Students’ Perceptions towards Using MOOCs Platform in Ideological and Political Courses

Massive open online course (MOOC) is an innovative educational model that has attracted widespread attention in recent years. Despite a growing number of registered users, many have given up continuously using MOOC platforms after the first-time user experience; thus, a high dropout rate has severely hindered the sustainable development of MOOC platforms. To address the problem, this study started with the quality factors of MOOC platforms and the confirmation of user expectations by integrating the D&M ISS model and the expectation confirmation model into one, with the goal of identifying the factors that affect users’ continuance intention to use MOOC platforms. In this study, online questionnaires were distributed to Chinese users with experience in using MOOC platforms, and a total of 550 valid samples were recovered. In addition, the theoretical model was tested using structural equation modeling (SEM). The research results showed that there are three critical antecedents affecting the confirmation of user expectations for a MOOC platform, including information quality, system quality, and service quality, of which service quality has the greatest impact on users’ expectation confirmation. If user expectations for an MOOC platform are positively confirmed, the perceived usefulness of the platform as well as the satisfaction with it will effectively be improved. Moreover, perceived usefulness has been proven to be a critical factor affecting users’ continuance intention to use MOOC platforms, which is followed by user satisfaction. Compared to the original ECM, the integrated research model has delivered significantly improved explanatory power for users’ continuance intention. Hence, this study makes up for the insufficiency of ECM in explaining the factors affecting users’ expectation confirmation and provides theoretical support for MOOC platform developers.

Retaining learners has been an important issue for massive open online course (MOOC) platforms. Given the different, and even contradictory, conclusions in studies on the continuance intention of MOOC learners, this study selected 53 highly correlated empirical studies published from 2008 to 2022 and constructed a research model based on visual knowledge map analysis. Meta-analysis was applied to identify the key factors, and subgroup analysis was conducted to explore the moderating effect of mandatory participation and prior learning experience. The results show that attitude and satisfaction play the most significant role. Perceived usefulness, perceived ease of use, confirmation, social influence, perceived enjoyment, outcome expectation, self-efficacy and task-technology fit all play essential functions, while the direct impact of social presence requires further research. Prior learning experience and mandatory participation have moderating effects on perceived usefulness. MOOC developers should make more efforts and improvements in content quality, social quality and service quality. Implications for practice or policy: Learners’ continuance intention can be enhanced by improving individual perceived positive feelings related to MOOCs and individual satisfaction with MOOC platforms. Directors of mandatory courses in MOOCs should place greater emphasis on improving learners’ perceived ease of use of MOOC platforms. Superintendents of MOOC platforms need to be aware of the role of perceived usefulness of learners with less prior learning experience in their continuance intention.

Massive Open Online Course (MOOC) has been playing an important role in the latest e-learning initiative and has obtained a widespread popularity in many universities. However, the low course completion rates of students have become an outstanding issue that should not be neglected. Based on the Expectation-Confirmation Model (ECM), this study examines the effects of students’ perceived usefulness, confirmation and satisfaction on MOOC continuance intention. Structural Equation Modeling (SEM) was used to validate the proposed model and hypotheses. Participants were 368 undergraduate students enrolled in a MOOC platform. The study’s result revealed that confirmation has significant effects on students’ perceived usefulness and satisfaction. Perceived usefulness and satisfaction have significant effects on students’ continuance intention while perceived usefulness has no significant effects on students’ satisfaction. This study will help to outspread our understanding of what influence students to continue using MOOC.

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

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.

We reviewed numerous course reports and research papers generated through massive open online courses (MOOCs) and generally found two phases of MOOCs research, with a turning point in 2012, the so-called year of the MOOCs. Among these sources, research analyzing educational big data of MOOCs can be sorted into three groups: (1) Learning pattern and learner categories; (2) learners completing or dropping out of courses; (3) specific learning behaviors and different functions of the MOOCs platform. However, we find limitations in the existing data. This insufficiency is partly derived from the lack of conventional educational and psychological theoretical frameworks in MOOCs research based on big data from online platforms. We point out that researchers could use MOOCs platforms as valid data resources to further verify and to extend conventional educational research theories and frameworks, such as learning theories, pedagogy and educational policy. We also analyze different data types that MOOCs platforms offer and their roles in educational data mining (EDM). MOOCs data include user logs, learning paths and performance results. It is important in future research to combine conventional theories with options presented by new data. This paper presumes there will be three types of research based on big data from MOOCs platforms. Such research will mainly be on: the MOOCs platform itself; MOOCs design and delivery; EDM and learning behavior analytics.

The purpose of this study was to examine the relationships between users’ satisfaction with actual use of massive open online courses (MOOCs) and intrinsically motivated, task-technology fit, attitudes toward using MOOCs, and behavioral intention to use MOOCs. As the primary technique for data collection, a survey questionnaire on self-determination theory (SDT) as well as task-technology fit (TTF) was distributed to a total of 228 students. The results of the users’ (TTF) to attitude toward using MOOCs and their behavioral intention to use MOOCs had a positive impact on their satisfaction and actual use of MOOCs in higher education institutes. However, the users’ perceived autonomy was not entirely satisfied, based on the results of their intrinsic motivation for the actual use of learning courses. Similarly, technology characteristics were insignificant with TTF for the actual use of MOOCs in academic institutions. Additionally, mediation studies showed that the correlations between independent factors on the one hand and users’ satisfaction with their actual use of MOOCs on the other were significantly mediated by intrinsic motivation, TTF attitude, and behavioral intention to use. Finally, practical ramifications were examined, and recommendations were made with regards to the direction of future studies.

An accessible Massive Open Online Course (MOOC) environment should consider each learner’s abilities, goals, context, and which specific assistive technologies can be used to facilitate the learning experience. Learners with accessibility needs can face difficulties in interacting with MOOCs, different MOOC platforms and course designs may influence their self-regulated learning skills, learning engagement, and communications with other learners. Unfortunately, MOOC platforms and the pedagogies used in the courses are not fully accessible. Literature has shown that there is a lack of understanding of what learners with accessibility needs can expect from participating in MOOCs. While there are extensive studies of MOOC demographic data, these studies rarely consider the diverse needs of learners. This chapter reports a research study which employed pre- and post-course survey data from 14 Open University MOOCs in the UK’s MOOC platform, FutureLearn, (with 29,000 and 5,000 respondents). The analysis of survey data provided preliminary insights and was a source of secondary data as a precursor to interviews with 15 learners who had declared a disability, participated in MOOCs, and filled in the course surveys. The data from the semi-structured interviews with MOOC learners helped understand their motivations, the accessibility barriers they experienced, whether/how they worked around those barriers and their suggestions for accessibility solutions. A descriptive approach was applied to analyse the survey data, while a thematic analysis of the interview data was conducted. This research has yielded an understanding of the motivations of learners with accessibility needs when taking part in MOOCs and how MOOCs should be designed to be more accessible.KeywordsAccessibilityDisabilityLearner motivationMOOCMixed-methods researchUser-centred research

Explaining Chinese university students’ continuance learning intention in the MOOC setting: A modified expectation confirmation model perspective

PurposeThe purpose of this study is to propose the research model integrating the expectation-confirmation model with the views of learning engagement (LE) and extending DeLone and McLean information systems (IS) success model to examine whether quality determinants as antecedents to students' beliefs can influence students' continuance intention of massive open online courses (MOOCs).Design/methodology/approachSample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed, and 363 (60.5%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study proved that students' perceived knowledge quality, system quality, interface design quality, learner–instructor interaction quality, and collaboration quality all positively caused students' perceived usefulness, confirmation and LE in MOOCs, which jointly explained students' satisfaction with MOOCs and subsequently resulted in students' continuance intention of MOOCs.Originality/valueThis study fully evaluates IS-related and interaction-related quality determinants via an understanding of students' state of LE in explaining students' continuance intention of MOOCs that is difficult to expound with only their utilitarian perception of MOOCs. Hence, this study contributes to deep insights into an all-round quality evaluation in the field of MOOCs continuance intention and takes extrinsic and intrinsic motivators into account in the theoretical development of MOOCs continuance intention to acquire a more comprehensive and robust analysis.

Massive open online courses (MOOC) have become important in the learning process and have been adopted in higher education, especially during the COVID-19 pandemic. However, few studies investigated MOOC continuance intention (CI) for arts disciplines. Thus, an integrated framework was proposed based on the expectation–confirmation model (ECM) and value–software–hardware–design system perception framework, focusing on the exploration of the potential factors of MOOC CI for art education taking music education as the context. A questionnaire-type survey was used, and responses from university students were analyzed using partial least squares structural equation modeling. The findings reveal that perceived music familiarity (PMF), perceived emotional value (PEV), and perceived user interface design (PUID) positively influence music MOOC CI. In addition, expectation–confirmation factors (i.e. confirmation, perceived usefulness of individual learning, and satisfaction) not only considerably affect CI but also play partially mediating roles between music MOOC CI and perception factors (i.e. PMF, PEV, and PUID). Accordingly, the ECM is extended in the music MOOC context. Moreover, the results reveal that personality traits fail to moderate CI, which denotes no significant difference across groups. The findings present several implications for researchers and practitioners in the MOOC, music and arts education, and learning system design in the context of higher education.

BackgroundMassive open online courses (MOOCs) have become immensely popular in a short span of time. However, there is very little research exploring MOOCs in the discipline of health and medicine.ObjectiveWe aim to provide a review of MOOCs related to health and medicine offered by various MOOC platforms in 2013, by analyzing and comparing the various offerings, their target audience, typical length of course, and credentials offered. We also discuss opportunities and challenges presented by MOOCs in health and medicine.MethodsHealth and medicine–related MOOCs were gathered using several methods to ensure the richness and completeness of data. Identified MOOC platform websites were used to gather the lists of offerings. In parallel, these MOOC platforms were contacted to access official data on their offerings. Two MOOC aggregator sites (Class Central and MOOC List) were also consulted to gather data on MOOC offerings. Eligibility criteria were defined to concentrate on the courses that were offered in 2013 and primarily on the subject of health and medicine. All language translations in this paper were done using Google Translate.ResultsThe search identified 225 courses, of which 98 were eligible for the review. Over half (58%, 57/98) of the MOOCs considered were offered on the Coursera platform, and 94% (92/98) of all the MOOCs were offered in English. Universities offered 90 MOOCs, and the John Hopkins University offered the largest number of MOOCs (12/90). Only three MOOCs were offered by developing countries (China, West Indies, and Saudi Arabia). The duration of MOOCs varied from 3-20 weeks with an average length of 6.7 weeks. On average, MOOCs expected a participant to work on the material for 4.2 hours a week. Verified certificates were offered by 14 MOOCs, while three others offered other professional recognition.ConclusionsThe review presents evidence to suggest that MOOCs can be used as a way to provide continuous medical education. It also shows the potential of MOOCs as a means of increasing health literacy among the public.

This study tries to propose a unified model integrating the unified theory of acceptance and use of technology (UTAUT) model, task–technology fit (TTF) model, and user satisfaction to investigate the determinants that affect university students’ continued intention of using massive open online courses (MOOCs). Based on the data of a survey on 464 respondents, structural equation modeling is adopted to assess the model. The results reveal that performance expectancy, effort expectancy, social influence, and user satisfaction are the crucial predictors of university students’ continued intention. TTF has an indirect influence on continued intention through user satisfaction. Performance expectancy is affected both by effort expectancy and TTF. Facilitating conditions do not directly influence continued intention; however, they present indirect influences in that they play a mediating role for user satisfaction. The findings help researchers and practitioners to attain a better understanding of university students’ continued usage intention of MOOCs. The implications and limitations of this study are also described.

This study aims to investigate the influence of interaction on undergraduates’ continuance intention to use Massive Open Online Courses based on the Expectation Confirmation Model (ECM) and to examine the moderating effect of gender. 235 undergraduates were randomly sampled and surveyed, providing self-reports on 10 constructs (student-student interactions, student-teacher interactions, student-content interactions, controllability, responsiveness, confirmation, perceived usefulness, satisfaction, and continuance intention). The Partial Least Squares Structural Equation Modelin was employed for data analysis. The findings indicate that student-teacher interactions, student-content interactions, controllability, and responsiveness have a significant positive impact on undergraduates’ continuance intention to use Massive Open Online Courses. However, student-student interactions do not show a significant relationship with continuance intention. Additionally, no significant gender differences were found concerning the influence of perceived usefulness and satisfaction on continuance intention. The study also discusses the theoretical and practical impacts of undergraduates’ use of Massive Open Online Courses.

Purpose Although Massive Open Online Courses (MOOCs) have experienced unprecedented growth globally, their popularity presents two of education’s greatest challenges today: low completion rates and user retention. This study aims to examine the various factors that influence the continuous usage of MOOCs amongst learners by integrating two theoretical models: The Expectation-Confirmation Model in Information Systems (ECM-IS) and Task-Technology Fit (TTF). The study assesses the impact of information quality, system quality, service quality, confirmation, perceived usefulness and learning satisfaction on long-term continued engagement in MOOCs. Design/methodology/approach Data were obtained from 377 respondents through a structured survey and analysed using partial least squares structural equation modelling (PLS-SEM) to identify factors determining success of MOOC. Findings Findings suggest that information and system quality strongly affect confirmation with subsequent effects on perceived usefulness and learning satisfaction, key antecedents of continuous usage intention. It also indicates that the matching of MOOC platform features with users’ learning tasks (TTF) positively influences satisfaction in learning by promoting subsequent long-term engagement. Originality/value This study provides some theoretical implications on the understanding of MOOC retention and some practical recommendations for MOOC providers in terms of content, system stability as well as support questionnaire adaptability to enhance user experience. Overall, the derived effectuation will offer a deeper understanding of the interconnection of variables that influence persistent usage with implications for practical strategies for sustaining learners in online education platforms.