward continuous learning, with a majority re-enrolling in subsequent courses within a short timeframe. The average completion rate across courses is around 42.14%, with learners maintaining consistent academic performance. Demographic factors, notably, race/color and disability, are found to influence enrollment and completion rates, underscoring the importance of inclusive educational practices. Geographical location impacts students’ decision to enroll in and complete courses, highlighting the necessity for region-specific educational strategies. The research concludes that a diverse array of factors, including content interest, personal motivation, and demographic attributes, shape student engagement in MOOCs. These insights are vital for educators and course designers in creating effective, inclusive, and engaging online learning experiences.

Effect of video styles on learner engagement in MOOCs

ABSTRACT Video lectures in massive open online courses (MOOCs) provide an opportunity to not only deliver instructional content but also engage learners. While there are many different styles of video lectures, it is not clear how video styles affect learner engagement. This study analysed and critiqued different typologies of video styles and classified MOOC video styles on a speaker-centric to media-centric spectrum. A total of 1372 survey responses were used for data analysis. The findings indicated that the ‘media-centric’ and ‘balanced’ video styles enhanced learner engagement to varying degrees in MOOCs of different study areas. In contrast, the ‘speaker-centric’ video style offered no advantages for promoting engagement in any MOOC study area. Effect sizes ranged from .03 to .07, indicating that video styles had a small to medium effect on engagement. These findings can provide new insights into the design of video lectures for different study areas in MOOCs.

Log Data Indicators for Identifying Learner Engagement in MOOCs

Engagement during learning is crucial as the instructor and even management can see how well and understood is learner about the topic or course they are up to. As Engagement happens in Massive Open Online Courses (MOOCs), a lot of research papers discuss it and it is more interesting as the pandemic happens and most students must adapt to online learning. Log data in MOOCs have recorded engagement indicators and it is called log data indicators. However, it comes to the question of what is considered engagement in MOOCs as engagement has three parts which are affective, cognitive, and behavioral. A Systematic Literature Review (SLR) was used in this study to find out what engagement indicators for MOOCs can be captured. The result showed for this study is the indicators that can be used to analyze to explore student engagement which include the description of the indicators accordingly. From an online education perspective and improvement of the MOOCs platform, The engagement indicators are really necessary as it is part of learning. Able to identify the engagement and view the level of engagement for every participant in the course. The exploration of the engagement itself makes the instructor well knowledge of what to improve in their courses materials.

Learning engagement in massive open online courses: A systematic review

Although massive open online courses (MOOCs) increase the number of choices in higher education and enhance learning, their low completion rate remains problematic. Previous studies have shown that learning engagement is a crucial factor influencing learning success and learner retention. However, few literature reviews on learning engagement in MOOCs have been conducted, and specific data analysis methods are lacking. Moreover, the internal and external factors that affect learning engagement have not been fully elucidated. Therefore, this systematic literature review summarized articles pertaining to learning engagement in MOOCs published from 2015 to 2022. Thirty articles met the inclusion and quality assurance criteria. We found that (1) learning engagement can be measured through analysis of log, text, image, interview, and survey data; (2) measures that have been used to analyze learning engagement include self-report (e.g., the Online Learning Engagement Scale, Online Student Engagement Questionnaire, and MOOC Engagement Scale) and automatic analysis methods [e.g., convolutional neural network (CNN), bidirectional encoder representations from transformers-CNN, K-means clustering, and semantic network analysis]; and (3) factors affecting learning engagement can be classified as internal (learning satisfaction, etc.) or external (curriculum design, etc.). Future research should obtain more diverse, multimodal data pertaining to social engagement. Second, researchers should employ automatic analysis methods to improve measurement accuracy. Finally, course instructors should provide technical support (“scaffolding”) for self-regulated learning to enhance student engagement with MOOCs.

The Effects of Basic Psychological Needs, Task–Technology Fit, and Student Engagement on MOOC Learners’ Continuance Intention to Use

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.

Location in the multiverse of methods: measuring online users’ contexts

ABSTRACT Identifying online users’ contexts can help researchers understand their needs. However, the validity of different methods for identifying the location of online users has been underexplored. This paper proposes using multiple methods and examining their impact on different research questions to determine their validity. It then demonstrates this approach using data from six Massive Open Online Courses (MOOCs) by examining whether different methods produce different results regarding the relationship between SES and participation and engagement in MOOCs. We found that the choice of method impacted the estimated SES of the sample; IP geolocation placed participants in lower SES districts in comparison with their self-reported districts. Using all geolocation methods, we found that our MOOCs’ learners tended to be located in high-SES districts, but the results were inconclusive regarding the relationship between SES and course engagement. Based on this case study, we suggest that using multiple methods produces more robust findings. However, when methods diverge in findings, researchers should consider which method is most suitable for their specific purposes.

Indicators for enhancing learners’ engagement in massive open online courses: A systematic review

Massive open online courses (MOOCs) have paved a new learning path for the 21st-century world. The potential to reach a massive geographically dispersed audience is one of the major advantages of MOOCs. Moreover, they can be offered on a self-paced and self-regulated basis and have become an integral part of lifelong learning, especially in workplaces. However, one persistent problem is the lack of learners’ engagement. A harmonisation of studies providing a holistic view into aggregating indicators for enhancing learners’ engagement in MOOCs is lacking. The coronavirus pandemic has accelerated MOOC adoption, and learners’ engagement in MOOCs has become even more essential for the success of this educational innovation. We examine the existing literature to derive indicators important for enhancing learners’ engagement in MOOC learning environments. Using a systematic approach, 83 empirical studies were examined, and 10 indicators were identified as important considerations for enhancing learners’ engagement while designing MOOCs—from initiatives for individual learners to platform and instructional design perspectives. We also present a table describing these indicators and offer a structured discussion on each one. We believe the results provide guidelines for MOOC designers and instructors, educational policymakers, higher education institutions, and MOOC engagement researchers.

Linking web-based learning self-efficacy and learning engagement in MOOCs: The role of online academic hardiness

Even though Massive Open Online Courses (MOOCs) have created highly personalized and dynamic learning environments for higher education, the low completion rate has hampered their development. Nevertheless, how to engage MOOC learners in continuing to learn online remains unclear in terms of psychological mechanisms. Enlightened by the social cognitive view of learning and hardiness theory, this study investigates the mediating role of online academic hardiness (the courage that is needed to turn stressful changes from burdens into advantageous growth in online environments) between web-based learning self-efficacy (the specific beliefs that people have in their capability to complete tasks when learning online) and online learning engagement. Using validated self-reported scales, a total of 608 participants of six MOOCs courses from Taiwan were included in this study. The results of structural equation modeling indicated the significant mediating effect of commitment on behavioral, emotional and cognitive engagement in learning MOOCs. Additionally, we found that the components of web-based learning self-efficacy led to different types of engagement: general Internet-based learning self-efficacy contributes to behavioral and emotional engagement, whereas functional Internet-based learning self-efficacy contributes to emotional and cognitive engagement. The direct and indirect effects of web-based learning self-efficacy highlight its critical role in online learning engagement. Overall, our conceptual model based on the agentic view of social cognitive theory provides researchers and practitioners with a holistic picture to understand the MOOC engagement phenomenon by revealing mixed results compared to traditional distance education.

How Knowledge Stock Exchanges can increase student success in Massive Open Online Courses.

Massive Open Online Courses (MOOCs) allow lecturers to overcome spatiotemporal boundaries and reach large numbers of participants. However, the completion rates of MOOCs are relatively low, a critical obstacle to their ultimate success. Existing literature suggests that strengthening student interaction has the potential to increase student commitment. The goal of this study is to develop a novel, market-based knowledge-sharing method that fosters student engagement and interaction in MOOCs, addressing the problem of low completion rates and demonstrating how MOOC engagement can lead to greater student success. The proposed method, “Knowledge Stock Exchange” (KSX), is derived from the concept of crowd-based intelligence mechanisms for incentive-compatible information aggregation. Using a popular MOOC as the focus of our empirical study, we show that the KSX method increases student interaction as well as MOOC completion rates. Moreover, we find that KSX participation has a significant positive effect on participants’ exam grades.

Enhancing Fun Through Gamification to Improve Engagement in MOOC

Massive Open Online Courses (MOOCs), regardless of their topic, are a perfect space to generate, through virtual learning communities associated with them, very valuable resources for their participants and, in general, anyone interested in the topic covered. If in the design of these learning spaces, elements specific to games are added to them, which is known as gamification, we can try to increase the engagement of the student towards the course and, therefore, towards the community. This paper presents an experience of a MOOC of Universidad Rey Juan Carlos (Spain) with a connectivist approach. Aspects such as fun and motivation have been worked on in the design, through the application of gamified activities and the use of elements from social networks, considered as gamification, with the aim of increasing participation and engagement within a Facebook group, used as a community to support the course. We have analyzed aspects such as enjoyment and motivation, the result of which has been active participation and high engagement within the MOOC community in the form of content and especially great interaction, highlighting the existence of continuous activity once the edition of the MOOC is finished, as a consequence of a habit generated in the student.

Effect of Payment on User Engagement in MOOCs

Massive Open Online Courses (MOOCs) have the potential to democratize education by improving access. Although retention and completion rates for non-paying users have not been promising, these statistics are much brighter for users who pay to receive a certificate upon completing the course. We investigate whether paying for the certificate option can increase engagement with course content. In particular, we consider two such effects: (a) the certificate effect, which is the boost in motivation to stay engaged in order to receive the certificate; and (b) the sunk-cost effect, which arises solely because the user paid for the course. We use data from over 70 courses offered on the Coursera platform and study the engagement of individual participants at different milestones within each course. The panel nature of the data enables us to include controls for intrinsic differences between non-paying and paying users in terms of their desire to stay engaged. We find evidence that the certificate and sunk-cost effects increase user engagement by approximately 8%-9%, and 17%-20%, respectively. However, whereas the sunk-cost effect is transient and lasts only for a few weeks after payment, the certificate effect lasts until the participant reaches the grade required to be eligible to receive the certificate. We discuss the implications of our findings for how platforms and content creators may want to design course milestones and schedule the payment of course fees. Given that greater engagement tends to improve learning outcomes, our study serves as an important first step in understanding the role of prices and payment in enabling MOOCs to realize their full potential.

Learner engagement in MOOCs: Scale development and validation

AbstractThe purpose of this study is to contribute to a better understanding of the complexity of conceptualising and measuring learner engagement in Massive Open Online Courses (MOOCs). The paper develops and validates a MOOC engagement scale (MES) to measure learner engagement. The initial questionnaire items of the scale were developed by reviewing existing related literature and validated student engagement constructs. This was followed by a modified scale development process, including two focus group interviews (n = 10), an exploratory survey (n = 12), an expert review (n = 10), a pilot survey (n = 15), an item purification study (n = 590) and a construct validation study (n = 303). The final version of the scale is made up of four dimensions: behavioural engagement, cognitive engagement, emotional engagement and social engagement. The paper concludes with recommendations for how the MES can be used to assess the pattern of engagement in MOOCs and to investigate the relationship between learner engagement and other important MOOC teaching and learning factors.

Characterizing Super-Posters in a MOOC for Teachers’ Professional Development

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.

Social interaction in MOOCs: The mediating effects of immersive experience and psychological needs satisfaction

Drawing on self-determination theory (SDT), the study proposes a model to reveal the underlying mechanism by which social interaction shapes learning engagement. This study uses survey data from 318 massive open online courses (MOOCs) learners and structural equation modeling method to assess the proposed model. The results show that immersive experience and three psychological needs satisfaction (i.e., competence, relatedness, and autonomy needs) fully mediate the effect of interaction on MOOC learning engagement. Psychological needs satisfaction demonstrates different effectiveness on learning engagement. Specifically, competence need satisfaction is shown to be the strongest predictor of MOOC learning engagement, while autonomy need satisfaction has the weakest effectiveness. Further, the results demonstrate that peer learning group identification strengthens the effect of social interaction on psychological needs satisfaction. The study is among the first to specifically focus on exploring the mechanism how psychological needs satisfaction mediates the relationship between social interaction and learning engagement and has important managerial implications for MOOC platform design and operation in order to facilitate MOOC engagement.

Understanding students’ engagement in MOOCs: An integration of self‐determination theory and theory of relationship quality

AbstractAlthough Massive Open Online Courses (MOOCs) attract millions of people to enroll in their courses, the completion rate for most courses is very low. A majority of MOOCs students are not fully engaged in MOOCs, thus leading them to quit in the early stage of the courses. Therefore, it is important to investigate students’ engagement in MOOCs. Drawing on self‐determination theory and the theory of relationship quality, this study proposes a model that conceptualizes the MOOCs engagement as consisting of psychological engagement and behavioral engagement and explores the antecedents of students’ engagement in MOOCs. The research model is tested using data collected from 374 students of Chinese University MOOC. The results show that fulfillment of three basic psychological needs for autonomy, competence and relatedness have significant positive effects on intrinsic motivation, increasing students’ psychological engagement in MOOCs. Relationship quality significantly predicts students’ psychological engagement, and psychological engagement promotes behavioral engagement in MOOCs. Implications for research and practice as well as limitations of this study are discussed finally.

A semantic network model for measuring engagement and performance in online learning platforms

AbstractDue to the increasing global availability of the internet, online learning platforms such as Massive Open Online Courses (MOOCs), have become a new paradigm for distance learning in engineering education. While interactions between instructors and students are readily observable in a physical classroom environment, monitoring student engagement is challenging in MOOCs. Monitoring student engagement and measuring its impact on student performance are important for MOOC instructors, who are focused on improving the quality of their courses. The authors of this work present a semantic network model for measuring the different word associations between instructors and students in order to measure student engagement in MOOCs. Correlation analysis is then performed for identifying how student engagement in MOOCs affect student performance. Real‐world MOOC transcripts and MOOC discussion forum data are used to evaluate the effectiveness of this research.

The contribution of a MOOC to community discussions around death and dying

BackgroundAdvances in medicine have helped many to live longer lives and to be able to meet health challenges. However death rates are anticipated to increase given the ageing population and chronic disease progression. Being able to talk about death is seen to be important in normalising death as part of life and supporting preparedness for death. Massive Open Online Courses (MOOCs) provide opportunities for the community to engage in collaborative learning. A 5 week MOOC was developed covering four main topics (language and humour, representations of death, medicalisation of dying, and digital dying) aiming:To enable participants to openly and supportively discuss and learn about issues around living, death and dying,To explore the normally unheard opinions and views of Australians around death and dying, andTo determine what effect online learning and discussions offered through the MOOC had on participants’ feelings and attitudes towards death and dying.MethodsData was captured on engagement rates in the various MOOC activities. Death Attitudes were measured by five items representing the MOOC’s learning objectives and completed at enrolment and conclusion. MOOC Satisfaction was measured with six items at the end of the MOOC. Descriptive statistics were produced for each variable and Chi-Square Tests of Independence assessed the extent of the relationship between categorical variables. Socio-demographic variables were examined as predictors of the outcome variables of MOOC engagement, MOOC satisfaction, and death attitudes. Ethical approval was received from Flinders University Social and Behavioural Research Ethics Committee (Project No. 7247).ResultsOne thousand one hundred fifty six people enrolled in the Dying2Learn MOOC with 895 participating in some way. Enrolees were primarily female (92.1%). Age ranged from 16 to 84 (mean = 49.5, SD = 12.3). MOOC satisfaction scores were high. Responses to the experience of participating in the MOOC were very positive, with mean scores ranging from 4.3 to 4.6 (aligning with agreement and strong agreement to statements on the value of participating). Death Attitudes were positive at commencement but increased significantly following participation.ConclusionsThe Dying2Learn MOOC provided an environment that enabled open and supportive discussion around death and dying and influenced attitudinal change.

Clustering patterns of engagement in Massive Open Online Courses (MOOCs): the use of learning analytics to reveal student categories

Massive Open Online Courses (MOOCs) are remote courses that excel in their students’ heterogeneity and quantity. Due to the peculiarity of being massiveness, the large datasets generated by MOOC platforms require advanced tools and techniques to reveal hidden patterns for purposes of enhancing learning and educational behaviors. This publication offers a research study on using clustering as one of these techniques to portray learners’ engagement in MOOCs. It utilizes Learning Analytics techniques to investigate an offered MOOC by Graz University of Technology held for undergraduates. The authors mainly seek to classify students into appropriate categories based on their level of engagement. Clusters afterward are compared with another classical scheme (Cryer’s scheme of Elton) for further examination and comparison. The final results of this study show that extrinsic factors are not enough to make students highly committed to the MOOC, yet, adding intrinsic factors are recommended to improve future MOOCs.

Who will pass? Analyzing learner behaviors in MOOCs.

Massive open online courses (MOOCs) have recently gained worldwide attention from educational institutes. MOOCs provide a new option for learning, yet measurable learning benefits of MOOCs still need to be investigated. Collecting data of three MOOCs at Yuan Ze University (YZU), this paper intended to classify learning behaviors among 1489 students on the MOOC platform at YZU. This study further examined learning outcomes in MOOCs by different types of learners. The Ward’s hierarchical and k-means non-hierarchical clustering methods were employed to classify types of learners’ behavior while they engaged in learning activities on the MOOC platform. Three types of MOOC learners were classified—active learner, passive learner, and bystander. Active learners who submitted assignments on time and frequently watched lecture videos showed a higher completion rate and a better grade in the course. MOOC learners who participated in online discussion forum reported a higher rate of passing the course and a better score than those inactive classmates. The finding of this study suggested that the first 2 weeks was a critical point of time to retain students in MOOCs. MOOC instructors need to carefully design course and detect risk behaviors of students in early of the classes to prevent students from dropping out of the course. The feature design of discussion forum is to provide peer interaction and facilitate online learning. Our results suggested that timely feedback by instructors or facilitators on discussion forum could enhance students’ engagement in MOOCs.

Exploring the communication preferences of MOOC learners and the value of preference-based groups: Is grouping enough?

Approximately 10 % of learners complete Massive Open Online Courses (MOOCs); the absence of peer and professor support contributes to retention issues. MOOC leaders often form groups to supplement in-course forums and Q&A sessions, and students participating in groups find them valuable. Instructors want to assist in the formation of groups, creating multi-national collaborations, an asset possible in MOOCs that is generally sacrificed when students form their own groups. Little is known about how people from various cultures prefer to communicate with each other, or about the value of groups formed by MOOC leaders. To understand MOOC leaners’ grouping preferences, we administered a pre-course online survey to volunteers registered in the “Creativity, Innovation, and Change” MOOC offered by Penn State University via Coursera and assigned volunteers to groups based on their preferences. We also examined whether assigning learners to groups based on their preferences enhanced their performance or completion of the course. This paper reports MOOC learners’ preferences for different modes of online communication with group members (asynchronous text posts, synchronous text chats, or synchronous video and audio). Statistically significant relationships were found between learners’ preferred communication modes and their level of English proficiency, gender, level of education, and age. Although placing learners in groups based on their preferences and introducing them to each other did not improve course performance or completion, our findings on preferred communication modes, combined with more formal instruction of how to function as group members may prove to enhance learning and engagement in MOOCs.