Massive Open Online Courses Providers Research Articles

Navigating the Learning Landscape: Social Cognition and Task-Technology Fit as Predictors for MOOCs Continuance Intention by Sales Professionals

Massive open online courses (MOOCs) have gained popularity among sales professionals who use them for self-directed learning and upskilling. However, research related to their intentions to continue learning is scarce. Drawing from the social cognition theory, this research aimed to address this gap by investigating the role of task-technology fit, self-development, and social recognition in sales professionals’ continued use of MOOCs. The study hinged on empirical research and used a survey to collect data from 366 sales professionals. The results suggest that task-technology fit, self-development, and social recognition play a significant role in sales professionals’ continued use of MOOCs. The study has practical implications for organizations promoting employee learning and development. The findings provide valuable information for MOOC designers and providers to develop more effective courses that meet the needs of sales professionals.

Massive open online courses learners' continuance intention: shaping a roadmap to micro-credentials

PurposeThis study intends to investigate the determinants of learners' continuance intention to use massive open online courses (MOOCs) for personal or professional development.Design/methodology/approachThis study employed quantitative research design. The respondents were individual learners from six selected universities in China who used MOOCs for continuous learning. A purposive sampling technique was employed to obtain 270 valid samples. Data were analyzed and analytical outputs were produced using the techniques of Partial Least Squares Structural Equation Modeling and Importance-Performance Matrix.FindingsExpectation confirmation was found to have a positive relationship with perceived usefulness, flow experience, learning self-efficacy and satisfaction with MOOCs. Perceived usefulness, flow experience and leaning self-efficacy were also found to have a positive relationship with MOOC satisfaction. In addition, perceived usefulness, flow experience, learning self-efficacy and MOOC satisfaction had a positive impact on continuance usage intention.Originality/valueThe outcomes of the study can serve as a practical reference for MOOC providers and decision-makers to develop relevant strategies to increase the course completion rates.

Students’ Perception Towards Learning Massive Open Online Courses on Coursera Platform: Benefits and Barriers

The advent of Massive Open Online Courses (MOOCs) has opened up new possibilities for students to access high-quality educational content worldwide faster and easier. Among these online learning platforms, Coursera is the most popular MOOC provider, with over a thousand courses in various fields of study. This study investigated the perception of students towards learning MOOCs on the Coursera platform, examining the benefits and barriers that influence their engagement in this mode of learning. The data were collected from a private university in Vietnam via online surveys with 200 MOOCS participants using a 7-point Likert scale questionnaire and semi-structured interviews with 30 participants. The findings indicated positive opinions of university students on the Coursera platform, including access to diverse topics, high-quality learning materials, a high level of academic support, flexible learning, and the ability to learn at their own pace. The findings revealed a number of benefits of learning Coursera MOOCs, such as earning high-quality certifications, improving knowledge and skills, enhancing personal development, and having chances for higher education and career advancement. In addition, the study identified some barriers to their learning, for example, a lack of interaction with instructors, an overload of information, a lack of motivation and concentration, and difficulties with study language and time management.

Reinforced Explainable Knowledge Concept Recommendation in MOOCs

In this article, we study knowledge concept recommendation in Massive Open Online Courses (MOOCs) in an explainable manner. Knowledge concepts, composing course units (e.g., videos) in MOOCs, refer to topics and skills that students are expected to master. Compared to traditional course recommendation in MOOCs, knowledge concepts recommendation has drawn more attention because students’ interests over knowledge concepts can better revealstudents’ real intention in a more refined granularity. However, there are three unique challenges in knowledge concept recommendation: (1) How to design an appropriate data structure to capture complex relationships between knowledge concepts, course units, and other participants (e.g., students, teachers)? (2) How to model interactions between students and knowledge concepts? (3) How to make explainable recommendation results to students? To tackle these challenges, we formulate the knowledge concept recommendation as a reinforcement learning task integrated with MOOC knowledge graph (KG). Specifically, we first construct MOOC KG as the environment to capture all the relationships and behavioral histories by considering all the entities (e.g., students, teachers, videos, courses, and knowledge concepts) on the MOOC provider. Then, to model the interactions between students and knowledge concepts, we train an agent to mimic students’ learning behavioral patterns facing the complex environment. Moreover, to provide explainable recommendation results, we generate recommended knowledge concepts in the format of a path from MOOC KG to indicate semantic reasons. Finally, we conduct extensive experiments on a real-world MOOC dataset to demonstrate the effectiveness of our proposed method.

The mysterious adventures of Detective Duke: How storified programming MOOCs support learners in achieving their learning goals

About 15 years ago, the first Massive Open Online Courses (MOOCs) appeared and revolutionized online education with more interactive and engaging course designs. Yet, keeping learners motivated and ensuring high satisfaction is one of the challenges today's course designers face. Therefore, many MOOC providers employed gamification elements that only boost extrinsic motivation briefly and are limited to platform support. In this article, we introduce and evaluate a gameful learning design we used in several iterations on computer science education courses. For each of the courses on the fundamentals of the Java programming language, we developed a self-contained, continuous story that accompanies learners through their learning journey and helps visualize key concepts. Furthermore, we share our approach to creating the surrounding story in our MOOCs and provide a guideline for educators to develop their own stories. Our data and the long-term evaluation spanning over four Java courses between 2017 and 2021 indicates the openness of learners toward storified programming courses in general and highlights those elements that had the highest impact. While only a few learners did not like the story at all, most learners consumed the additional story elements we provided. However, learners' interest in influencing the story through majority voting was negligible and did not show a considerable positive impact, so we continued with a fixed story instead. We did not find evidence that learners just participated in the narrative because they worked on all materials. Instead, for 10–16% of learners, the story was their main course motivation. We also investigated differences in the presentation format and concluded that several longer audio-book style videos were most preferred by learners in comparison to animated videos or different textual formats. Surprisingly, the availability of a coherent story embedding examples and providing a context for the practical programming exercises also led to a slightly higher ranking in the perceived quality of the learning material (by 4%). With our research in the context of storified MOOCs, we advance gameful learning designs, foster learner engagement and satisfaction in online courses, and help educators ease knowledge transfer for their learners.

A Systematic Literature Review on Recommender Systems for MOOCs

In recent years, MOOCs (Massive Open Online Courses) have become popular and the online learning resources are increasing, they are an offered courses by schools and universities, which are accessible to everyone and free of charge on the internet, they offer the possibility to teach a very group of students, in the same course, at the same time, even if they are not in the same location. There are many MOOCs platforms with different characteristics, they contain a huge amount of data, so the learner does not know which course to take and can choose irrelevant MOOCs. Therefore, he will waste the time and also the motivation. Recommender systems give a solution to this problem, they suggest learning resources to learners according to their interests and needs, so learner will be satisfied because he finds an appropriate course. In this paper, we give a systematic literature review of MOOCs recommender systems, based on published papers in the past ten years, between 2012 and 2022. We have selected 123 papers from five databases, IEEE Xplore, Springer Link, Science Direct, Google Scholar and ACM Library. We have divided the data analysis in two parts, the quantitative analysis, and the qualitative analysis. In the quantitative analysis, we have studied first the evolution of papers by year and the distribution of papers on databases by type. Then, in the qualitative analysis, we have based principally on the distribution of papers by the existed areas in MOOCs. We have found that there are six main fields, course recommendation, peer recommender, MOOC provider, video recommendation, learning activities and OER, paid activities recommender system and other papers in various types. A high number of articles have been published in the field of courses, which confirms that this domain is very important and crucial for learners.

Formation mechanism of popular courses on MOOC platforms: A configurational approach

Popular courses are representative of high-quality courses on MOOC (Massive Open Online Course) platforms. However, current research on the formation mechanism of popular courses is rare. Thus, a fuzzy-set qualitative comparative analysis (fsQCA) is adopted to explore configurations of MOOC quality elements for popular courses on MOOC platforms. This study selects courses on the Coursera platform as the research object. Unique datasets of 272 observations and 261 observations before and after the outbreak of pandemic, respectively, are used to investigate for a better understanding of the role of quality elements in forming popular courses. Three key findings are revealed. First, the configurations for MOOC popular courses differ from those of nonpopular courses, suggesting an asymmetric view of causality that underpins MOOC quality. Second, parsimonious configurations emergent from complex interactions among eight MOOC quality elements which are selected from three aspects of MOOC course arrangement, MOOC teaching faculty arrangement, and MOOC learner reviews, suggesting causality of equifinality that produces a popular course both before and after the outbreak of pandemic. Notably, the role of the professional title of MOOCs teachers becomes more important for forming popular courses after COVID-19. Third, although the number of MOOC teachers appears as a peripheral element along with the number of long reviews as a core element in all configurations for popular courses, they need the presence of other quality elements to form popular courses, suggesting a conjunction between quality elements. All findings provide implications not only for MOOC providers to regard popular courses as a result of configurations of MOOCs quality elements, but also for further research on fsQCA in course quality on MOOC platforms.

Providing recommendations for communities of learners in MOOCs ecosystems

Massive Open Online Courses (MOOCs) have been widely disseminated due to the arrival of Web 2.0. However, the growth of MOOCs brings some difficulties for students in choosing suitable courses in these ecosystems. In recent years, some recommendation systems emerged to solve this problem but remain limited since they do not identify the student’s prior knowledge broadly or the student’s goals. To overcome this limitation, this work proposes the Fragmented Recommendation for MOOCs Ecosystems (FReME), a recommendation system to suggest parts of courses from multiple providers (i.e., Khan Academy, Udemy, and edX). FReME is based on the student profile and on the MOOCs ecosystems perspective to balance the ecological environment and strengthen interactions. Moreover, we differ from the current recommendation systems since our method identifies and reduces the students’ knowledge gap optimizing the learning process. Experimental results conducted with a dataset integrating 3 MOOCs providers and 19 students demonstrated that the implemented techniques are more consistent than other approaches. Finally, it was verified through precision, utility, novelty, and confidence that our recommendations are 62,24% accurate, 68.89% useful, 72.81% reliable, and present new content in 99.12% of cases. These results validate that FReME supports students in reducing their knowledge gap.

Migrating Vs. Decentralizing MOOC-based e-content to Teaching MA Language and Communication Students

Never before has education been more tech-oriented, cloud-based, and online-driven, especially with this new pandemic-altered educational environment. However, new regulations worldwide limit physical interaction inside the bounds of educational institutions, which pushed Algerian university teachers to operate mainly online under unsuitable conditions. Therefore, our prime objective is to devise a MOOC-based teaching modal that primarily palliates the current dire problems regarding students’ equity. One of the solutions proposed in this paper is two equitable, to some extent, tech-enabled modalities of instruction that leverage the available first-rate Massive Open Online Courses (MOOC) e-content to teach Master of Arts (MA) students: language and communication students of English department at Mostaganem University in Algeria. There were two online groups, the first one regards migrating to the MOOC itself and letting students operate on the MOOC provider. The second e-group decentralizes the e-content to a closed Facebook group where students can access the e-pedagogical materials directly from the social-media-mediated landscape. To this end, a pedagogical action research based on the comparative approach is used to undertake this study that comprehended 44 students to compare the two e-groups through different working situations. Findings revealed the difference between the two e-modes of teaching. They presented a framework enabling instructors to choose which one to leverage according to students’ digital skills and access to internet bandwidth, thus serving as a guideline for any instructor wishing to participate in such an educational endeavor. Finally, implications of these two technologized modes of instruction on the teaching profession overall are set forth.

Large scale analytics of global and regional MOOC providers: Differences in learners’ demographics, preferences, and perceptions

Massive Open Online Courses (MOOCs) remarkably attracted global media attention, but the spotlight has been concentrated on a handful of English-language providers. While Coursera, edX, Udacity, and FutureLearn received most of the attention and scrutiny, an entirely new ecosystem of local MOOC providers was growing in parallel. This ecosystem is harder to study than the major players: they are spread around the world, have less staff devoted to maintaining research data, and operate in multiple languages with university and corporate regional partners. To better understand how online learning opportunities are expanding through this regional MOOC ecosystem, we created a research partnership among 15 different MOOC providers from nine countries. We gathered data from over eight million learners in six thousand MOOCs, and we conducted a large-scale survey with more than 10 thousand participants. From our analysis, we argue that these regional providers may be better positioned to meet the goals of expanding access to higher education in their regions than the better-known global providers. To make this claim we highlight three trends: first, regional providers attract a larger local population with more inclusive demographic profiles; second, students predominantly choose their courses based on topical interest, and regional providers do a better job at catering to those needs; and third, many students feel more at ease learning from institutions they already know and have references from. Our work raises the importance of local education in the global MOOC ecosystem, while calling for additional research and conversations across the diversity of MOOC providers.

Revealing the regulation of learning strategies of MOOC retakers: A learning analytic study

Massive Open Online Courses (MOOCs) have already shown a great potential to be used as an alternative model for teacher professional development (TPD). Not only do MOOCs offer relevant content and activities, but they also provide opportunities for strengthening the skills for self-regulated learning of teachers as life-long learners. In this study, we focused on a unique sub-group of MOOC learners – retakers who take the same TPD MOOC multiple times. In the empirical study reported in this paper, we examined what learning strategies they choose when taking a TPD MOOC and the extent to which they are able to adapt their learning strategies to improve their performance in the subsequent attempts. By using learning analytic methods, we detected five learning strategies and eight major forms of strategy change adapted by MOOC retakers. We found that two strategy changes (from Content-Oriented Strategy to Intensive-Thorough Strategy or Balanced Strategy) with associated with significantly higher performance in the subsequent attempts compared to no change in strategy. Our findings have implications for MOOC instructors and providers about the ways they can support MOOC retakers. Our findings also suggest that MOOCs are not only valuable TPD resources for teachers, but they also have unique opportunities for strengthening the self-regulation skills of teacher learners as the “by-products of learning”.

The impact of MOOC aggregators on the development of language education

Due to a large number of massive open online courses (MOOC), it becomes more and more difficult for the users to determine which course best suits their needs. To improve the efficiency of course selection, a place is needed where they can visually compare the offers of different MOOC providers. The article aims to identify the number and characteristics of massive open online courses for language learning (MOOLC) using MOOC aggregators and to trace their impact on the development of language education. The article presents different approaches to such concepts as MOOC, MOOLC, MOOC platform, MOOC aggregator and MOOC provider. The article determines MOOC aggregators, which would allow identifying the number and characteristics of MOOLC, and examines the possibilities of some MOOC platforms, which offer courses for English language learning, basing on the selected criteria for evaluation of the existing MOOC platforms. The author concludes that nowadays, the ideal MOOC platform, which could offer the necessary conditions for creating an ideal MOOLC, does not exist.

Customer-Oriented Aggregators of Massive Open Online Courses: Opportunities and Prospects

In recent years, the number of online courses known as massive open online courses (MOOC) has increased significantly. Such courses are available on online providers’ sites, such as edX and Coursera. As a result, there is a notable reduction of clarity in terms of various course offerings, and this causes a need to change the MOOC description schemes to help inform potential applicants. The article is aimed at identifying the capabilities of customer-oriented MOOC aggregators and the prospects for their further improvement. The article presents approaches to the concept of customer focus, based on which the definition of a customer-oriented aggregator is formulated. The article analyses course descriptions used by MOOC providers and aggregators for their potential students. Based on this analysis, the authors develop a set of categories describing MOOC, used for the creation of a new MOOC description according to the customer-oriented criteria. The authors conclude that the optimal descriptive MOOC scheme on the MOOC aggregator should satisfy both the academic environment and the customer-oriented criteria that correspond to students’ interests when choosing a MOOC.

Analisa Pemilihan Kursus Daring Pada Karyawan PT. Gramedia Asri Media dengan Metode Analytical Hierarchy Process

PT. Gramedia Asri Media established the Gramedia Digital Technical Department which implements remote work so that it is possible for employees working in various places to stay connected and collaborate. However, with the limited space and time for employees and the difficulty of meeting at one time to get various trainings, then MOOC is expected to be the answer to the need for workers to get proper training and in accordance with the technical capabilities required by the company. MOOC (Massive Open Online Courses) is an example of technological development of the learning process that offers flexibility in time and place. Currently, there are many alternative MOOC providers with various criteria, so it is necessary to choose the one that is most suitable for its users. One method of making decisions based on many criteria is AHP (Analytical Hierarchy Process). This study uses 5 criteria, namely Teacher Credibility, Certificate, Price, Course Topics and Course Time and 4 alternatives, namely Coursera, EdX, Udemy and Codecademy, where the course topic is obtained as the priority with a priority weight of 0.2289 then followed by Course time with a priority weight of 0.2238 Price with priority weight 0.2133, Credibility of teachers with priority weight 0.1833, Certificate with priority weight 0.1508. While the alternative with the priority is Udemy with a priority weight of 0.4379 followed by Coursera with a priority weight of 0.2234, Codecademy with a priority weight of 0.1989 and lastly Edx with a priority weight of 0.1723.

A qualitative study to understand the perspectives of MOOC providers on accessibility

Massive open online courses (MOOCs) are widely available and have become a common option for learners. However, their full potential cannot be realised if they are not accessible to all learners, including those with disabilities. It is, therefore, important to understand the different stakeholders and their requirements and perspectives in designing accessible MOOCs. This research investigated the perspectives of MOOC providers on MOOC learners who have accessibility needs and the processes used to manage accessibility and MOOCs in their individual organisations. In this paper, we report the results of a study using thematic analysis, which involved 26 semi-structured interviews with MOOC providers and focused on MOOC accessibility. The results show that, while MOOC providers are aware of learners with accessibility needs who are participating in MOOCs, they prioritise legislation over learners’ accessibility preferences. MOOC providers consider the technology of the platform itself creates barriers and are aware of the limitations for learners in finding help, reporting accessibility barriers and obtaining feedback, when participating in MOOCs.
 Implications for policy and practice:
 
 Course providers should acknowledge MOOC design is being guided by legal requirements. That involves uncertainty to who is the responsible to deliver accessible MOOCs.
 Platform providers need to consider the lack of information about their learners makes it difficult to design educational resources that consider different target groups and provide personalisation.
 Learners can find MOOCs helpful for continuing professional development and lifelong learning. MOOCs are attractive due to their low-cost and self-regulated learning.

‘We Are a Global Community’: Communicating Knowledge through Moocs and Teacher Training Platforms

A socio-rhetorical discourse community consists of a group of people who come together to pursue objectives that predate those of socialization and solidarity, and who aim to develop and maintain their own discoursal characteristics. We have examined MOOCs (Massive Open Online courses) and teacher training educational platforms in order to ascertain whether and to what extent they may be identified as networked learning tools and discourse communities characterized by a commonality of goals, mechanisms and procedures of intercommunication, exchange of knowledge, information, as well as specialized genres and their terminology. MOOCs and learning platforms have dramatically changed the way people learn. Starting from ongoing research, we analyze the metadiscoursal features of an ad hoc corpus of online filmed lectures drawn from two MOOC providers (FutureLearn and Coursera). We look at both interactive and interactional resources (to guide the listener through the texts and to involve the listener in the subject), in order to discover how these features are used to control, evaluate and negotiate the communicative goals and impact of the ongoing exchanges. The quantitative and qualitative analysis shows a significant use of metadiscourse markers in the video lectures with a higher frequency of interactional features such as self-mentions, engagement markers, hedges and boosters, rather than interactive ones. These commentaries in the lectures signal the instructors’ attitudes towards the texts and their listeners. Additionally, they were found to perform a rhetorical function since they persuasively reinforce the instructors’ attitude and stance. Thus, their use engages the participants as members of a digital community, where commitment, dedication, and common goals seem to be fundamental features.

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

INVESTIGATING INHIBITING FACTORS AFFECTING MOOCS ADOPTION AMONG TEACHERS IN HIGHER EDUCATION INSTITUTIONS OF INDIA

Massive Open Online Courses (MOOCs) has the potential to eradicate the digital divide and endorse education globally among the learners in the education industry. Through MOOCs platforms, teachers can upgrade their knowledge skills and abilities in their respective fields. The present study aims to identify the inhibiting factors underlying the adoption of MOOCs by teachers employed in higher education institutions. The research has employed an Interpretative Phenomenological Analysis of qualitative research methodology. In this research, teachers from the identified Universities of Uttarakhand, India are selected as the respondent to investigate the factors affecting the adoption of MOOCs. Findings reveal that technological barriers, financial barriers, and lack of awareness act as inhibiting factors in adopting MOOCs by teachers of HEI. This study also contributes to the literature by assessing the factors influencing teachers’ intention to adopt Massive Open Online Courses for learning. Through this paper, the three stakeholders of MOOCs, that is teachers, HEI and MOOC provider are suggested measures that will enhance the support and acceptability of the online courses.

Understanding learners' completion intention of massive open online courses (MOOCs): role of personality traits and personal innovativeness

PurposeThe present study investigates the influence of five personality traits based on the Big Five model, i.e. extraversion, neuroticism, conscientiousness, agreeableness and openness to experience and personal innovativeness on learners' intention to complete MOOCs.Design/methodology/approachThe proposed model was empirically tested using cross-sectional design. The primary data were gathered through a survey of 515 students at five higher educational institutions in the National Capital Region of Delhi, India. Structural equation modelling was used to test the hypothesized relationships in the proposed model.FindingsThe study has found significant associations between the personality traits, personal innovativeness and MOOC completion intention. The findings indicate that extraversion, conscientiousness, agreeableness, openness to experience and personal innovativeness have significant positive effects whereas neuroticism has no significant effect on MOOCs continuance intention. Personal innovativeness has been found to mediate the relationships between all the personality traits and MOOCs completion intention of learners.Practical implicationsOur findings can potentially address the issue of drop-out rates of MOOCs in developing countries such as India. The findings of the study are helpful for MOOCs providers and other stakeholders. The MOOC developers should develop courses with wide scope so as to accommodate learners with different personality profiles. Additionally, during the enrolment process, MOOC providers can identify the students' attributes through personality tests. This will help in customizing the study material and teaching pedagogy as per the needs of the students.Originality/valueThe study contributes to the growing area of research in MOOCs usage by exploring the influence of personality traits on learners' behaviour towards completing MOOCs. Since the learners' intention to complete MOOCs is a major concern for MOOC developers, hence the present study makes a worthwhile contribution as it is a relatively under-researched area.

MOOCs One-Stop Shop: A Realization of a Unified MOOCs Search Engine

Massive open online courses (MOOCs) have gained great popularity among adult learners, as many professionals use them to advance their careers. However, many MOOCs providers offer a large number of courses across many subjects, making the search and selection of the appropriate course cumbersome for the learner through a regular Web search. Hence, there is a crucial need for a unified search engine that acts as a one-stop-shop for all MOOCs. This paper presents the design and implementation of a unified MOOCs search model for retrieving and recommending courses from multiple MOOCs. The evaluation showed that the proposed model is reliable and convenient. Initial results showed that the system could present courses from multiple MOOCs that suit users’ needs. Moreover, the recommendation functionality is applied for a better user-centric orientation.