Decoding and designing massive open online courses (MOOCs)

Purpose This study aims to investigate the attributes of the online programme that are considered and compute their relative importance in the purchase decision. This study aims to identify the most lucrative bundling of these attributes and their levels that can be used by online education companies to craft their product design strategy to attract customers with the most attractive offering. Design/methodology/approach This research paper endeavours to identify the attributes of online education, which customers consider for making a purchase decision. Exploratory factor analysis followed by confirmatory factor analysis was used to identify the key attributes of online education programmes. This paper uses the conjoint analysis technique to identify the most preferred bundling of attributes, which online education companies can package to attract customers. Findings Based on various attributes and their respective levels, it is evident the most lucrative design for attracting customers to buy online education programmes is to provide certification from a reputed international university, which requires an investment to the tune of 3,000–5,000. The duration of four weeks with asynchronous pedagogy and access to course material vial uniform resource locator (URL) is a preferred feature. Access via a mobile application is more preferred over Web access. A phone application is known to be optimised, and most people are using mobile phones to access the internet. Online certification or degrees that are considered as valid employment qualifications were most preferred over other reasons. Originality/value There is a dearth of studies on massive open online courses (MOOCs) from a product design perspective. There is a gap in the context of the features to be included in the MOOCs package so that the customer can find more value in it, and the companies can benefit by expanding their customer base. The research question which this study endeavours to explore is what attributes consumers of MOOCs consider when making a purchase decision. This study will also find the relative importance of these attributes.

Co-Creation of Massive Open Online Courses to Improve Digital Health Literacy in Pregnant and Lactating Women

Background: Digital health literacy (DHL) increases the self-efficacy and empowerment of pregnant and lactating women (PLW) in using the Internet for health issues. The European project IC-Health aimed to improve DHL among PLW, through the co-creation of Massive Open Online Courses (MOOCs). Methods: The co-creation of the MOOCs included focus groups and the creation of communities of practice (CoPs) with PLW and healthcare professionals aimed to co-design the MOOCs. The quantitative measures of MOOCs’ acceptability, experience in the co-creation process and increase in DHL (dimensions of finding, understanding and appraisal) were assessed. Results: 17 PLW participated in focus groups, 113 participants were included in CoPs and 68 participants evaluated the acceptability of MOOCs. A total of 6 MOOCs aimed at improving PLW’s DHL were co-designed. There was a significant improvement in self-perceived DHL after using MOOCs (p-value < 0.001). The acceptability of MOOCs and co-creation experience were positively valued. Conclusions: The preliminary results of the quantitative assessment showed a higher self-perceived DHL after the IC-Health MOOCs. These results suggest that IC-Health MOOCs and the co-creation methodology appear to be a viable process to carry out an intervention aimed to improve DHL levels in European PLW.

The Day the Classroom Flipped: Lessons Learned from Interdisciplinary Science Education Online

The Covid‐19 pandemic, evolving needs of students &amp; mentors, and the drive for global educational equality are collectively shifting how courses are packaged/distributed, ushering a more holistic approach and blending of fields. We recently created interdisciplinary courses in chemical biology aimed at massive open online and small private levels. These courses cover biology, chemistry, &amp; physics, and concepts underlying modern chemical‐biology tools. We discuss what we learned while creating/overseeing these courses: content optimization and maintaining material freshness while fostering a stimulating learning environment. We outline mechanisms that help sustain student attention throughout rapidly‐moving courses, how to integrate adaptability to students&rsquo; needs in the short &amp; long term, and speculate how we could have improved. We believe this will be an important guide for anyone wanting to develop online learning formats ideal for nurturing interdisciplinary scientists of tomorrow.

Application of Massive Open Online Course to Grammar Teaching for English Majors Based on Deep Learning

The study aims to explore the roles of Massive Open Online Courses (MOOCs) based on deep learning in college students’ English grammar teaching. The data are collected using a survey. After the experimental data are analyzed, it is found that students have a low sense of happiness and satisfaction and are unwilling to practice oral English and learn language points in English learning. They think that college English learning only meets the needs of CET-4 and CET-6 and does not take it as the ultimate learning goal. After the necessity and problems in English grammar teaching are discussed, the advantages of flipped classrooms of MOOCs are discussed in English grammar teaching. A teaching platform is constructed to study the foreign language teaching mode under MOOCs, and classroom teaching is combined with the advantages of MOOCs following the principle of “teaching students according to their personalities” to improve the listening, speaking, reading, writing, and translation skills of foreign language majors. The results show that high-quality online teaching resources and the deep learning-based teaching environment can provide a variety of interactive tools, by which students can communicate with their peers and teachers online. Sharing open online communication, classroom discussion, and situational simulation can enhance teachers’ deep learning ability, like the ability to communication and transfer thoughts. Constructivism with interaction as the core can help students grasp new knowledge easily. Extensive communication and interaction are important ways for learning and thinking. The new model provides students with profound learning experience, expands the teaching resources of MOOCs around the world, and maximizes the interaction between online and offline teachers and students, making knowledge widely rooted in the campus and realizing the combination of online resources and campus classroom teaching. Students can learn the knowledge through autonomous learning and discussion before class, which greatly broadens the learning time and space. In the classroom and after class, the internalization and sublimation of knowledge are completed through group cooperation, inquiry learning, scenario simulation, display, and evaluation, promoting students to know about new knowledge and highlighting the dominant position of students.

Measuring online self-regulated learning among early-career medical doctors in a Massive Open Online Course on COVID-19

Introduction: As significant autonomy is given in a Massive Open Online Course (MOOC), online self-regulated learning (SRL) ability is crucial in such courses. We aim to measure the online SRL abilities of early-career medical doctors enrolled in a MOOC. Methods: We performed a cross-sectional study using the Self-Regulated Online Learning Questionnaire-revised version (SOL-Qr). We conducted a three-stage cross-cultural validation of the SOL-Qr, followed by Confirmatory Factor Analysis (CFA). The online SRL ability of 5,432 medical doctors enrolled in a MOOC was measured using the validated SOL-Qr. Results: The CFA of the cross-translated SOL-Qr confirmed its comparability to the original version, with excellent validity & reliability. Participants showed high levels of online SRL during their early careers. Despite high online SRL scores, MOOC completion rate was low. Male participants showed slightly better time management ability than female participants. Participants working in the primary epicentrum for COVID-19 in the country showed lower online SRL scores, while participants who graduated from higher accreditation levels showed better time management ability. Conclusion: The SOL-Qr and its subscales are suitable and valid for measuring the online SRL abilities of medical doctors in a MOOC during their early-career period. Time management ability was associated with previous experience during the medical education period, while other online SRL subscales were mostly associated with workload. However, as the scores did not correlate with the time spent for learning in MOOC, the corresponding learning effort or time spent may be beyond just the commitment to the described MOOC.

Measuring online self-regulated learning among early-career medical doctors in a Massive Open Online Course on COVID-19

Introduction: As significant autonomy is given in a Massive Open Online Course (MOOC), online self-regulated learning (SRL) ability is crucial in such courses. We aim to measure the online SRL abilities of early-career medical doctors enrolled in a MOOC. Methods: We performed a cross-sectional study using the Self-Regulated Online Learning Questionnaire-revised version (SOL-Qr). We conducted a three-stage cross-cultural validation of the SOL-Qr, followed by Confirmatory Factor Analysis (CFA). The online SRL ability of 5,432 medical doctors enrolled in a MOOC was measured using the validated SOL-Qr. Results: The CFA of the cross-translated SOL-Qr confirmed its comparability to the original version, with excellent validity & reliability. Participants showed high levels of online SRL during their early careers. Despite high online SRL scores, MOOC completion rate was low. Male participants showed slightly better time management ability than female participants. Participants working in the primary epicentrum for COVID-19 in the country showed lower online SRL scores, while participants who graduated from higher accreditation levels showed better time management ability. Conclusion: The SOL-Qr and its subscales are suitable and valid for measuring the online SRL abilities of medical doctors in a MOOC during their early-career period. Time management ability was associated with previous experience during the medical education period, while other online SRL subscales were mostly associated with workload. However, as the scores did not correlate with the time spent for learning in MOOC, the corresponding learning effort or time spent may be beyond just the commitment to the described MOOC.

Towards Adaptive Gamification: A Method Using Dynamic Player Profile and a Case Study

The design of gamified experiences following the one-fits-all approach uses the same game elements for all users participating in the experience. The alternative is adaptive gamification, which considers that users have different playing motivations. Some adaptive approaches use a (static) player profile gathered at the beginning of the experience; thus, the user experience fits this player profile uncovered through the use of a player type questionnaire. This paper presents a dynamic adaptive method which takes players’ profiles as initial information and also considers how these profiles change over time based on users’ interactions and opinions. Then, the users are provided with a personalized experience through the use of game elements that correspond to their dynamic playing profile. We describe a case study in the educational context, a course integrated on Nanomoocs, a massive open online course (MOOC) platform. We also present a preliminary evaluation of the approach by means of a simulator with bots that yields promising results when compared to baseline methods. The bots simulate different types of users, not so much to evaluate the effects of gamification (i.e., the completion rate), but to validate the convergence and validity of our method. The results show that our method achieves a low error considering both situations: when the user accurately (Err = 0.0070) and inaccurately (Err = 0.0243) answers the player type questionnaire.