MOOC 5.0: Comparison
Please note this is a comparison between Version 1 by Ishteyaaq Ahmad and Version 6 by Ishteyaaq Ahmad.

Massive Open Online Course 5.0 (MOOC 5.0), OCs 5.0, was introduced and discussed in a Research paper titled "MOOC 5.0: A Roadmap to the Future of Learning" published in 2022. Itsose features include better universal access, better learner engagement, adaptive learning, greater collaboration, security, and curiosity, which is being developed using Industry 4.0 technologies of the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence/Machine Learning, Blockchain, Gamification Technologies, and the Metaverse and would incorporate the zones of ethics and humanism, while at the same time providing learners with a richer and more individualized experience.

  • MOOC
  • education technology
  • IoT
  • big data
  • artificial intelligence

1. Overview of Industry 5.0 and Education 5.0

The effect of technology in today’s fast-changing world is not confined to modes of transportation and communication; the “Fourth Industrial Revolution” has brought us a new wave of change in all fields. The digital revolution is significantly changing how people live and work [1][11]. The “Fifth Industrial Revolution”, branded as Industry 5.0, promises to alter the way we develop products, increasing productivity and competitive advantage. While Industry 4.0 aspired to develop future “Smart Factories” by combining physical, digital, and virtual environments using cyber-physical systems, in Industry 5.0, intelligent machines will act as collaborators rather than opponents since they will be integrated with human brains [2][12]. Industry 5.0 offers a vision of the business that goes beyond the narrow focus on production and efficiency and strengthens the function and value of the industry in society [3][13]Figure 13 illustrates all five industrial revolutions.
Figure 13.
 Industrial Revolutions.
“Industry 4.0” developments are having a wide range of organizational repercussions, not simply technological ones [4][14]. The first and foremost challenge of “Industry 4.0” is that there is a greater need for highly skilled employees [5][6][15,16]. Over the next five years, technology-driven job creation is likely to outnumber job loss. There is a growing sense of urgency to assist people in transitioning to more long-term employment prospects [7][17]. Industry 4.0 is said to be driven by technology, whereas Industry 5.0 is driven by values [8][18]; as a result, the current state of industry inevitably raises concerns in this period of exponential technological advancement, such as the appropriateness of the current educational system in light of Industry 5.0′s requirements, design of the new educational paradigm, components in Education 5.0, etc.
Education has progressed from ‘going to university’ of Education 1.0 to Internet-based learning of Education 2.0, proceeding towards knowledge-based education of Education 3.0, and finally to innovation-based education in Education 4.0 [9][19]. Technology infiltrations into education, such as the use of smartphones, online testing, Artificial Intelligence, and Big Data, are all part of Education 4.0 [10][20]. Education 5.0 moves beyond the creation and use of technology and into the spheres of humanism and ethics [11][21]. The term “Education 4.0” and “Education 5.0” has gained popularity among educators all across the world, and emphasizes adapting to the changes, and for institutions of higher learning, this involves knowing what is expected of their incoming graduates. Figure 24 illustrates the progression of education.
Figure 24.
 Progression of Education.
The technologies of Industry 4.0 are already influencing our daily lives. Universities and colleges should prepare for the significant shift of incorporating technology-driven designs into the curriculum with the support of educationists and other visionaries. It is heartening to learn that the education system is integrating the usage of Cyber System technologies in learning under the mantra Education 4.0 [12][13][22,23]. At this juncture, it is vital to explore teaching methodologies in the context of the technical advancements of Industry 4.0 as the future years will test our ability to redesign learning for the learners of today’s digital generation [14][15][24,25]. MOOCs also require improvements on the parts of both learners and instructors to adapt to the new paradigms of learning.  The features  are depicted in Figure 35.
Figure 35.
 Features of MOOCs 5.0.

2. Technology Intervention in MOOCs

The social revolution has been sparked by Industry 5.0. technologies such as the Internet of Things (IoT), Cloud Computing, Big Data, Artificial Intelligence/Machine Learning, Block Chain, Robotics, Digital Twin, Gamification Technologies, Virtual reality (VR)/Augmented reality (AR), and the Metaverse. It is anticipated that technology will have advanced to the point of total autonomy by 2050 [6][16]. Future MOOCs will undergo a significant change in terms of education due to these technological improvements.

2.1. IoT in MOOCs

Kevin Ashton, a British technologist, coined the phrase “Internet of Things” (IoT) [16][26] to describe a way for people and items to be connected across a network. These are now widely utilized and well liked in a variety of industries, including smart homes, smart cities, wearable technology, and industrial equipment. IoT envisions a bright future for such an Internet where machine–machine communication will predominate over the present models of human–human or human–device connection [17][27]. Future intelligent virtual products will be created from real-world objects with the expansion of the Internet of Things [18][28]. IoT can be embedded in online higher education with the help of a cutting-edge AI-assisted system that considers environmental data and embedded biosensor data to estimate learners’ progress, wellness, and health [19][29]; this will not only improve e-learning platforms but will improve learning outcomes for professions and will increase completion but also reduce expenses [20][30]. A literature review suggests that researchers concentrated on several topics, a few of these included IoT in mobile learning [21][31], blending lab projects with IoT-based learning frameworks for Science, Technology, Engineering, and Mathematics (STEM) learners [22][32], personalized instruction for students through IoT data collection [23][33], etc. All students will profit from the inclusion of IoT in MOOCs since there will be improved communication and individualized learning, not to mention the unique advantages for those with impairments. 

2.2. Cloud Computing in MOOCs

In recent years, the shift to Cloud Computing has picked up pace [24][34]. Business owners are turning over control of their assets, including critical systems, to platforms that cloud service providers offer and operate [25][35]. Cloud Computing is quickly replacing traditional computer paradigms in all facets of life including education; some of the successful examples of this paradigm in the education field are Learning management systems (LMS), MOOCs, and Podcasts [26][36]. They all use the Internet to make education perpetually accessible to a limitless number of learners. In this paradigm, two main cloud service models are employed, which are infrastructure as a service (IaaS) and software as a service (SaaS). All the major MOOC providers employ cloud services and resources to promote quality teaching and learning internationally [27][37]. As the Cloud Computing trends make it abundantly evident that it will be crucial to IT in the upcoming years [28][38], MOOCs will witness better and more affordable services in the near future. 

2.3. Big Data in MOOCs

MOOCs produce a significant amount of heterogeneous educational data [29][39] and provide several chances to study a variety of issues connected to teaching design and learner outcomes [30][40]. Finding a way to extract knowledge from the extraordinarily rich datasets being produced and turn it into information that can be used by students, instructors, and the general public is the key problem in Big-Data-intensive research and learning analytics [31][41]. According to a literature study, researchers investigated a variety of MOOC categories using Big Data, among which included diverse Big Data of MOOC [32][42], identification of MOOC dropout learners [33][34][43,44], forecasting MOOC learners’ potential grades [35][45], MOOC data analytics [36][46], learning analytics [37][47], demand for MOOC [38][48], Educational Privacy in the Online Classroom [39][49], Automated text detection [40][50], Privacy in MOOC [41][51], MOOC video watching behavior [42][52], Topic-oriented learning assistance [43][53], etc.

2.4. Artificial Intelligence/Machine Learning in MOOCs

Artificial Intelligence (AI) and Machine Learning (ML) have made considerable strides in recent years, and they now represent an emergent technology that will transform how people live. The use of AI/ML in education is expanding quickly to enhance the caliber of teaching and learning. According to the Horizon Report’s Higher Education Edition from 2017, Artificial Intelligence will be applied in higher education by 2022 [44][54]. MOOCs have a strong probability of using AI/ML by an analysis of the extensive MOOC dataset [45][55]. AI/ML may employ data analytics to enhance teaching and learning methods. Large datasets of MOOCs may be used to train Machine Learning algorithms so they can learn from them and provide predictions or suggestions on how to learn something new or improve teaching. The MOOC dropout prediction studies using AI/ML have been discussed by several authors [46][47][48][49][56,57,58,59]. While notable researchers focused on many different subjects, some of these included learner clickstream analyses [50][51][60,61], satisfaction among the learners [52][53][62,63], time-based metrics of learner interactions and evaluations [54][64], the usage of MOOC datasets for the K-means method [55][65], using Machine Learning techniques to sort and categorize MOOC learners [56][66], learners’ emotional tendencies [57][67], MOOC learning behaviors [58][68], an intelligent investigation [59][69], Convolutional neural networks (CNN) for measuring the levels of learner engagement through webcam [60][70], etc.

2.5. Blockchain Technology in MOOC

Blockchain technology has demonstrated remarkable application opportunities since its beginnings and has been used in numerous sectors; because of its strengthening security feature, it may be used to construct many Blockchain systems [61][62][71,72]. Blockchain technology may be implemented at higher education institutions to enhance teaching strategies, provide better learning platforms, improve recordkeeping, and enhance student involvement and motivation [63][73]. The literature suggests that the rapid advancement of Blockchain technology will have a positive impact on the creation of MOOC communication platforms resulting in the advancement of higher education [64][74]. MOOCs’ completion records are kept in Electronic Learning Records (ELRs), which are often maintained in a cloud data center, which are crucial for learners since they provide solid proof of the learning process. However, the security and Privacy of ELRs cannot be ensured with third-party storage. As a result, a Blockchain-based solution for the safe storing and distribution of ELRs in MOOC learning systems can be implemented [65][75]. A Blockchain system that keeps track of every detail of every transaction will allow the academic institution that awards credentials to confirm that learning actually happened and that knowledge, competencies, and skills were accurately assessed [66][76]. Melanie Swan suggested using Blockchain to encode open badges for MOOCs [67][77].

2.6. Digital Twin in MOOCs

Though highly creative and needing a broad framework of several technologies, the Digital Twin notion is still not at the cutting edge [68][78]. The qualities of a Digital Twin include a virtual and actual symbiosis, high levels of simulation, real-time contact, and deep understanding, among others. The trend of its use is moving from the industrial to the educational sectors [69][79]. Interesting scientific material has begun to stream on topics such as smart factory Digital Twin technology in education [70][80], Digital Twin Campus [71][81], Ontology [72][82], etc. For many IT applications in Industry 5.0, the concept of the “digital twin for everything” seems to be a relevant one [73][83]. However, the use of Digital Twin (DT) in education is still in its infancy when compared to that of DT in the industrial sector. 

2.7. Gamification Technologies in MOOCs

Gamification is the application of components often prevalent in games, such as plot, feedback, rewards systems, conflict, collaboration, competition, defined objectives and rules, levels, trial-and-error, enjoyment, engagement, and interactivity [74][84], and it is often used to fix problems and enhance learning [75][85]. The primary goal of Gamification, for non-gaming objectives in real-world environments, is to increase human motivation and performance concerning a particular task [76][86]. In the beginning, Gamification techniques were used in marketing campaigns and web applications to encourage, involve, and retain customers [77][87].
With the shifting paradigm in education, Gamification has also found use in the teaching–learning process. Concept acquisition and awareness were considerably enhanced when using information and communication technologies (ICT) along with Gamification [78][88]. It applies the foundational principle of learning by doing, which encourages students to acquire knowledge and make discoveries about many topics via independent experimentation. There is limited acceptance of serious games in higher education; for example, higher education institutions in Portugal use only around 20% of the Gamification techniques [79][89]. Massive Online Open Courses (MOOCs) are a growing trend, but their extremely low completion rates provide difficulty. Finding innovative strategies to inspire learners and persuade them to finish the course is vital because a significant number of learners drop out of the MOOC [80][90]. Gamification-based methodology for motivating MOOC learners to complete the course can be a better strategy [81][82][83][84][91,92,93,94]. Gamification design for MOOCs should incorporate both social and individual components, based on the implementation goal, social presence, social impact, and flow theory [85][95]. Studies have revealed that MOOC Gamification has been implemented in a few cases and even if the outcomes on motivation and learning are positive, there are still prospects for scholarly publishing [86][96]

2.8. Metaverse in MOOCs

The Metaverse is a perpetual multi-user habitat that unifies the actual world with digital virtual elements [87][97]. Virtual reality (VR), Augmented reality (AR), as well as mixed reality (MR), are some of the most important elements of the Metaverse since they successfully give users a 3D immersive virtual experience [88][98], although Virtual reality (VR)/Augmented reality (AR) is now employed extensively across many industries. As MOOCs need personalization and communication for traditionalist means of material introduction (fixed visual, sound, and contents) to provide the learners with a more engaging learning experience [89][99], the Metaverse and its components provide excellent chances to raise educational standards by developing fresh approaches and strategies. Few Metaverse MOOCs have been implemented where learners confirmed their applicability and functioning both within and outside of the classroom [90][100] and some have been proposed [91][101]; however, it will take time, and studies presently show that there is a research gap in the educational Metaverse [92][102]

3. MOOC 5.0

For a substantial portion of the world’s population, MOOCs provide not only learning opportunities but access to world-class educators and researchers from top-tier educational institutions [93][103]. Some literature categorizes MOOCs in various ways; however, there does not appear to be agreement on the best way to do so. It has been classified as MOOC 2.0. on the concepts of collaboration among other online learners [94][95][104,105], credit credentials [96][106], and personal learning goals [97][107], as MOOC 3.0 is based on MOOC incorporation into traditional academic programs and credit recognition [98][108]. Otto Scharmer [99][109] suggests that MOOCs have evolved from instructor-centric one-to-many to learner-centric many-to-one personalized education. Figure 46 explains all four levels of evolution of MOOCs. The theory was based on a pilot MOOC, where for evolution from MOOC 1.0 to MOOC 4.0, there has effectively been a change in the conversational level at which the learning takes place, which evolves from downloading MOOC 1.0 to a two-way interaction in MOOC 2.0, to a multi-lateral dialogue in MOOC 3.0 before finally being anchored in level 4 as collective creativity in MOOC 4.0 because conversation is experienced as a co-creative.
Figure 46. Evolution of MOOCs based on Otto Scharmer’s classification [99].
 Evolution of MOOCs based on Otto Scharmer’s classification [109].
As learners will have access to more technology in the future, humanized online courses that cater to each learner’s unique requirements will be more and more essential [100][110]. This is where MOOC, which is being developed using Industry 5.0 technology and also examines the areas of ethics and humanism, may be extendedly classified, giving it the name MOOC 5.0. The focus of MOOC 5.0 teaching may be on each learner’s interpretation and way of thinking, as well as providing them with personalized learning recommendations that have humanism and ethics. The concept is shown in Figure 57.
Figure 57.
MOOCs 5.0.