MOOC learners’ demographics, self-regulated learning strategy, perceived learning and satisfaction: A structural equation modeling approach

Massive Open Online Courses (MOOCs) became very popular during the last years leading to an increasing global debate about their quality. To address the quality issues, several research surveys and instruments were developed to analyse the current status of MOOCs and to examine the different perspectives of learning with MOOC from core MOOC stakeholders. Based on a literature review and analysis of existing quality approaches and indicators for MOOCs, the Global MOOC Quality Survey was designed and conducted (n=267). Final objective is the development of the Quality Reference Framework (QRF) with quality indicators and tools in close collaboration with all interested stakeholders worldwide. This paper presents first results from the Global MOOC Quality survey relating to the overall experiences with MOOCs and their offered four interaction types: learner-facilitator (LF), learner-resource (LR), learner-learner (LL) and group-group (GG). There was a very high significant relationship (p<.001) between the learners' MOOC experience and the three interaction types LF, LR and LL and a significant relationship (p=.026) for the fourth interaction type GG. There was not a significant relationship between the designers' MOOC experience and all four interaction types. Comparing the different perspectives of learners and designers, our analysis presents significant differences in MOOC learners' and designers' intentions and experiences. Hence, it can be questioned whether MOOC designers are currently understanding and meeting the interests and demands of the MOOC learners.

Massive Open Online Courses (MOOCs) have been integrated into face-to-face language modules to enhance the educational experience of students. MOOCs appear to offer language learning opportunities as well as challenging the self-regulated learning (SRL) behaviour of students. This paper presents a work in progress with regards to the literature review of my PhD, which investigates SRL in face-to-face language modules using MOOCs. It discusses SRL as a requirement for engaging with these courses and analyses the way studies have integrated MOOCs into instructional language modules. This paper concludes by highlighting the need for understanding students’ SRL behaviour when engaging with MOOCs as part of their language modules.

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.

Massive open online courses (MOOCs) require registered learners to be autonomous in their learning. Nevertheless, prior research studies showed that many learners lack the necessary self-regulated learning (SRL) skills to succeed in MOOCs. This research study aimed to gain insights into the relationships that exist between SRL and background information from MOOC learners. To this end, a series of three MOOCs on computer programming offered through edX were used to collect self-reported data from learners using an adaptation of the Motivated Strategies for Learning Questionnaire. Results show significant differences in general learning strategies and motivation by continent, prior computing experience and percentage of completed MOOCs. Men reported higher motivation than women, whereas pre-university learners needed further guidance to improve their learning strategies.

Aim/Purpose: This study aims to develop a theoretical framework for enhancing students’ higher-order thinking skills (HOTS) by integrating massive open online courses (MOOCs) with gamification elements. Background: There is a growing demand to develop students’ innovative thinking abilities through MOOCs, focusing on higher-order thinking skills (HOTS), which are essential for 21st-century challenges. While gamification has shown potential in enhancing HOTS, its integration within MOOCs to improve these skills remains underexplored. Enhancing students’ HOTS through MOOCs combined with gamification is crucial for developing advanced skills like analysis, evaluation, and creativity. Therefore, there is an urgent need for a robust theoretical framework that effectively merges MOOCs and gamification to enhance students’ HOTS. Methodology: This research used a qualitative research approach employing critical analysis techniques. The research procedures were guided by the SALSA framework. A total of 19 articles from the SCOPUS and Google Scholar databases were selected based on specific criteria: articles published between 2013-2023, articles with keywords such as MOOCs, gamification, higher-order thinking, or engagement, and articles written in English. Thematic analysis was conducted to identify common themes in the selected articles. The proposed framework was developed by drawing upon well-established theories in the fields of educational technology, online learning, collaborative learning, connectivism, student engagement, and Bloom’s taxonomy. Contribution: This study not only synthesizes existing research on MOOCs but also presents a holistic and integrated framework for leveraging learning theories, gamification elements, student engagement dimensions, and HOTS to enhance the effectiveness of MOOC-based education. The proposed framework aims to provide researchers and educators with a comprehensive model for integrating gamification elements into MOOCs to enhance students’ higher-order thinking skills. By utilizing this framework, educators can design more engaging and effective online courses, while researchers can further investigate the impact of gamification on learning outcomes and student engagement. Findings: This study proposes a framework that integrates three main components: connectivism, online collaborative learning, and gamification principles. Implementing these components in the MOOC learning environment aims to enhance digital higher-order thinking as proposed by Churches and improve students' feelings and perceptions towards MOOC learning. Recommendations for Practitioners: By recognizing the unique challenges of maintaining students’ attention in the context of MOOC learning, practitioners can incorporate gamification elements into MOOC learning environments to enhance students’ HOTS. Recommendation for Researchers: Researchers can further explore the understanding and measurement of the dynamics of interactions and engagement within MOOCs. Additionally, they should aim to identify which gamification elements effectively capture students’ attention and contribute to their overall engagement. Impact on Society: By focusing on HOTS, especially through gamification, society can anticipate a generation of individuals with improved critical thinking, problem-solving, and innovative capabilities. Furthermore, the implementation of connectivism in MOOCs can promote a global exchange of knowledge, resulting in diverse perspectives and a shared pool of information. This, in turn, will contribute to a more interconnected and collaborative world to address complex challenges. Future Research: The future direction of research in MOOC learning contexts should prioritize guaranteeing and fostering student engagement. It should also involve exploring the potential of gamification within MOOCs and refining instructional designs to specifically enhance higher-order thinking skills. By addressing these critical aspects, researchers can contribute to the ongoing evolution of online education and ensure its effectiveness and relevance in the ever-changing landscape of digital learning.

Self-Regulated Learning (SRL) is a field in educational psychology that as attracted tremendous research studies from various communities including ICTs. Recent studies and meta-analysis have greatly contributed to the domain knowledge that the use SRL strategies boost academic performance for learners. Despite these developments in SRL, our understanding on the tools and instruments to measure SRL in online learning environments is limited as the use of traditional tools developed for face-to-face classroom settings are still used to measure SRL on e-learning systems. Additionally, most of these studies focus on SRL on Massive Open Online Course (MOOC) environments and only analyse SRL strategies with limited attention to the scaffolds or interventions employed to stimulate growth of SRL skills in learners. The modern Learning Management Systems (LMS) such as Moodle allow storage of datasets on student activities. Consequently, it is possible to use Educational Data Mining (EDM) to extract learner patterns which can be used to support SRL and explore how SRL strategies change over time and inform the instructor. In view of this, the research examines the current SRL measurement and promotion tools for e-learning environments and proposes a conceptual model grounded on EDM for implementation as a solution to measuring and promoting SRL strategies for learners within LMS.

This chapter reviews the concept of seamless learning for Massive Open Online Courses (MOOC) based on the distillation of key factors from papers discussing and describing the Mobile Seamless Learning (MSL) concept. The MSL concept was used as a starting point to explore how MOOC could be prepared for seamless learning and to explore future research options. There is a vast area of research to be explored related to seamless learning in MOOC. The authors belief that some of the challenges faced by MOOC, such as “dropout” rates, redefining learning activities to fit diversity of contexts, self-directed learning, collaborative content artifact creation, the mobility of the adult learners, and the “dip-in, jump-out” aspect of participation, can be countered by researching and suggesting seamless learning designs and guidelines that fit both the adult learners and the MOOC realities. Investigating all the elements, challenges and benefits for providing seamless learning in MOOC environments will contribute to the body of knowledge of contemporary online learning.

Methods for teaching large numbers of people over the Internet have become a popular topic as new technologies for communication and teaching large audiences have emerged in recent years. Many educational institutions are turning toward MOOCs, or massive open online courses, as a technology for delivery of learning content. In this article, we describe a brief history of MOOCs and the technologies that support learning in MOOCs. We also illustrate what uniquely defines MOOCs in comparison to other forms of distance or online learning. We conclude with a discussion on the implications for teaching and learning with MOOCs and valuable steps for MOOC design, implementation, and future research.

Instead of measuring success in Massive Open Online Courses (MOOCs) based on certification and completion-rates, researchers started to define success with alternative metrics recently, for example by evaluating the intention-behavior gap and goal achievement. Especially self-regulated and goal-oriented learning have been identified as critical skills to be successful in online learning environments with low guidance like MOOCs, but technical support is rare. Therefore, this paper examines the current technical capabilities and limitations of goal-oriented learning in MOOCs. An observational study to explore how well learners in five MOOCs achieved their initial learning objectives was conducted, and the results are compared with similar studies. Afterwards, a concept with a focus on technical feasibility and automation outlines how personalized learning objectives can be supported and implemented on a MOOC platform.

Massive Open Online Courses (MOOCs) have become a popular tool for worldwide learners. However, a lack of emotional interaction and support is an important reason for learners to abandon their learning and eventually results in poor learning performance. This study applied an integrative framework of achievement emotions to uncover their holistic influence on students’ learning by analyzing more than 400,000 forum posts from 13 MOOCs. Six machine-learning models were first built to automatically identify achievement emotions, including K-Nearest Neighbor, Logistic Regression, Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machines. Results showed that Random Forest performed the best with a kappa of 0.83 and an ROC_AUC of 0.97. Then, multilevel modeling with the “Stepwise Build-up” strategy was used to quantify the effect of achievement emotions on students’ academic performance. Results showed that different achievement emotions influenced students’ learning differently. These findings allow MOOC platforms and instructors to provide relevant emotional feedback to students automatically or manually, thereby improving their learning in MOOCs.

BackgroundLearners in a given massive open online course (MOOC) are usually provided with the same learning materials, guided by the same syllabus, and assessed in the same format. This “one‐size‐fits‐all” approach constrains learners' ability to reap the optimal benefits from online learning.ObjectivesThis study aims to characterize learners' differences in MOOC learning. Specifically, it examines how learners might vary in their enrolment motivation and the development of continuance intention to learn in a MOOC because of their gender and employment status.MethodsData were collected via a questionnaire survey. Quantitative and qualitative methods were used to analyse data from 664 learners in a Chinese MOOC.Results and ConclusionThe research revealed significant differences in learners' enrolment motivation across groups defined by employment status, but not for gender groups. Learner groups defined by gender and employment status experienced variant psychological processes when deciding to continue to learn in the MOOC.Major TakeawaysWorking adults stressed the instrumental values derived from MOOC learning; therefore, it is vital to design and integrate additional features into the MOOC to satisfy their needs. Besides, it would be critical to understand female learners' and working adults' expectations of MOOC learning, as they are more sensitive to confirmation in determining their attitudes toward learning in a MOOC. A short pre‐course survey of learners' expectations would serve the purpose.

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.

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.

Design for collaborative learning in Massive Open Online Courses (MOOCs) is considered more challenging compared to another context, while the benefits are huge for learners to collaborate in MOOC, especially connectivism MOOC (cMOOC), where learning is to connect specialized nodes (learners) or information sources. This study based on a cMOOC with 2791 participants, aimed to build a platform for conversation and problem-solving among researchers and practitioners, in the field of educational technology. And this paper investigated the learning process of a high-performance collaborative learning group in a cMOOC by analyzing their blogs, artifacts to record and report learning formatively. We discovered that the group demonstrated strategies including keeping the balance between student agency and problem quality, building up trust and commitment, keeping an artifact to manifest thinking, and making each individual recognized, which could help inform future design for collaborative learning in MOOC.

&lt;p&gt;Despite the increase in massive open online courses (MOOCs), evidence about the pedagogy of learning in MOOCs remains limited. This paper reports on an investigation into the pedagogy in one MOOC - Oxford Brookes University’s ‘First Steps in Learning and Teaching in Higher Education’ MOOC (FSLT12).&lt;/p&gt;&lt;p&gt;FSLT12 was an open and free professional development opportunity for people moving into HE teaching. It was a small course (200 participants registered from 24 countries) which was focused on introducing HE teaching skills, and, uniquely, to deliberately integrate open academic practice as a vital part of professional development for HE teachers. A qualitative, case-study approach was used in the research, based on surveys, interviews, and social media, to provide evidence about how people learned in this course and consider wider implications for teaching and learning in higher education.&lt;/p&gt;&lt;p&gt;The evidence shows that participants who completed the course were able to learn autonomously and navigate the distributed platforms and environments. The most challenging issues were acceptance of open academic practice and difficulty in establishing an academic identity in an unpredictable virtual environment. An interesting and significant feature of the course was the support for learners from a number of MOOC ‘veterans’ who served as role models and guides for less experienced MOOC learners.&lt;/p&gt;&lt;p&gt;The research shows that small task-oriented MOOCs can effectively support professional development of open academic practice.&lt;/p&gt;