Knowledge socialism in the COVID-19 era: A collective exploration of needs, forms, and possibilities

The inspiration for this collective writing project began with a digital conference entitled ‘Knowledge Socialism, COVID-19 and the New Reality of Education' held at Beijing Normal University. In this conference and through this article, multiple researchers spread across six continents have engaged in the collaborative task of outlining emerging innovations and alternative contingencies towards education, international collaboration, and digital reform in this time of global crisis. Trends associated with digital education, knowledge openness, peer production, and collective intelligence as articulated by Michael A. Peters' conception of Knowledge Socialism are given careful analysis and exploration. Some of the members of this collective endeavor to identify problems, others, begin to draw boxes around potential solutions. Overall, this article engages with real world challenges and innovations that look beyond dominant neoliberal trends in the knowledge economy to build bridges toward novel possibilities in this era of rapid digital change.

Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time.

Massive Open Online Courses have become a frequent platform for learners to acquire knowledge. This study aims to explore multiple factors influencing learner retention in MOOCs during the COVID-19 pandemic. To address this, we collected quantitative and qualitative data from questionnaires and qualitative data from interviews and then analyzed them through the Partial Least Square-Structural Equation Modeling to test 14 research hypotheses. The proposed research model and research hypotheses are empirically tested with 243 participants across the world. According to the results, support is found for all of the 14 research hypotheses. We confirmed 14 factors influencing learner retention in MOOCs. The result is beneficial for designers and manufacturers of MOOCs to improve the quality of the products and facilitate online or blended learning during this special time. It could also help students improve their learning experiences. Future research could examine influencing factors of learner retention in MOOCs with interdisciplinary cooperation.

Analysis of Learners' Sentiments on MOOC Forums using Natural Language Processing Techniques

MOOCs have gained a lot of popularity for past few years. Especially after the outbreak of Coronavirus, everyone is trying to gain some knowledge and skill while being at the comfort of home and making themselves safe. Due to sudden increase in the number of participants on MOOCs there is a need for an automated system to be able to assess the reviews and feedbacks given by the learners and find the sentiments behind their statements. This analysis will help trainers identify their shortcoming and make their courses even better. For sentiments analysis, several approaches may be used. This research aims to provide a system which will perform sentiments analysis on the novel dataset and show the comparison of lexicon-based vs transformer-based sentiment analysis models. For lexicon based, VADER was chosen and for transformer-based, state-of-The-Art BERT was chosen. BERT was found to be exceptionally good with an accuracy of 84% and F1-score of 0.64. © 2022 IEEE.

Gaining an Insight into Learner Satisfaction in MOOCs: An Investigation through Blog Mining

MOOCs can be considered as a powerful alternative in extraordinary situations where people cannot reach formal education. In recent years, the widespread use of the internet worldwide and especially the CoVID-19 has increased the need of people for MOOCs. However, in order to increase the effectiveness of MOOCs, and to provide a better learning environment, the need to evaluate MOOCs has arisen. One of the indicators of quality in online learning is student satisfaction. Accordingly, this research aims to reveal learner satisfaction in MOOCs. The most important indicator for measuring this satisfaction in MOOCs is user comments. In this study, 39101 comments of the participants in 960 MOOCs were examined by using text mining techniques within the framework of satisfaction.

Indicators for enhancing learners' engagement in massive open online courses: A systematic review

Massive open online courses (MOOCs) have paved a new learning path for the 21st-century world. The potential to reach a massive geographically dispersed audience is one of the major advantages of MOOCs. Moreover, they can be offered on a self-paced and self-regulated basis and have become an integral part of lifelong learning, especially in workplaces. However, one persistent problem is the lack of learners' engagement. A harmonisation of studies providing a holistic view into aggregating indicators for enhancing learners' engagement in MOOCs is lacking. The coronavirus pandemic has accelerated MOOC adoption, and learners' engagement in MOOCs has become even more essential for the success of this educational innovation. We examine the existing literature to derive indicators important for enhancing learners' engagement in MOOC learning environments. Using a systematic approach, 83 empirical studies were examined, and 10 indicators were identified as important considerations for enhancing learners' engagement while designing MOOCs-from initiatives for individual learners to platform and instructional design perspectives. We also present a table describing these indicators and offer a structured discussion on each one. We believe the results provide guidelines for MOOC designers and instructors, educational policymakers, higher education institutions, and MOOC engagement researchers.

Student performance prediction in e-learning system and evaluating effectiveness of online courses

In recent years, the number of online courses in India has skyrocketed especially due to the Covid pandemic. The most significant increments have happened in degree colleges, where 85% concur that internet based courses are important for their drawn-out procedure when contrasted with 60% in 2015. The distribution of online courses has evolved dramatically as technology has advanced. Web-based platform provides new challenges for both teachers and students. Teachers should be clear about the effectiveness of online learning in teaching students. For that, the possibilities of online learning should be compared with traditional learning. Students are evaluated based on their focus on online learning. This study aims to determine the efficacy of online courses by predicting student performance in an e-learning system. These research findings evaluate modern learning methods, highlight students' potential and help teachers understand how to assess and lead students on online platforms. © 2023 IEEE.

The use of Deep Learning techniques in E-Learning systems and MOOCs

E-Learning and Massive Open Online Courses are old techniques, but since the Coronavirus, they have become more popular again. Students already suffer from a lack of concentration and motivation in traditional courses;thus, this lack affects online courses. Furthermore, another important Online Learning systems problem is the difference between learners in terms of Learning Styles, abilities, social characteristics as well as preferences, background, and other psychological and mental features. Generally, these features are not taken into account by scientists. Therefore, Deep Learning techniques and Datasets have been used to improve E-Learning systems and MOOCs in several aspects such as: predicting dropout, Learning Styles and performance of online learners, and even their attention after taking an online course. In this work, we have studied and analyzed many recent works in the area of using Deep Learning techniques to improve Online Learning systems and MOOCs. This analysis shows what researchers rely on to improve E-Learning and MOOCs and demonstrates that research does not use the definition of the appropriate Learning Style frequently. However, the most used ones are dropout and performance of learners. In another hand, learners' attention is still gap. © 2022 IEEE.

An Empirical Investigation into Students' Actual Use of MOOCs in Saudi Arabia Higher Education

Massive Open Online Courses, or MOOCs, are a type of educational innovation where enrollment in the courses given is free and available online. The MOOCs course selection is extensive and may accommodate hundreds or thousands of students at once. The current study, however, aims to look into how the academic self-efficacy of real MOOC users affects learning engagement and perseverance in higher education in Saudi Arabia. This study added the Technology Acceptance Model (TAM) to social cognitive theory. Therefore, the primary goal is to create a new model by examining the variables that affect the perceived utility and perceived service quality, as well as the students' general perceptions of MOOCs that are really used. Therefore, this research used a quantitative approach and distributed the questionnaire online through a Google Form. It collected data from 276 King Saud University students and used it to test the hypothesized correlations using structural equation modeling (SEM-PLS). The study's findings showed that perceptions of perceived benefits and service quality consistently had a significant influence on social interaction, influence, networks of support, and social identity. A further finding was that reported utility and perceived service quality have always been significantly influenced by academic self-efficacy in actual MOOC use. Because of this, learning engagement and perseverance in Saudi Arabian higher education are significantly impacted by the academic self-efficacy of real MOOC users. According to the findings, MOOC programs generally have a positive influence on the kingdom's higher education system. As a result, it is almost certain that this research model will assist university decision-makers in determining whether or not MOOC usage is prevalent at Saudi educational institutions.

Intention to Participate in MOOCs: Case of University Students in Northwestern Nigeria During COVID-19 Pandemic

Massive open online courses (MOOCs) have been introduced over the past few decades to account for the twenty-first-era education and recent COVID-19 pandemic trials driven by the spread of internet-based technology on the internet. This research seeks to give an extended model investigating the intention to use MOOCs based on students at public universities in northwestern Nigeria. The extended TAM model was tested via PLS structural equation modelling using data collected from 451 students at public universities in northwestern Nigeria. The research findings indicated that the proposed extended model delivers a 72.0% descriptive effect. The creative technology acceptance TAM model establishes a strong signal for the effects of PU, PR, PEOU, SN, and TA on intentions to practice MOOCs technology among students in Nigerian public universities during the COVID-19 pandemic. The outcomes present practical and theoretical implications that MOOC developers can use to justify why MOOCs are not high within public universities in Northern-western Nigeria. The findings also indicated that PU, PEOU, PR SN, and TA significantly impact students' intention to use MOOCs. The research has provided insight into extended TAM in Nigerian learning environments to discover the issues influencing students' intention to use MOOCs. Dissimilar to preceding empirical reviews, this research broadly investigated the intention to participate in MOOCs of public University students in northwestern Nigeria during the COVID-19 pandemic, delivering crucial discoveries and commendations for impending research openings. The findings could practically enlighten administrators, instructors, developers, and policymakers in making informed decisions © 2023, International Journal of Interactive Mobile Technologies.All Rights Reserved.

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

In recent years, the increasingly fierce competition among higher education institutions (HEIs), the finite resources, and the enormous influence of the COVID-19 epidemic on higher education have made it especially important to evaluate the performance of Chinese higher education institutions. This paper utilizes the DEA-BCC and Malmquist index to analyze the efficiency and productivity of 34 Chinese "985 Project” universities in the period 2017–2021. The indicator system includes three inputs and five outputs, contained in Model 1 and Model 2 for comparative analysis. The results demonstrate that the COVID-19 epidemic has had a considerable negative impact on Chinese higher education, and has induced the reduction of technical efficiency and productivity. Setting up online MOOCs is conducive to enhancing the efficiency and productivity of HEIs;in addition, the efficiency mentioned varies noticeably among different university levels, and there is no significant difference in different university types and geographical locations. © 2023 by the authors.

Students' continuance intention to use MOOCs: empirical evidence from India.

In recent years, there has been an increasing interest in understanding the Massive open online courses (MOOCs) due to its gaining popularity. Even though the number of online platforms and programs has grown during the COVID-19 pandemic, there is still a high rate of dropout and non-completion. In this work, the expectation-confirmation model is combined with MOOC features such as perceived openness, perceived reputation, and other factors i.e., perceived enjoyment, and perceived computer self-efficacy to investigate the learner's continued intention to use MOOC. A survey was undertaken and the data was collected from 383 students pursuing their degrees (undergraduate and post-graduate) in Karnataka state, India. The collected data were analyzed with structural equation modelling in Smart PLS 3. The study confirms a significant influence of confirmation and perceived usefulness on satisfaction, and direct significant influence of perceived computer self-efficacy, satisfaction, and perceived usefulness on continuance intention. Also, the results demonstrated the significant influence of confirmation on perceived enjoyment and usefulness and the effect of computer self-efficacy on usefulness. The findings in this study indicate that the MOOC platforms should focus on confirming learner expectations and the usefulness of courses to ensure student satisfaction and continuance of courses.

MOOC-based learning for human resource development in organizations during the post-pandemic and war crisis: a study from a developing country perspective

PurposeHuman resources (HR) management has encountered unforeseen obstacles and issues in recruiting, retaining, training and developing workforces under the "new normal” due to pandemic circumstances followed by the Russo–Ukrainian War and global economic turmoil. As the world is now well-equipped with technological advancements and internet-based connectivity, many pandemic disruptions have been avoided through rapid adaptation of technological systems. Despite the constructive outcomes of this contemporary approach to learning and development (L&D), this study explores the further depths of massive open online courses (MOOC) platform adoption in human resource development initiatives during pandemic times.Design/methodology/approachA qualitative research approach was adopted to understand the employee and HR perspective on the changes in L&D approaches in organizations. To gather the primary data, respondents were divided into two clusters;different sets of questionnaires were developed for interview sessions.FindingsResults suggest that employee L&D was much more improvised with distance or online learning, including organizational e-learning systems and MOOC platforms. To accomplish their HR development goals, organizations went through significant transformations during the Coronavirus pandemic;organizational attempts to initiate online training and MOOC-based learning fostered positive results in employee capacity development, process improvement, employee engagement and motivation.Originality/valueThis research will assist organizations in developing interactive training methods as an effective replacement for traditional training. Additionally, it will assist readers, practitioners and HR specialists in understanding how MOOCs are changing the L&D ecosystem.

Using Deep Transfer Learning to Predict Student Engagement in Online Courses

The use of online courses is growing worldwide that has opened the door for the interested students to learn comfortably from their locations especially, during Covid-19 pandemic. However, an important aspect of traditional classroom is real-time students' feedback for content delivery and interactive sessions, which is missing in online courses. The aim of this work is to bridge this gap by providing an automatic recognition system for engagement level of the students during online courses using deep transfer learning. In this paper, a CNN based method is proposed to predict the level of engagement while watching online class sessions. The CNN based method consists of two different modalities including: (1) pre-trained network based transfer learning for feature extraction from image data, (2) support vector machine (SVM) classifier for classification. Ten different pre-trained networks are used in the proposed method. The superiority of the method is evaluated on the dataset created using images of graduate students. Of all pre-trained networks, Resnet50 and VGG16 achieved highest classification accuracy of 72.34% and 71.77% using the proposed approach respectively. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Making Online English Learning More Engaging for Chinese College Students: A Comparative Analysis of MOOCs and Bilibili

Due to the COVID-19, Chinese universities have moved their English courses online. Students took lessons through various online learning platforms, especially MOOCs. However, MOOCs' problems such as low course completion rate, poor learning engagement, and learning efficiency harm the education quality. This study explores whether Bilibili, an online entertainment platform providing English videos, has better affordances in online English learning. Through a comparative analysis of the two platforms using questionnaires and SPSS software, the results show that compared to MOOCs, respondents perceived Bilibili to have a higher level of interactivity. In addition, respondents regarded Bilibili's screen bullets to have more significant positive effects on their English learning than MOOCs' discussion forums, especially in triggering their English learning interest. Still, the difference is not prominent in learning English grammar. Based on the results, the study argues that universities should choose between MOOCs and Bilibili according to the different characteristics of English skills. © 2022 Owner/Author.

Leveraging MOOCs for learners in economically disadvantaged regions.

While Massive Online Open Courses (MOOCs) have seen a surge in enrollments in higher education around the world especially during the Covid-19 pandemic, it is unclear if learners from the economically disadvantaged regions (EDR) are also able to capitalize on them. Specifically, challenges related to using MOOCs in these regions have been reported in the literature. Thus, the objective of this paper is to address the pedagogical challenge by investigating approaches to leverage MOOCs for learners in EDR. Drawing from the ARCS (i.e. Attention, Relevance, Confidence and Satisfaction) model, we proposed an embedded MOOCs approach where bite-sized MOOCs segments are integrated into in-class lectures under the guidance of the instructors. The effectiveness of the embedded MOOCs approach was evaluated and compared with other instructional methods. Results from randomized experiments showed that the embedded MOOCs approach had higher evaluations in terms of attention, relevance and satisfaction than face-to-face learning approach. In addition, the embedded MOOCs approach outperformed asynchronously blended MOOCs in enhancing students' relevance perception. Regression analysis further revealed that attention, confidence, and satisfaction perceptions were positively associated with students' intention to adopt the embedded MOOCs approach in their future studies. The findings shed light on how to utilize MOOCs and re-use content in MOOCs for global benefits and enable new pedagogical developments. The findings also underscore the importance of local social support and offline interactions to support the online learning materials.

Towards an understanding of the engagement and emotional behaviour of MOOC students using sentiment and semantic features

Online learning and teaching increased in 2020, driven by the COVID-19 pandemic. As many researchers attempted to understand the impact stress had on the emotional behaviours and academic performance of students, most studies explored these pre- and during-COVID behaviours in the context of brick and mortar institutions transitioning to online delivery. There is an opportunity to compare the experiences of students in the MOOC environment in this period, particularly in terms of the difference of engagement, semantics and sentiment/stress behaviours in 2019 and 2020. In this study, we use a dataset from AdelaideX between this time period to identify the most significant features that impact student outcomes. Where previous machine learning approaches used singular features such as student interaction or sentiment in discussion forum posts, we incorporate three feature categories of engagement, semantics and sentiment/stress in an ensemble model is based on voting and stacked methods to determining the relationship between them and academic performance. From our results, we discover that sentiment/stress played little part in academic performance and was relatively unchanged in online courses in this dataset between 2019 and 2020. We present two individual student cases to further contextualise our findings. © 2023 The Author(s)

A perspective of massive open online courses (MOOCs) and public health.

Massive open online courses (MOOCs) have emerged as an innovative educational technology relevant to and affecting higher education, professional development, and lifelong learning. This paper introduces the principles of MOOCs and reviews the development of these platforms over time. We reflect upon the considerable investment by institutions to develop, deliver and promote such courses, particularly in public health. While open to interpretation, the inherent power, influence, and effectiveness of MOOCs is unquestionable. The potential contribution of MOOCs to public health education is immense, with almost universal reach and access. However, apart from research into participant engagement and knowledge, MOOC-related research and evaluation continue to lag with the rapid proliferation of these courses in response to emerging challenges, as seen with the Coronavirus Disease 19 (COVID-19) pandemic. This makes analyzing the contribution of MOOCs to public health education, health promotion and community programs challenging. This perspective article provides a robust rationale for the necessity of MOOCs and their utility in upskilling health professionals and the general public. It builds on current knowledge to comprehensively explore the factors influencing the development, and application of MOOCs.

Reflections on Massive Open Online Courses (MOOCS) during the COVID-19 Pandemic: A Bibliometric Mapping Analysis

Massive Open Online Courses (MOOCs) have been around for some time, but several studies highlighted different issues associated with them, including quality. The COVID-19 pandemic catalyzed their second blooming, where MOOCs have seen a surge in enrollments since March 2020. This study intended to explore how this enrollment reflected on the research studies included in scientific publications, indexed by Web of Science. Specifically, the bibliometric mapping analyses of 108 studies have revealed an ongoing trend in the countries contributing to the MOOCs research, namely USA, China, UK and Spain. Additionally, MOOCs research coming from US, UK and other western countries was decreasing before the pandemic and showed a continuous dramatic reduction also during the COVID-19 pandemic. Growing attention in MOOCs research among less represented countries was also observed. Besides, most of the topics focused on by MOOCs research during the pandemic were mainly related to education and engineering.

A technology-enhanced scaffolding instructional design for fully online courses

The COVID-19 pandemic has forced teachers to implement fully online teaching. This study reviewed the popular technologies that are used in online learning, as well as the advantages and difficulties of applying fully online courses for formal education. Based on this research background, this study proposed a nested scaffolding design of an online course for 215 college students in China with the help of six technological tools, which effectively replaced face-to-face interactions and significantly improved the usage of the supporting learning platform. The inner-outer learning cycles supported by the technological tools improved the quality of the scaffolding conversations, reduced the scaffolding time cost that teachers had to expend and enhanced the effectiveness of the individualised scaffolding instructions.Implications for practice or policy:center dot First-year students' learning outcomes can be improved by the scaffolding support from Web 2.0 resource URLs, a small private online course, and EducCoder resources.center dot Course leaders should construct at least 3-5 stage-wise evaluations to deconstruct the big learning process into several observable learning cycles, making the Kolb (1984) cycles controllable.center dot Assessors may need to consider involving various exercises, such as quizzes, online experiments and synthesised tasks to facilitate students' learning.

Public Administration Studies: The Digital Trajectory

This paper asks how Information and Communi-cation Technology (ICT) will influence Public Admin-istration (PA) as an academic discipline in the near future, both in research and teaching. After looking at current ICT phenomena - from AI to gaming - and how PA has taken them up, two critical, interlinked phenomena are then analyzed: MOOCs (Massive Open Online Courses) and their effects, including a review of how the Covid-19 pandemic pushed this kind of teaching, and the current ability of algorithms to write a certain type of texts. These may have the effect to strongly enforce, even lock in, current epis-temological tendencies of PA, but they may also give rise to an altogether different kind of development of scholarly inquiry in the discipline and beyond.