Massive Open Online Courses Platform Research Articles

Occupational health in developing countries – a massive open online course

In 2015 the University of Bergen launched the Massive Open Online Course (MOOC) Occupational Health in Developing Countries. The objective of this study is to describe the geographic and demographic diversity of the course participants, as well as the course participation activity with emphasis on low- and middle-income country (LMIC) learners. All data on MOOC participation were provided by the MOOC platform FutureLearn. Out of totally 5866 registrants, 72.4% attended from a LMIC geo-location, and 71.9% of the 768 course completers were LMIC residents. Most of the participants were young, well-educated and employed. Most were employed within the health and social sector. The gender distribution was almost equal, except from a higher female non-completer proportion, especially among LMIC participants. The MOOC succeeded in reaching its LMIC target group.

A Novel Search Ranking Method for MOOCs Using Unstructured Course Information

Massive open online courses (MOOCs) are a technical trend in the field of education. As the number of available MOOCs continues to grow dramatically, the difficulty for learners to find courses that satisfy their personalized learning goals has also increased. Unstructured texts, such as course descriptions and course skills, contain rich course information and are useful for MOOC platforms in constructing personalized services. This paper proposes a novel search ranking method for MOOCs that integrates unstructured course information. We propose a latent Dirichlet allocation-based model to cluster courses into groups based on course descriptions. Courses in the same cluster are considered to share similar educational contents. We then propose the CourseRank algorithm based on the information of course skills to recommend and rank courses when students search for or click on a specific course. Our experiments on the dataset from Coursera indicate that our method is able to cluster courses effectively and produce satisfactory ranking results for courses in MOOC platforms.

How Do Mixed Teaching Teams Influence Learning in IT MOOCs?

The impact of mixed teaching teams on learning quality and the outcomes of diverse target groups in a massive open online learning context in the workplace is scarcely analyzed. Insights from gender studies on female role models, research on team teaching in computer science as well as digitally supported learning do not transcend these separate areas and are therefore of restricted explanatory power. Accordingly, this session will answer the research question on how male-only and mixed teaching teams influence IT MOOCs (Massive Open Online Courses) in regard to the proportion of female learners, participation in the discussion forum, and success rates. This study will be backed by the learning data gathered in the time of running two courses about blockchain with 14,000 learners on our MOOC platform openHPI with a mixed teaching team and a male teacher. The courses are conducted entirely online and are open and free of charge. All the material provided can be accessed from any device connected to the Internet. As our MOOCs in the enterprise context address not only employees, but also partners, students and other interested (lifelong) learn-ers we will include a closer look at learners’ socio-demographic background, such as career status, highest degree, professional life, and position. Additionally, we statistically analyze accompanying survey data using research methods in social sciences. Finally, our session will highlight and discuss challenges of mixed teaching teams in IT MOOCs and possible solutions to support gender diverse online learners in the workplace.

Using Massive Open Online Course (MOOC) on Pancasila Education Increasing Students’ Score

This article analyzes the development of virtual learning capabilities through massive open online courses (MOOC) on Pancasila Education. The Pancasila Education course has only been delivered in traditionally managed classes by relying on face-to-face meetings. Therefore there needs to be a new approach in Pancasila education to deal with 21st century learning. This research was designed as a research and development education (R&D). Starts with developingthe MOOC Pancasila education platform and conducting tests on students. The research instrument used in this study was the learning outcomes (scores) of students taking Pancasila education courses. The data analysis used is the independent sample t test, which is a statistical test to find out the differences between two samples that are not interconnected. The result of the development is known that virtual learning through the MOOC platform can increasing students’ score. That are known from the average of virtual class score than traditional classes, but the level of equality is lower values than virtual classes. This average that not all students in one membership can receive virtual classes equally. The traditional and virtual classes of the Pancasila education has a significant difference

Building antimicrobial stewardship through massive open online courses: a pilot study in Macedonia

BackgroundThe global struggle against antibiotic resistance requires antimicrobial stewardship (AMS). Massive open online courses (MOOCs) offer health professionals unprecedented access to high-quality instructional material on AMS; the question is how apprehensible it is to non-native English speakers. Furthermore, to better understand how education interventions promote change towards rational antibiotic prescribing, leading institutions call for studies integrating behavioural science. Research from lower- and middle-income countries is particularly needed.ObjectivesTo measure the knowledge improvement from an AMS MOOC, the influence of language, course satisfaction and subsequent effect on intention to change antibiotic prescribing behaviour.MethodsFifty-five physicians from Macedonia completed the MOOC. Pre- and post-course knowledge test scores were compared using a one-sample t-test. The effect of a language barrier was assessed using self-reported English level. Scores were compared with participants’ intention to change behaviour in clinical practice.ResultsScores significantly improved from 77.8% to 82.2%. Participants with a higher English level improved most, while the low-level group showed no significant improvement. Physicians reported a high or very high intention to change behaviour. This was independent of knowledge improvements.ConclusionsFirst, lower self-reported English proficiency hindered knowledge acquisition from a MOOC platform. AMS programmes should commit to bridge this barrier so as to enable a global spread of education in AMS. Second, factors underlying the physicians’ intentions to engage in AMS appear to be more complex than simple knowledge improvements. This suggests that less time-consuming interventions could be as effective.

LEARNING MATHEMATICAL STATISTICS IN MASSIVE OPEN ONLINE COURSES (MOOCs)

E-learning using Massive Open Online Courses (MOOCs) has attracted a great deal of attention among higher education providers. The use of MOOCs is one of the great ideas supported by the Malaysian Ministry of Education in making the standard of our country’s education system in line with global education. Today, there were a growing number of MOOCs that continually becoming available on commercial platforms such as Openlearning.com and MOOCs Universiti Teknologi MARA (UiTM). Like many other subjects, Mathematical Statistics is a challenging subject for teaching and learning. Certain skills in this subject require ongoing guidance on how to provide the best teaching. Hence, MOOCs for Mathematical Statistics has been created to provide knowledge and skills to teach mathematics and statistical modeling briefly, conveniently, and effectively. This study focuses on providing a general design for assessing learners who study Mathematical Statistics through MOOCs platform. The platform is developed in such a way that learners can discuss and reflect. The design of MOOCs is governed by the Guidelines for Development and Delivery of Malaysia MOOCs. With the development of these MOOCs, it is hoped that it could help learners to understand Mathematical Statistics in a more effective and efficient way.

On Status Quo, Problems, and Future Development of Translation and Interpreting MOOCs in China—A Mixed Methods Approach

The release of China MOOCs Action Declaration signifies the strategic role of Massive Open Online Courses (MOOCs) in China’s national education. Compared with traditional face-to-face instruction, MOOCs have distinctive advantages, such as their large scale, openness, accessibility, flexibility and convenience, so they have shown great development momentum since the very beginning. However, translation and interpreting (TI) MOOCs in China have started relatively late, with limited numbers and types of courses offered and only sporadic studies, especially in-depth empirical research, on existing courses. By adopting a mixed-methods approach involving both desk research of TI MOOCs on 10 major MOOC platforms and in-depth interviews of two teachers and 10 students with TI MOOC teaching or learning experience, this study explores the status quo, problems, and future development of TI MOOCs in China. It is hoped that this paper will shed some light on the research and development (R&D), and application of TI MOOCs, as well as on reforms and innovations of TI education in China and other similar contexts.

An Evaluation of the Udacity MOOC based on Instructional and Interface Design Principles

Since the first appearance of the Massive Open Online Course (MOOC), the problem of low completion rates in MOOC has often been an object of research in terms of the instructional design and interface design. However, in-depth studies that examine the implementation of instructional and interface design principles in learning on the MOOC platform are still limited. Therefore, the purpose of this study is to find out the extent of Udacity in applying those principles from the Indonesian perspective. This study also aims to evaluate the usability of the MOOC platform. There are 228 participants in this study from various regions in Indonesia. The study findings indicate that Udacity has been successful in implementing content, interactivity, and course design, but there is still room for improvement in terms of instructor presence. Some usability problems were also found, and most of them are related to the online discussion forum. This study also offers an alternative design and recommendations to tackle the problems.

Reviewing and analyzing peer review Inter-Rater Reliability in a MOOC platform

Peer assessment activities might be one of the few personalized assessment alternatives to the implementation of auto-graded activities at scale in Massive Open Online Course (MOOC) environments. However, teacher's motivation to implement peer assessment activities in their courses might go beyond the most straightforward goal (i.e., assessment), as peer assessment activities also have other side benefits, such as showing evidence and enhancing the critical thinking, comprehension or writing capabilities of students. However, one of the main drawbacks of implementing peer review activities, especially when the scoring is meant to be used as part of the summative assessment, is that it adds a high degree of uncertainty to the grades. Motivated by this issue, this paper analyses the reliability of all the peer assessment activities performed as part of the MOOC platform of the Spanish University for Distance Education (UNED) UNED-COMA. The following study has analyzed 63 peer assessment activities from the different courses in the platform, and includes a total of 27,745 validated tasks and 93,334 peer reviews. Based on the Krippendorff's alpha statistic, which measures the agreement reached between the reviewers, the results obtained clearly point out the low reliability, and therefore, the low validity of this dataset of peer reviews. We did not find that factors such as the topic of the course, number of raters or number of criteria to be evaluated had a significant effect on reliability. We compare our results with other studies, discuss about the potential implications of this low reliability for summative assessment, and provide some recommendations to maximize the benefit of implementing peer activities in online courses.

Cognitive optimism of distinctive initiatives to foster self-directed and self-regulated learning skills: A comparative analysis of conventional and blended-learning in undergraduate studies

Independent learning in massive open online courses (MOOCs) requires considerable effort from the learners themselves. Blended-learning has been recognised to foster independent learning among undergraduate students. With the popularity of the blended-learning approach to teach in traditional educational settings, little has been mentioned on how cohesive this approach is in fostering self-directed learning and self-regulation among university students. This study hopes to explore undergraduate learners in their distinctive study patterns. The study was conducted to investigate a comparative study between students from two departments; Science and Social Science. The aim was to explore the students’ self-directed and self-regulated learning skills in conventional classrooms and aspects of blended-learning embedded in a MOOC platform in two academic years for undergraduates at a top UK university. This study encompasses two case studies; firstly, a combine blended-learning seminar and a conventional seminar classes and a study undertaken with a student of English as a second language (ESL). The blended-learning students were participants who registered in a conventional university and took an optional module in computer security. The second group of students participated in a core module of logic and verification. The second case study was with a final year undergraduate student in Education Studies. The students studied and engaged with the course content using their initiative and directing their learning approaches.

Feature-Based Analysis of Social Networking and Collaboration in MOOC

The aim of this article is to get insight into the features of social networking and collaboration in a massive open online course (MOOC) platform. We performed a feature-based analysis of twelve popular MOOC platforms – seven proprietary and five open-source platforms. Our study reveals that there are: (1) Two ways to include social networking – in-course and external; and (2) Two ways to incorporate collaboration functionality – built-in tools and third-party tools. The functionality provided by third-party tools differs; so, the selection of the tool is a challenge. For a built-in tool of MOOC, there is a need to re-identify the features for including it in any other MOOC platform; (3) Different ways to integrate the same tool in platforms; and (4) Different features of the same tool supported by various platforms. The proposed feature list helps future MOOC providers and developers to include social networking and collaboration functionality by selection, in contrast to specifying them afresh; and prospective educators can compare and select platforms, accordingly.

Predicting completion of massive open online course (MOOC) assignments from video viewing behavior

ABSTRACT Predicting student performance in Massive Open Online Courses (MOOCs) is important to aid in retention efforts. Researchers have demonstrated that video watching features can be used to accurately predict student test performance on video quizzes employing neural networks to predict video test grades from viewing behavior including video searching (ff, rw, pause), replays, stop, and start. Deep learning neural networks are susceptible to overfitting with low data and higher dimensions; hence, we compare various commonly used classification algorithms including logistic regression and demonstrate similar or higher rates of prediction. However, using a path analysis approach we find that the features collectively explain only a small to moderate amount of variance in assignment completion, which suggests that other factors than video-viewing behavior influence assignment completion such as student goal motivation and student self-regulation. Overall, our findings highlight the important contribution of active searching and repeated viewing to successful assignment completion in a MOOC course. Predictive models based on user interactions with the MOOC platform can help target course retention strategies to increase MOOC completion where retention is abysmally low and help to target video viewing strategies to optimize teaching and learning platform functionality using adaptive agents.

A Semantic Recommendation System for Learning Personalization in Massive Open Online Courses

<p class="0abstract">For an innovation producing education, MOOC (Massive Open Online Course) platforms offer a plethora of learning resources and pedagogical activities to support the university’s 4.0 new era and the lifelong learning movement. Nevertheless, the rapid advances in learning technologies imply the need for personalized guidance for learners and adapted learning materials. In this paper we seek to enhance the MOOC learner experience by providing a semantic recommender system for the diversity and abundance of MOOCs available for learners. Firstly, the paper analyses the state of the art of the semantic recommendation approach in a distance learning context. Then it describes the proposed MOOC recommendation system that uses the ontological representation of the learner model and MOOCs content to make its intelligent suggestions. Finally, we explore the development phases of the semantic MOOC recommendation system to define the implications for the progress of our research.</p>

MOOCs Lack Interactivity and Collaborativeness: Evaluating MOOC Platforms

Massive open online courses (MOOCs) have considered to be a potential to disseminate engineering education at scale. However, the pedagogical requirement demanded engineering student to equip with specific skillsets such as communication, interactivity, and collaboration. Yet, MOOCs are skeptical of facilitating those skills. Generally, MOOCs evaluated against accessibility and usability. These evaluations may not perceive whether the platform designs in MOOCs support to much-needed interactions and collaboration required in engineering education. We evaluated 6 MOOC platform designs under the lens of collaboration and types of interactions which occur as learner to learner, learner to instructor, learner to platform and learner to content. Evaluation criteria were derived us-ing previous frameworks and evaluations were conducted using 10 participants. Based on each criterion a matrix was formed with a weight to compare results. We found overall collaboration opportunities in platforms are significantly less than the opportunities to interact. Based on the findings we provide 5 design recommendations and provide a future direction for MOOC platform designs which en-ables facilitation to engineering education through MOOCs.

Brain–computer interface for assessment of mental efforts in e‐learning using the nonmarkovian queueing model

AbstractThe rapid advancement in information and communication technology has made e‐learning an alternative learning method for many learners. In the last few years, a huge number of learners around the world have registered in massive open online courses (MOOCs) provided by various online learning platforms. However, MOOC platforms have a vital task for the online course provider to provide enhanced students' learning experiences and satisfaction. In this work, we developed a brain–computer interface for gathering data and detecting a learner's mental situation by observing MOOC videos and electroencephalogram (EEG) devices based on John Sweller's Cognitive Load Theory. The acquired EEG signals are preprocessed with two different normalization methods to scale signals. To validate the introduced framework, the system adopted three machine learning algorithms (random forest using non‐Markovian model, support vector machine, and k‐nearest neighbors) to develop a model with preprocessed training data and test the classifiers to validate their ensemble classifiers' performance. Finally, experimental analysis showed that the random forest classifier with the non‐Markovian approach achieved more than the other two techniques in the form of overall accuracy (99.15%) and F‐measures (99.21%).

Application of Information Technology in Employee Training

This paper presents the application of information technology in employee training of the State Grid Corporation of China (SGCC). It focuses on the construction and function of online learning platform, the development of Corporate Massive Open Online Courses (MOOCs), and employees learning method. The Corporate MOOC platform is built on the enterprise cloud server and plays a critical role in the construction of enterprise culture, the publicizing of enterprise policies, the recruitment and training of employees, and the appraisal and promotion of employees’ abilities. The Knowledge Integration Center organized staff teams to build competency models and create MOOC contents based on industry skill requirements, maintain consistency between MOOC contents and competency models, and place them on a cloud-based MOOC platform. By using digital technology, instructional services are supplied to employees and assessment systems have been built, and assessment systems make great contributions to employee recruitment, training, appraisal and promotion. The Corporate MOOCs provides a good opportunity for those employees who can’t leave their jobs to learn at their own pace and have a positive relationship with the improvement and innovation of employees’ abilities.

Practice of “Internet +” in Biology Teaching

The digital teaching resources represented by MOOCs (Massive Open Online Courses) have great potential to subvert traditional classrooms. Excessive digital teaching cannot promote teaching effectively. Hence, the Internet is used as a medium in this paper to analyze the advantages and disadvantages of online learning of the MOOC platform and the classroom teaching comprehensively. The principle of complementary advantages is adopted to explore the establishment and application of teaching mode for biology teaching courses. In specific practice, the online teaching contents of the online platform account for 35%. The feedback information after one round of application suggests that the teaching effect of mixed courses is good, and students are generally willing to accept the mixed course teaching mode.

The Design and Implementation of Massive Open Online Course (MOOC): English for Pre-Diploma Students

Higher institutions are being reshaped to include technology-based syllabus in their curriculum design. It is worth to note that the emerging of Massive Open Online Courses (MOOCs) has triggered the university’s curriculum reviewers to include the platform in the syllabus contents. An English MOOC for Pre-Diploma was developed. To evaluate the course developed, the study aims to determine students’ perceptions on the MOOC course. The data were collected via survey and there were 186 respondents involved. Three main areas of the course evaluation were evaluated: 1) Content Evaluation, 2) Instructional Evaluation and 3) Technical Evaluation. The study revealed that content evaluation has the mean value of 4.25 (SD=0.68), technical evaluation with the mean value of 4.24 (SD=0.71) and instructional evaluation with the mean value of 4.14 (SD=0.70). The average mean value reported for three different types of evaluations is 4.21 (SD=0.70). The finding indicates that the respondents are most likely strongly agreed with the course content, instructional and technical part, thus, has effectively helped the users to learn the English language by using MOOC platform.

Exploring the diversity of creative prototyping in a global online learning environment

ABSTRACTIn this paper, we examine the diversity of creative prototyping responses and perceptions in a global online learning environment through our investigation of a simple building task (i.e., ‘the Shoe Tower’) in the context of a Massive Open Online Course (MOOC) focused on creativity, innovation, and change. This simple creative task, which used common household objects (shoes), was designed and presented to a global community of online learners using the Coursera MOOC platform. Performance data gathered from the task outcomes (Shoe Tower metrics and number of build attempts) and student reflections (self-assessed beauty and creativity ratings) were analyzed with respect to gender, country of origin, and occupation. Our results show that gender and country of origin were associated with creative prototyping performance in statistically significant ways, while occupation was not. In addition, the self-assessment of individual creativity was independent of gender, country of origin, and occupation, while self-assessed beauty ratings were related to country of origin and occupation, but not gender.

An Overview of Massive Open Online Course Platforms: Personalization and Semantic Web Technologies and Standards

Abstract Massive Open Online Course (MOOC) is a form of online education that provides great learning capabilities. Semantic Web technologies is an appropriate mechanism for personalization in MOOC platforms. The aim of this paper is to find out how Semantic Web is used to facilitate personalization in modern MOOC platforms. The paper describes state-of-the-art MOOC platforms from the position of personalization and Semantic Web features. We defined five personalization and five Semantic Web criteria as well as 20 MOOC platforms to review. The personalization criteria includes a personalized learning path, personalized navigation, recommendation system, personalized assessment, and personalized feedback. The Semantic Web criteria includes ontology, Resource Description Framework (RDF), Web Ontology Language (OWL), SPARQL Protocol and RDF Query Language (SPARQL), and Linked Data. The results show that most of the platforms support personalized feedback. Half of the platforms has personalized learning path tools. One third of the platforms allow personalized assessment. Three platforms recommend learning materials, and one platform allows personalized navigation. The selected platforms have poor Semantic Web technologies and standards support: three platforms use ontologies and none of the platforms supports other criteria: RDF, OWL, SPARQL, and Linked Data. Personalization tools are supported better than Semantic Web tools. Most of the platforms have no support for Semantic Web criteria. This means that currently Semantic Web is not used for personalization in the reviewed MOOC platforms.