Massive Open Online Courses Learners Research Articles

Emotionally Engaged Learners Are More Satisfied with Online Courses

Research on massive open online courses (MOOCs) has tended to focus on outcome indicators valued in traditional higher education settings, particularly achievement and completion. This study highlights the differences between MOOCs and credit-bearing university courses and shifts this focus to an alternative outcome indicator—learner satisfaction. In this study, engagement is identified as an important antecedent of learner satisfaction and is conceptualised and operationalised as a multidimensional construct. This study built three regression models to identify the relative importance of behavioural, cognitive, emotional, and social engagement for learner satisfaction after controlling for personal characteristics unrelated to the criteria of good teaching. The analysis showed that engagement explained approximately 20% of the variance in learner satisfaction with MOOCs. Emotional engagement was more influential for predicting learner satisfaction than cognitive engagement and behavioural engagement. Social engagement had no significant effect on learner satisfaction. Demographics (age, education level, and origin) and motivation were of limited utility in predicting learner satisfaction with MOOCs, accounting for 4% and 2% of variance, respectively. Based on research findings, the article presents the following propositions: (1) configure the MOOC teaching and learning environment in a way that enhances emotional engagement; (2) statistically adjust for age, education level, origin, and motivation when interpreting learner satisfaction results; and (3) monitor the level of emotional engagement and implement educational interventions to provide support for emotional disengagers.

A qualitative study to understand the perspectives of MOOC providers on accessibility

Massive open online courses (MOOCs) are widely available and have become a common option for learners. However, their full potential cannot be realised if they are not accessible to all learners, including those with disabilities. It is, therefore, important to understand the different stakeholders and their requirements and perspectives in designing accessible MOOCs. This research investigated the perspectives of MOOC providers on MOOC learners who have accessibility needs and the processes used to manage accessibility and MOOCs in their individual organisations. In this paper, we report the results of a study using thematic analysis, which involved 26 semi-structured interviews with MOOC providers and focused on MOOC accessibility. The results show that, while MOOC providers are aware of learners with accessibility needs who are participating in MOOCs, they prioritise legislation over learners’ accessibility preferences. MOOC providers consider the technology of the platform itself creates barriers and are aware of the limitations for learners in finding help, reporting accessibility barriers and obtaining feedback, when participating in MOOCs.
 Implications for policy and practice:
 
 Course providers should acknowledge MOOC design is being guided by legal requirements. That involves uncertainty to who is the responsible to deliver accessible MOOCs.
 Platform providers need to consider the lack of information about their learners makes it difficult to design educational resources that consider different target groups and provide personalisation.
 Learners can find MOOCs helpful for continuing professional development and lifelong learning. MOOCs are attractive due to their low-cost and self-regulated learning.

MOOC learners' time‐investment patterns and temporal‐learning characteristics

AbstractBackgroundFailure to effectively organize and manage learning time is an important factor influencing online learners' performance. Investigation of time‐investment patterns for online learning will provide educators with useful knowledge of how learners engage in and regulate their online learning and support them in tailoring online course design and teaching. However, understanding of how learners invest and manage their time during online learning remains limited.ObjectivesThis study aims to discover the typical time‐investment patterns of MOOC learners and their temporal‐learning characteristics based on a systematic time‐investment analysis framework and their relationship with learning performance.MethodsBased on a proposed time‐investment‐analysis framework, this study applied statistical, cluster and lag sequential analyses to investigate learners' time‐investment patterns and their relationships with learning performance, session time allocation, and learning sequences by analysing the learning data from 12,463 participants of a Massive Open Online Course (MOOC) in China.Results and ConclusionsSeven time‐investment patterns of MOOC learners were defined, and learning performance was found to differ among them. Further analysis shows that high performers invested time throughout the whole course and allocated time to multiple activities, exam‐takers performed better in time management and produced more behavioural sequences related to cognitive strategy and recourse use, and learners’ motivation and prior knowledge affected the management and effectiveness of their time investment.ImplicationsThe results support the recognition and evaluation of online learning time‐investment patterns and suggest relevant cues for improving MOOC design and teaching.

A preliminary investigation for assessing attention levels forMassive Online Open Courseslearning environment usingEEGsignals: An experimental study

Rapid progress in expansion of the internet services have provided an alternative way for learning other than the traditional classroom learning. Due to the availability of multiple learning options, evaluating each option and judging the best use case plays a vital role. One of the most important characteristics that a human brain utilizes during process of learning is cognition that involves attention and retention. Student's attention span and situational interests during learning have always been a subject matter of research. Apart from classroom learning, e-learning (MOOC based learning) is the other most preferred way of learning. Therefore, the objective of this study is to assess attention levels of a learner in MOOC (Massive Open Online Courses) learning environments and compare it with conventional classroom learning using brain signals. The proposed method captures electroencephalogram (EEG) frequency bands of different subjects while going through a short lecture in MOOC/e-learning environment and classroom environment. The captured data points were annotated for attentiveness manually by referring to the subject's feedback and video clips. Machine learning classification model of support vector machines (SVM) was used to classify student's mental state as attentive or nonattentive. Promising results were obtained and experiments revealed that higher attention levels were maintained during MOOC learning environment in comparison to traditional learning approach.

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

Research on the mechanism of knowledge diffusion in the MOOC learning forum using ERGMs

Undergraduate Students’ Experiences of the Use of MOOCs for Learning at a Cambodian University

Currently, some universities in Cambodia are exploring the usage of Massive Open Online Courses (MOOCs), which can support education by allowing cost-free independent learning for university students. For effective implementation, it is fundamental to understand the current Cambodian ecosystem, how universities implement MOOCs for teaching, and how students use them for learning. Due to a current gap in the literature on this matter, this research work aims to investigate students’ awareness of MOOCs, usage, and difficulties encountered with their adoption for learning. This research work is a case study of a university in Cambodia, and it adopts a mixed-mode approach involving a quantitative questionnaire, followed by qualitative semi-structured interviews. Currently, many students are not aware of MOOCs, and regarding those using them, they report a low level of organized effort, which points out to the fact that students are in general not very organized and systematic in the way they approach learning using MOOCs. Furthermore, a major issue still lies in the way these courses are implemented in the curriculum and the learning activities, underlined by the type of ICTs affordances currently exploited by the usage of MOOCs for learning.

Enhancing MOOC learners’ skills for self-directed learning

ABSTRACT The management of self-directed learning is especially critical for massive open online course (MOOC) learners. This mixed-method study investigated MOOC instructors’ strategies to facilitate learners’ self-management skills for SDL. The study used three data sources: (a) an online survey with 198 MOOC instructors; (b) semi-structured interviews with 22 participants (the primary data source); and (c) document reviews of 22 MOOCs. The quantitative data were analyzed using descriptive statistics, and the qualitative data were analyzed using content analysis. The study findings indicate that MOOC instructors facilitated learners’ self-management skills from four perspectives: the enactment of learning goals (e.g., explanations and appreciation of students’ learning goals); time management (e.g., providing time frames, progress indicators, and short learning units); management of resources and support (e.g., flexible learning resources, peer assessments, and accessibilities); and navigation (e.g., clear organization and video tutorials on navigating the MOOC). The paper discusses the implications for researchers and practitioners.

Online Oral Hygiene Instructions for Orthodontic Patients in Malaysian Population

Fixed orthodontic appliances causes plaque accumulation, which leads to the formation of dental caries and gingivitis. Therefore, concise oral hygiene instructions (OHI) is necessary to avoid the occurrence of these diseases. Massive Open Online Course (MOOC) ensures interactive learning to improve knowledge retention. MOOC transfers the responsibility of learning OHI to the patients with remote guidance from the clinician, thus reduces clinical time. This research aimed to develop the MOOC learning content on OHI in orthodontic practice. The secondary aim was to assess the overall analytics data among learners enrolled for the completion rate and time taken to complete the MOOC. The ADDIE principles which were, "Analyse, Design, Develop, Implement and Evaluate", were used to develop the MOOC. The contents were based on a published pamphlet of OHI from the Ministry of Health, Malaysia. The MOOC was pre-tested, and content was improved based on the feedback from users and experts. The MOOC named “Penjagaan Kebersihan Pendakap Gigi” utilises the Bahasa Melayu language to educate learners regarding oral care with orthodontic appliances. Sixty-two learners joined the MOOC, with 77.4% achieving a high rate of completion of the MOOC learning content. There were forty-six female learners (74.2%), while male learners comprised sixteen (25.8%). The median (interquartile range) time taken to complete MOOC learning content were 31.50 minutes, (13.00 minutes to 55.50 minutes). This shows that MOOC could be an alternative platform to instruct patients on OHI with fixed appliances. MOOC can potentially reduce clinical time to teach OHI to patients.

Linking web-based learning self-efficacy and learning engagement in MOOCs: The role of online academic hardiness

Even though Massive Open Online Courses (MOOCs) have created highly personalized and dynamic learning environments for higher education, the low completion rate has hampered their development. Nevertheless, how to engage MOOC learners in continuing to learn online remains unclear in terms of psychological mechanisms. Enlightened by the social cognitive view of learning and hardiness theory, this study investigates the mediating role of online academic hardiness (the courage that is needed to turn stressful changes from burdens into advantageous growth in online environments) between web-based learning self-efficacy (the specific beliefs that people have in their capability to complete tasks when learning online) and online learning engagement. Using validated self-reported scales, a total of 608 participants of six MOOCs courses from Taiwan were included in this study. The results of structural equation modeling indicated the significant mediating effect of commitment on behavioral, emotional and cognitive engagement in learning MOOCs. Additionally, we found that the components of web-based learning self-efficacy led to different types of engagement: general Internet-based learning self-efficacy contributes to behavioral and emotional engagement, whereas functional Internet-based learning self-efficacy contributes to emotional and cognitive engagement. The direct and indirect effects of web-based learning self-efficacy highlight its critical role in online learning engagement. Overall, our conceptual model based on the agentic view of social cognitive theory provides researchers and practitioners with a holistic picture to understand the MOOC engagement phenomenon by revealing mixed results compared to traditional distance education.

Massive Open Online Course Fast Adaptable Computer Engineering Education Model

Massive Open Online Course (MOOC) is a new online education model that provides new opportunities and challenges for the development and reform of teaching in colleges and universities. This paper first builds a MOOC-based model of influencing factors of blended learning adaptability. Through investigation and research, it is found that the six influencing factors all have different ways and different degrees of influence on learning adaptability. Among them, learning motivation has a direct and significant impact on learning adaptability, and learning self-efficacy not only has a direct and significant impact on learning adaptability but also has an indirect impact on learning adaptability through learning motivation. Teacher teaching has indirect effects on learning adaptability through learning self-efficacy, learning motivation, and learning support. Learning support not only has a direct and significant impact on learning adaptability but also has an indirect impact on learning adaptability through learning motivation. MOOC platform has a direct and significant impact on learning adaptability. The quality of course content has a direct and significant impact on learning adaptability through the MOOC platform and learning motivation. The creative results of this research are mainly embodied in the combination of theory and practice, exploring and forming related results based on MOOC-based college students’ learning adaptability. According to the MOOC-based learning-adaptive intervention model, teaching practice is carried out to verify the effect of the intervention model from two aspects of student procedural performance and result performance. Finally, in view of the problems existing in traditional computer teaching in colleges and universities, combined with the design ideas and basic characteristics of MOOC, the teaching mode reform of computer courses is analyzed and discussed, and a MOOC-based computer engineering education teaching mode is proposed.

Learning Analytics to Reveal Links Between Learning Design and Self-Regulated Learning

The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of learning analytics (LA), shows that SRL skills are best exhibited in choices of learning tactics that are reflective of metacognitive control and monitoring. However, in spite of high significance for evaluation of learning experience, the link between learning design and learning tactics has been under-explored. In order to fill this gap, this paper proposes a novel learning analytic method that combines three data analytic techniques, including a cluster analysis, a process mining technique, and an epistemic network analysis. The proposed method was applied to a dataset collected in a massive open online course (MOOC) on teaching in flipped classrooms which was offered on a Chinese MOOC platform to pre- and in-service teachers. The results showed that the application of the approach detected four learning tactics (Search oriented, Content and assessment oriented, Content oriented and Assessment oriented) which were used by MOOC learners. The analysis of tactics’ usage across learning sessions revealed that learners from different performance groups had different priorities. The study also showed that learning tactics shaped by instructional cues were embedded in different units of study in MOOC. The learners from a high-performance group showed a high level of regulation through strong alignment of the choices of learning tactics with tasks provided in the learning design. The paper also provides a discussion about implications of research and practice.

Adaptive learning module for a conversational agent to support MOOC learners

Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that complements a MOOC on Java programming, helping learners review the key concepts of the MOOC. This adaptive learning module adapts the difficulty of the questions provided to learners considering their level of knowledge using item response theory (IRT) and also provides recommendations of video fragments extracted from the MOOC for when learners fail questions. The adaptive learning module for JavaPAL has been evaluated showing good usability and learnability through the system usability scale (SUS), reasonably suitable video fragments recommendations for learners, and useful visualisations generated as part of the IRT-based adaptation of questions for instructors to better understand what is happening in the course, to design exams, and to redesign the course content.

Examining the Influence of Teaching Presence and Task-Technology Fit on Continuance Intention to Use MOOCs

This study aimed to examine the structural relationships among factors that affect learners’ continuance intention to use Massive Open Online Courses (MOOCs). Drawing upon the Technology Acceptance Model (TAM), it posited teaching presence and task-technology fit as exogenous variables, examining how they affect continuance intention to use MOOCs, mediated by perceived usefulness and perceived ease of use. Based on survey data from 252 Korean MOOC learners, structural equation modeling was employed to assess the model. The results indicated that perceived usefulness affected continuance intention to use, while perceived ease of use did not; however, perceived ease of use did affect perceived usefulness. Further, teaching presence was not significantly related to continuance intention to use or perceived usefulness, but did affect perceived ease of use. However, task-technology fit affected perceived usefulness, perceived ease of use, and continuance intention to use. Finally, the mediating role of perceived usefulness and perceived ease of use on the relationships between teaching presence as well as task-technology fit and continuance intention were confirmed. Implications were suggested for designing courses in MOOCs to increase continuance intention to use.

Assessing the Psychometric Properties of Students’ MOOC-Efficacy Measurement Model

Massive Open Online Courses (MOOCs) have been identified as a potential innovation for improving teaching and learning. This research aims to develop and evaluate a measurement model of students’ MOOC-efficacy. The study conceptualized students’ MOOC-efficacy in four dimensions of information searching, making queries, MOOC learning, and MOOC usability. Data were collected with a 23 items questionnaire whose reliability indexes ranged from 0.822 to 0.890, identified from university students who have had some experience with MOOCs and who willingly volunteered to participate in the research (N=1,524). A sample of 623 respondents was drawn through simple random sampling. The Confirmatory Factor Analysis (CFA) was adopted for data analysis. The findings designate that four-dimensional students’ MOOC-efficacy measurement model achieved an acceptable level of fit (RMSEA = 0.061, CFI = 0.935 and a normed chi-square, χ2/df = 3.322). All statistics provide empirical evidence that the students’ MOOC-efficacy measurement model is psychometrically sound in terms of validity and reliability. The measurement model of students’ MOOC-efficacy provides further insights into what works in an open online environment which may be used to fulfill learners’ needs and preferences.

Persistence, performance, and goal setting in massive open online courses

AbstractGoal setting is an important component in successful teaching and learning, but relatively little is known about its impact on course persistence and achievement in massive open online courses. Using an experimental design and employing a variety of data including student writings, content‐related assignment attempts, and quantitative achievement in the courses, we compared the outcomes of two groups of learners who were given different writing prompts at the beginning of their course. While no overall effects of writing prompt type on the dependent variables were observed, highly statistically significant differences were found when goal writings were more closely examined and compared via qualitative coding. When learners’ written responses to prompts contained either learning or performance goals, those participants both achieved more and engaged in learning longer than participants whose written responses did not fall into either of these categories. Practitioner notesWhat is already known about this topic Goals are related to students’ behaviors and performance. Performance goals’ influences on learning have inconsistent results, while learning goals are considered beneficial. What this paper adds The effects of conscious goal setting in massive open online courses (MOOCs) may be different from traditional learning contexts. Having either learning and performance goals results in better persistence and performance than not having these goals. Implications for practice and/or policy More interventions should be designed to help MOOC learners set and commit to their goals. Use MOOC learner's learning and performance goals to promote learning and persistence.

Rethinking A Framework for Contextualising and Collaborating in MOOCs by Higher Education Institutions in Africa

Massive Open Online Courses (MOOCs) are online courses that are open to anyone with Internet access. Pioneered in North America, they were developed for contexts with broader access to technology and wider access to the Internet. As globally networked learning environments (GNLEs), MOOCs foster collaborative communities and learning in ways not conceived as feasible until recently. The affordances of MOOCs, such as the ability to access learning beyond one’s immediacy, exemplify their benefits for open and distance learning, especially in developing countries that continue to consume rather than produce online courses. However, the globality of MOOCs and their delivery mode pose a challenge of contextualising learning content to the local needs of educational institutions or individual students that choose to use the courses. This theoretical paper used a desk-research approach by revising literature to investigate and propose ways of contextualising MOOCs to the African higher education setting. It applied the principles of reuse and repurposing learning content, while suggesting the use of mobile learning as a technological delivery solution that is relevant to the local context. The paper also suggests a framework for inter-institutional collaboration for higher education institutions to guide future efforts in the creation and sharing of credit-bearing MOOCs.

Analyzing Large Collections of Open-Ended Feedback From MOOC Learners Using LDA Topic Modeling and Qualitative Analysis

There is a large variation in background and purpose of massive open online course (MOOC) learners. To improve the overall MOOC learning experience, it is important to identify which MOOC characteristics are most important for learners. For this purpose, in this article, we analyzed about 150 000 open-ended learner responses from 810 MOOCs to three postcourse survey questions about their learning experience: (Q1) What was your most favorite part and why? (Q2) What your least favorite part and why? (Q3) How could the course be improved? We used the latent Dirichlet allocation topic model to identify prominent topics present in learner responses to each question. We determined the theme of each identified topic through qualitative analysis. Our results show that the following aspects of MOOCs can significantly impact the learning experience: quality of course content, accurate description of prerequisites and required time commitment in course syllabus, quality of assessment and feedback, meaningful interaction with peers and educators, engaging instructor and videos, accessibility of learning materials, and usability of platform.

Analysing self-regulated learning strategies of MOOC learners through self-reported data

Massive open online courses (MOOCs) require registered learners to be autonomous in their learning. Nevertheless, prior research studies showed that many learners lack the necessary self-regulated learning (SRL) skills to succeed in MOOCs. This research study aimed to gain insights into the relationships that exist between SRL and background information from MOOC learners. To this end, a series of three MOOCs on computer programming offered through edX were used to collect self-reported data from learners using an adaptation of the Motivated Strategies for Learning Questionnaire. Results show significant differences in general learning strategies and motivation by continent, prior computing experience and percentage of completed MOOCs. Men reported higher motivation than women, whereas pre-university learners needed further guidance to improve their learning strategies.

An investigation of under-represented MOOC populations: motivation, self-regulation and grit among 2-year college students in Korea

Educators have raised concerns that massive open online courses (MOOCs) mainly serve the interests of advantaged groups. In response, this study examined underrepresented MOOC learners; namely, 2-year college students in South Korea in terms of their perceptions of MOOCs and learning readiness for MOOCs. A total of 119 Korean 2-year college students participated in the survey and their responses were analyzed. Research findings revealed that approximately 90% of participants were unaware of MOOCs, and few students had previously taken a MOOC. These results indicate that it is necessary to advertise MOOCs effectively to underrepresented learners. Importantly, most participants were optimistic about the effects of MOOCs for individual development. Some learners, however, were concerned about their lack of commitment or low self-regulation to complete MOOCs. In terms of intrinsic and extrinsic motivation, grit, and self-regulation, the learning readiness of 2-year college students for MOOCs was moderate. Additionally, 2-year college students preferred MOOCs with practical content offered in short study periods, and they emphasized extrinsic motivators over intrinsic ones.

Exploring the structural relationships between course design factors, learner commitment, self-directed learning, and intentions for further learning in a self-paced MOOC

The open and massive characteristics of Massive Open Online Course (MOOC) lead to a lack of instructor presence, which potentially hinders learners' commitment and learning processes. As a result, the effectiveness of MOOCs is contingent upon the extent to which learners direct their own learning. However, learners' self-directed learning and commitment are largely influenced by course design factors due to lack of direct learner-instructor interactions. In order to address the current gap in the literature with regard to how course design factors influence learning processes and outcomes, this study investigated the relationships between MOOC design factors, learner commitment, self-directed learning, and intentions for future learning, using survey responses collected from 664 learners who took a large-scale MOOC. We found that the transactional distance between learners and content was associated with students' self-directed learning. Course structure and organization predicted both students' self-directed learning and commitment to the MOOC. Importantly, self-directed learning mediated relationships between the course design factors and learners’ intentions for further learning. Based on our findings, we provide design strategies for effective learner-content interaction in large-scale self-paced MOOCs.