Article

Learner support in MOOCs: Identifying variables linked to completion

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Abstract

This study investigated learner support strategies that enable the success and completion of Massive Open Online Courses (MOOCs). It examined five MOOCs categorised into three groups according to their pedagogical approach and used in different learning settings: formal MOOCs, conventional MOOCs and professional MOOCs. A total of 4,202,974 units of variables (student behaviours and MOOC features) were analysed using Semi-Supervised Extreme Learning Machine (SSELM) and Global Sensitivity Analysis. In this study, the use of SSELM was compared to the state-of-art models (e.g. ELM, KELM, OP-ELM, PCA-ELM), and SSELM yielded 97.24% accuracy. Using unlabelled students helped improve the learning accuracy for the model, which confirms that SSELM is a good model to predict completion in MOOCs, considering the difficulty of labelling students in such an open and flexible learning environment. The findings show that designers and teachers should pay special attention to their students during the second quartile of the course (independently of the type of MOOC). The teachers’ presence during the course, his or her interactions with students and the quality of the videos presented are significant determinants of course completion.

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... Participants who complete a course are often regarded as persistent or successful learners, and their prevalence is frequently used to assess the quality of a course. As a result, high dropout rates are treated as a sign of deficient quality, which has yielded ample studies that identify the variables associated with dropout or completion rates (e.g., Gregori, Zhang, Galván-Fernández, & Fernández-Navarro, 2018;Pursel, Zhang, Jablokow, Choi, & Velegol, 2016;Romero-Rodriguez, Ramirez-Montoya, & Gonzalez, 2019). Currently, dropout studies are associated with personal intention and goals, design interventions and learning strategies, emphasising social aspects of learning and interactions in diverse academic settings and contexts. ...
... High dropout rates have become the greatest challenge for MOOCs (Brown, Costello, Donlon, & Giolla-Mhichil, 2015;Gregori et al., 2018;Littlejohn, Hood, Milligan, & Mustain, 2016). In higher education, the definition of a dropout dates back to the work of Tinto (1975), who defines college dropouts in 'Dropout from higher education: A theoretical synthesis of recent research' as students who leave without receiving an end qualification and students who attend one or more educational institutions but never receive an end qualification from any of them. ...
... Similarly, more studies have reported that the duration of course activity is the core factor influencing high dropout rates (Jiang, Williams, Schenke, Warschauer, & Dowd, 2014;Kloft, Stiehler, Zheng, & Pinkwart, 2014). In addition to course length, course design factors were explored using teachers' presence (Hone & Said, 2016) and accessibility (Hew, 2016), assessment and feedback (Bonk et al., 2018;Olivé, Huynh, Reynolds, Dougiamas, & Wiese, 2020), learner support (Gregori et al., 2018), and gamification (Romero-Rodriguez et al., 2019). In addition, a group of researchers (e.g., Rosé et al., 2014;Wang, Guo, He, & Wu, 2019;) attributed high dropout rates to interactions with instructors and peers, which highlights the importance of the social aspect of MOOC learning. ...
Article
Understanding the dropout phenomenon has advanced from viewing it as a sign of deficient quality to viewing it as an explicit sign of individual choice, which highlights the importance of investigating how dropouts learn in massive open online courses (MOOCs). Nevertheless, the short, limited and heterogeneous behaviours of individual dropouts create challenges for understanding how dropouts learn over time. Taking a systematic network perspective, this study used clickstream data to build a flow network model of collective attention to investigate how dropouts learn in XuetangX's Introduction to Psychology (2018 autumn). The results showed that the quantification of behavioural data presented a stereotypical image of dropouts, but the network analytics presented a rather different picture of how dropouts learn. Recognising the distinct roles of introductory learning resources could prevent dropping out and improve the accuracy of prediction models. Interestingly, the assessments embedded in the MOOCs performed a scaffolding role in guiding dropouts to learn. Thus, redesigning quizzes or examinations in open and flexible learning environments to construct a minimum cost network of collective attention is vital to making this online space cost effective for learners at risk.
... 77). This finding was confirmed by the literature, where researchers identified several insufficiencies of MOOCs in terms of learner support (Gregori et al., 2018), difficulty level (De Freitas et al., 2015), social presence (Poquet et al., 2018), pedagogical orientation (Toven-Lindsey et al., 2015), and learning assessment (Cooper & Sahami, 2013). These insufficiencies highlight the necessity of developing accurate tools for the diagnostic evaluation of MOOCs. ...
... Despite their scalability and affordability, MOOCs are online courses designed for autonomous learning (Gregori et al., 2018). Therefore, existing quality standards for online courses might apply to MOOC evaluation, as well. ...
... Contrary to the large number of positive comments on the standard of acquisition of knowledge & skills (B41), only a few testimonies of self-regulatory and metacognitive skill development were identified during DME, due to which acquisition of learning method (B42) was the lowest rated standard. This finding supports the general belief that most MOOCs continue to be lecture or content-based courses (Gregori et al., 2018;Toven-Lindsey et al., 2015), due to which they fail to promote the development of high-level cognitive skills, such as reflective metacognition and self-regulation, among their learners (Terras & Ramsay, 2015). ...
Article
The proliferation of massive open online courses (MOOCs) highlights the necessity of developing accurate and diagnostic evaluation methods to assess the courses' quality and effectiveness. Hence, this study proposes a diagnostic MOOC evaluation (DME) method that combines the Analytic Hierarchy Process algorithm and learner review mining to integrate expert opinions, standardized rubrics, and learner feedback into the evaluation process. For this purpose, 30 MOOCs from the Coursera website were purposively selected and evaluated using the DME method and the results compared with expert evaluation and learner rating scores. The preliminary findings, in general, support the feasibility, accuracy, and diagnostic utility of the DME method and its suitability as a low-cost, sophisticated, and accurate method for MOOC evaluation. Finally, the study discusses several limitations and technical issues of the DME method that should be addressed in future research and practice.
... Open e-learning refers to the delivery of educational content to students through open access platforms made freely available online (Daniel, 2012;Gregori, Zhang, Galván-Fernández, & de Asís Fernández-Navarro, 2018;Labarthe, Bouchet, Bachelet, & Yacef, 2016). In contrast to 'closed' e-learning platforms where access is contingent on the student satisfying eligibility criteria and paying registration fees, open e-learning platforms are typically available to anyone with an interest in the topic, on a voluntary and cost-free basis. ...
... In contrast to 'closed' e-learning platforms where access is contingent on the student satisfying eligibility criteria and paying registration fees, open e-learning platforms are typically available to anyone with an interest in the topic, on a voluntary and cost-free basis. Open e-learning platforms such as Massive Open Online Courses (MOOCs) are an increasingly prevalent medium of education and training delivery in which information, knowledge, and instruction are openly disseminated through online media to diverse user groups (Cidral, Oliveira, Di Felice, & Aparicio, 2018;Daniel, 2012;Gregori et al., 2018;Labarthe et al., 2016;W.-S. Lin & Wang, 2012). ...
... However, evidence suggests that open e-learning users often disengage and do not progress to completion, with drop-out rates cited as high as 97% (Hew & Cheung, 2014). One explanation for this centres on the diversity of user profiles where individuals from different educational, geographic, and socio-economic backgrounds are attracted to open e-learning by the low barriers to registration (Cidral et al., 2018;Daniel, 2012;Gregori et al., 2018;Labarthe et al., 2016;W.-S. Lin & Wang, 2012). ...
Conference Paper
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Recorded usage rates of open e-learning platforms are often low, with many users discontinuing their use after initial acceptance. One often cited reason for this acceptance-discontinuance anomaly is the design-reality gap between users’ diverse needs and the designed features of an open e-learning platform. To explore the challenges of user continuance behaviour we adopt the lens of ‘functional affordances’, the possibilities for action that an open IT artefact provides users for achieving individual and collective goals. We investigate the design implications of user-perceived affordances based on findings from an EU sustainability project which developed an open e-learning platform for citizens to improve household energy efficiency. Findings showcase how open e-learning users and designers perceive seven interrelated affordances differently: Informing, Assessment, Synthesis, Emphasis, Accessibility, Navigation, and Goal-planning. We put forward recommendations on how designers of open IT artefacts can bridge design-reality gaps by exploring affordance personalisation for diverse user groups.
... MOOCs (Massive Open Online Courses) have the potential to provide access to highquality education beyond social and geographical restrictions [1,2], allowing learners to learn at their own pace [3,4], from anywhere [3], at any time [4] and free of charge [5]. MOOCs also create opportunities for professional development [6] and participation in top university courses [4]. ...
... Learning in MOOCs often takes place autonomously, away from other learners and organizers [5]. The low completion rate is a significant challenge for MOOC organizers [4,9]. ...
... It is concluded that the number of learners who completed learning activities decreased each week [8,10]. Multiple MOOCs lasting 6-10 weeks have shown that the dropout rate was high before or at the mid-point of the course [2,4] or after the second quartile, usually during the second or third week or module [5]. Other studies have found that dropouts in the case of 4-11-week MOOCs is most problematic at the start of the course [1,11], especially in the first week [11]. ...
Article
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One of the problems regarding MOOCs (Massive Open Online Courses) is the high dropout rate. Although dropout periods have been studied, there is still a lack of understanding of how dropout differs for MOOCs with different levels of difficulty. A quantitative study was conducted to determine the periods with the highest dropouts in computer programming MOOCs and the performance of the dropouts on the course before dropping out. Four occurrences of three MOOCs, with different durations, difficulty of the topic, and the degree of supportive methods, were included. The results showed that dropout was highest at the beginning of all studied courses. Learners also dropped out before the project. In the easier and shorter courses, most dropouts were successful until they quit the course. In longer and more difficult courses, learners mainly dropped out in the week they started due to experiencing problems with the course activities. It is suggested to recommend that learners take courses at a level that suits them if their current course is too easy or difficult and encourage learners to use course resources for help. It would be a good idea to provide learners with example topics to assist them in starting with a project.
... Awarding digital badges and other gamification elements to stimulate motivation and offering course completion certificates x Bonafini et al. [13] x Labarthe et al. [63] x Borrás-Gené et al. [14] x Sharif and Guilland [93] x Sun and Bin [95] x Cook et al. [26] x Cassidy et al. [18] x Crosslin et al. [29] x Khalil et al. [58] x Petronzi and Hadi [79] x Zheng et al. [120] x Ferguson and Clow [37] x Chang and Wei [21] x Rodriguez et al. [85] x Walji et al. [105] x Lu et al. [68] x Vaibhav and Gupta [104] x Sunar et al. [97] x Perez-Alvarez et al. [78] x Dubbaka and Gopalan [36] x Anutariya and Thongsuntia [4] x Ramesh et al. [82] x Kaveri et al. [55] x Floratos et al. [40] x Romero-Rodriguez et al. [86] x Jung and Lee [54] x Li and Baker [66] x Williams et al. [112] x Phan et al. [80] x Barak et al. [11] x Gregori et al. [44] x Gallego-Romero et al. [41] x Lan and Hew [64] x Alharbi et al. [2] x Balasooriya et al. [9] x Rizzardini and Amado-Salvatierra [83] x Khalil and Ebner [57] x Goldberg et al. [42] x Rebecca Ferguson et al. [39] x Antonaci et al. [3] x Shi and Cristea [94] x (continued on next page) A.A. Ogunyemi et al. the various actions taking place during the activity, broadly classifying them into instructional and platform design. Instructional design process indicators are course-based. ...
... Additionally, video is a predominant pedagogical tool in terms of interactions with learning materials in MOOC environments. High-quality videos are imperative for fostering learners' interaction [44,115] but not sufficient for course completion [13]. Nevertheless, learners' participation increased as MOOC offerings progressed [44]. ...
... High-quality videos are imperative for fostering learners' interaction [44,115] but not sufficient for course completion [13]. Nevertheless, learners' participation increased as MOOC offerings progressed [44]. Summarising the discourse on learners' participation, Bonafini et al. [13] recommend that MOOC designers and instructors design forum discussions so that learners can exhibit critical thinking using relevant interaction prompts to foster sharing of complex concepts learned in courses. ...
Article
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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.
... Massive open online courses (MOOCs) have enjoyed increasing popularity in the world for the last 10 years (1)(2)(3)(4)(5)(6), and with the growth of the Internet and educational technologies, the number of people joining MOOCs is increasing every day (1,6,7). According to the European open training report, which provides MOOC-related statistics in European countries, there was a 130% increase in the number of MOOCs from September 2014 to September 2015 (8). ...
... Massive open online courses (MOOCs) have enjoyed increasing popularity in the world for the last 10 years (1)(2)(3)(4)(5)(6), and with the growth of the Internet and educational technologies, the number of people joining MOOCs is increasing every day (1,6,7). According to the European open training report, which provides MOOC-related statistics in European countries, there was a 130% increase in the number of MOOCs from September 2014 to September 2015 (8). ...
Preprint
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Background Recently, massive open online courses (MOOCs) have received increasing popularity throughout the world. Regardless of the subject taught and the university providing the course, the dropout rate of MOOCs is one of the most important challenges ahead. Methods This systematic review will search MEDLINE/PubMed, Scopus, Web of Science (Clarivate Analytics), Embase (Embase.com), ASSIA, CINAHL, Education Research, BEI, and Eric databases systematically according to predefined criteria without language restrictions to retrieve prospective and retrospective observational studies conducted between the 1st of January 2000 and 30th of March 2020 which evaluated the frequency of leaving MOOCs throughout the world. In the absence of severe methodological heterogeneity, the data will be combined and a meta-analysis will be performed. Discussion As dropout rate is one of the most challenges that universities may encounter, this systematic review will help universities extend their view, save their resources or maybe design their MOOCs differently. Registration Registered in Open Science Framework, available at: https://osf.io/jgyqx/
... It is well documented that factors, such as unreliable internet, difficulties accessing appropriate computing and technology, and distracting home environments, present barriers to students' online learning (Peña-López, 2015; Australian Academy of Science, 2020). In relation to job resources, online learning support refers to the quality of the online learning resources and learning opportunities made available to students by their schools (Yukselturk and Bulut, 2007;Means et al., 2009;Escueta et al., 2017;Gregori et al., 2018;AITSL, 2020). The other job resource is parent/home help, which refers to the extent to which parents provide help with schoolwork and the necessary routines and resources are available at home to assist learning (Galpin and Taylor, 2018). ...
... We showed that job demands by way of online learning barriers were associated with lower online learning self-efficacy (consistent with research showing such barriers impede online learning; e.g., Peña-López, 2015; Australian Academy of Science, 2020). We also showed that job resources by way of online learning support and parent/ home help were associated with higher online learning selfefficacy (consistent with prior research demonstrating a supportive role for these factors; e.g., Yukselturk and Bulut, 2007;Means et al., 2009;Escueta et al., 2017;Galpin and Taylor, 2018;Gregori et al., 2018;AITSL, 2020). ...
Article
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The present study investigated the role of adaptability in helping high school students navigate their online learning during a period of COVID-19 that entailed fully or partially remote online learning. Drawing on Job Demands-Resources (JD-R) theory and data from a sample of 1,548 Australian high school students in 9 schools, we examined the role of adaptability in predicting students’ online learning self-efficacy in mathematics and their end of year mathematics achievement. It was found that beyond the effects of online learning demands, online and parental learning support, and background attributes, adaptability was significantly associated with higher levels of online learning self-efficacy and with gains in later achievement; online learning self-efficacy was also significantly associated with gains in achievement—and significantly mediated the relationship between adaptability and achievement. These findings confirm the role of adaptability as an important personal resource that can help students in their online learning, including through periods of remote instruction, such as during COVID-19.
... Despite the acknowledged impact of feedback on learning and engagement [1], Massive Open Online Courses (MOOCs) represent a learning context where delivering timely and personalized feedback regards an ongoing challenge [2], [3]. Specifically, the wide instructor-learners ratio renders difficult the manual provision of interventions that satisfy the learners' needs [4]. ...
... VI. DISCUSSION AND CONLUSIONS Acknowledging the challenge of the provision of effective feedback in MOOC settings [2], [3], the current paper explores how MOOC instructors can be supported in the design of feedback interventions considering course design aspects. To that end, we introduced FeeD4Mi and FeeD4MiTool, a conceptual and a technological tool to guide instructions in the design and delivery of feedback in MOOCs. ...
... In such an environment, each student works autonomously, students do not know their peers' performance, and students are allowed to quit. Therefore, being self-driven is very important for MOOC learners to progress through the course [24]. Whether personal name disclosure still plays the role of such a selfdriven force in a noncompetitive learning environment needs to be examined. ...
... If the learner responds that he or she is often disturbed by something else or feels helpless, then we may inquire if he or she is interested in disclosing a personal name. If we can take all means to make a certification earner feel that he or she is taken care of, then he or she may have more chances to adhere to his or her primary goal [24]. Furthermore, all these suggested actions can be easily selected when the primary criterion is simple: whether the learner's screen name discloses a personal name. ...
Article
Full-text available
The anonymity of the Internet used to be considered as an encouraging factor that helped learners engage in online learning. However, academic studies on anonymity have found that its effect on learning is context-dependent or mixed. In this research, we focused on massive open online course (MOOC) learners’ preference for personal name disclosure in their screen names as a predictor of their final achievement levels (FALs) at the end of a course including 2606 active learners. We conducted two studies, one to examine the associations between these two variables and one to demonstrate how such associations can be utilized in MOOC FAL prediction. We found that MOOC learners who included personal names in their MOOC screen names significantly outperformed other learners in their FALs (p < 0.001). We also found that screen name preference improved FAL prediction accuracy utilizing natural language processing and proper machine learning technologies. The error rate was reduced to 4.03% by a random forest algorithm with an appropriate feature combination: the personal name disclosure indicator (PNDI), quiz scores, number of replies, and exam scores. The results are potentially useful for the development of an early intervention to provide different types of help to students who prefer to disclose personal names and those who do not. The practical effects of these interventions will be examined in the future. In addition, whether the course difficulty level or course type affects the associations between personal name disclosure and FAL will also be examined.
... According to the European Commission on Education and Culture, countries like Poland, Sweden, and Hungary have dropout rates in higher education of 38%, 47%, and 47%, respectively [11]. In Spain, the dropout rate is 50% at the Spanish National Distance Education University (UNED) [12]. In Brazil, the enrolment numbers significantly increased in the last few years, but student dropout rates simultaneously increased. ...
Article
Full-text available
Contemporary education is a vast field that is concerned with the performance of education systems. In a formal e-learning context, student dropout is considered one of the main problems and has received much attention from the learning analytics research community, which has reported several approaches to the development of models for the early prediction of at-risk students. However, maximizing the results obtained by predictions is a considerable challenge. In this work, we developed a solution using only students’ interactions with the virtual learning environment and its derivative features for early predict at-risk students in a Brazilian distance technical high school course that is 103 weeks in duration. To maximize results, we developed an elitist genetic algorithm based on Darwin’s theory of natural selection for hyperparameter tuning. With the application of the proposed technique, we predicted the student at risk with an Area Under the Receiver Operating Characteristic Curve (AUROC) above 0.75 in the initial weeks of a course. The results demonstrate the viability of applying interaction count and derivative features to generate prediction models in contexts where access to demographic data is restricted. The application of a genetic algorithm to the tuning of hyperparameters classifiers can increase their performance in comparison with other techniques.
... To tackle this challenge, past research efforts include those aiming at understanding students' dropouts, completion, motivation and engagement [3,8,9,22]. However, by looking mainly into overall behavior, they may have missed patterns related to student diversity. ...
Preprint
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Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of students. The advent of complex "big data" from MOOC platforms is a challenging yet rewarding opportunity to deeply understand how students are engaged in MOOCs. Past research, looking mainly into overall behavior, may have missed patterns related to student diversity. Using a large dataset from a MOOC offered by FutureLearn, we delve into a new way of investigating hidden patterns through both machine learning and statistical modelling. In this paper, we report on clustering analysis of student activities and comparative analysis on both behavioral patterns and demographical patterns between student subpopulations in the MOOC. Our approach allows for a deeper understanding of how MOOC students behave and achieve. Our findings may be used to design adaptive strategies towards an enhanced MOOC experience
... MOOCs learners can interact and communicate in a MOOCs course learning forum. Research has found that the number of postings in a MOOCs course learning forum has a positive impact on the course completion rate [22]; the openness and reputation of the MOOCs curriculum have a significant positive impact on the willingness of learners to continue learning. The better the reputations of the MOOCs are, the stronger the willingness of a learner to continue learning [10]. ...
Article
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MOOCs (Massive Open Online Courses) users continue to rise in number globally, and accordingly, the electronic word of mouth (eWOM) for MOOCs is an important source of information for MOOCs learners, but research on the effects of MOOCs eWOM is still lacking. Therefore, from the perspective of group size and group recognition in the MOOCs online review forum and the internal relationships in the MOOCs course learning forum, this paper studies the influence mechanism of MOOCs eWOM on the number of registrations and completions. First, according to the literature review, based on the number of online reviews, the online rating valence and eWOM publishers in the MOOCs online review forum, as well as the number of posts and the number of teaching assistants in the MOOCs course learning forum, research hypotheses are proposed in this study to construct a conceptual model. Second, Coursera is the typical MOOCs platform that is selected as the research object to obtain data from November 2018 to August 2019. Third, after preprocessing the data, on the basis of the Hausman test, the corresponding fixed effect of an econometric model is established, and Stata is used to process the data to verify the research hypotheses. Finally, according to the research conclusions related to eWOM, to improve the number of registrations and completions of MOOCs, development suggestions are proposed for MOOCs platform providers and MOOCs course providers, as well.
... However, the literature on employees' technology usage behaviors at educational institutions is scarce (Scherer et al., 2019). In blended learning environments with online systems, the teacher must continue to provide active consultation (Gregori et al., 2018), and hence their continued technology use is imperative. ...
Article
Full-text available
Technology permeates all walks of life. It has emerged as a global facilitator to improve learning and training, alleviating the temporal and spatial limitations of traditional learning systems. It is imperative to identify enablers or inhibitors of technology adoption by employees for sustainable change in education management systems. Using the theoretical lens of organizational support theory, this paper studies effect of institutional support on education management information systems use along with two individual traits of self-efficacy and innovative behavior of academic employees in British higher educational institutions. Data for this cross-sectional study were collected through a questionnaire completed by 591 academic employees of 23 universities from 10 cities in the United Kingdom. Partial Least Square structural equation modeling was used to analyze data with smartPLS 3.2.9 software. Results indicate that institutional support promotes self-efficacy and innovative behavior that help develop positive employee perceptions. The model explains a 55.2% variance in intention to use. Post-hoc mediation analysis shows that innovativeness and self-efficacy mediate between institutional support and employee technology adoption behavior. As opposed to student samples in past studies on educational technology, this study adds to the literature by focusing on academic employees.
... Other researchers have investigated MOOCs in terms of usability, quality and design (Loizzo & Ertmer, 2016;Gregori et al., 2018;Kumar & Al-Samarraie, 2018) as well as the users' responses and behaviors related to the adoption of technology (Chang, Hung & Lin, 2015;Nordin;Norman, & Embi, 2015;Liu, Brown & Lynch, 2016;Joo;So & Kim, 2018). From the perspective of business and economics, research has also been performed to explore MOOCs business models and their potential to disrupt the higher education sector (Kalman, 2014;Belleflamme & Jacqmin, 2016). ...
... At the end of 2019, there were more than 13,000 massive open online courses (MOOCs) offered in different fields and the number of learners exceeded 110 million (Shah, 2019). Compared to traditional courses learners of MOOCs are expected to have good self-regulation skills and be able to solve arisen difficulties themselves as teachers are physically absent (Gregori et al, 2018). The learners in programming MOOCs face additional, fieldspecific difficulties, such as orientation in language syntax, writing code to solve a task, finding bugs (Lahtinen, Ala-Mutka and Järvinen, 2005;Lawan et al, 2009;Tan, Ting and Ling, 2009). ...
Chapter
Participation in Massive Open Online Courses (MOOCs) allows people to discover new areas and improve knowledge about a specific field. Instructors provide various course materials using different teaching methods and offering a variety of activities to engage learners in the learning process. Learners are expected to have good self-regulation skills and be able to solve arisen difficulties themselves. To understand what actions were taken by learners to overcome difficulties with solving programming exercises, we collected responses from 580 completers who successfully passed a MOOC “About programming”. Learners were asked to specify from whom they got help, what resources they used to resolve difficulties, and what was their planned and actual time investment. We also collected demographic and social characteristics. K-means cluster analysis was employed to study actions taken by completers and to reveal clusters based on actions taken to resolve difficulties. Re-reading of learning materials was one of the most taken action in each cluster. However, each of the five identified clusters has a set of actions preferred by completers in the face of difficulties in programming exercises. It was found that taken actions are not related to age, education level and employment status but previous experience with webbased education and learning programming play a role in a choice and activity of taken actions. Most of completers overestimated time investment. The results can be useful for MOOC instructors who can recommend a particular group struggling with difficulties a possible list of actions. Also, the results may help instructors optimize less popular and costly help resources.
... The era of science and technology advocacy of internet information systems using mobile communication is farfetched. In the academic learning domain, the technology synergy has enabled self-learner motivation and retention, in a group or individually, in resolving tasks interactive settings (Gregori, Zhang, et al., 2018). ...
Article
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The proliferation of online crowdsourcing information via mobile technology intervention achieved progressive learning in recent times. The study seeks the mobility of crowds using internet-contents as crowdsourcing knowledge phenomenon in community-learning task actualization. Bandura’s Social Learning Theory (SLT) and TPB induced and investigated 361 respondents among international students using IBM Amos v. 25 for the analysis. Results found exogenous variables were positively significant, whiles broadband moderation on mobile learning behavior run-up. Mobile learning mediation magnifies the behavior actualization effectiveness. Significantly, crowdsource at the individual level colored internet-content via mobile learning technology collaborated communication problem-solving tasks. Mobility of learning makes a mountain of molehills in knowledge sourcing, communication community-centered performance.
... It is reported that this effective approach for timetabling problems shows competitive results, both in terms of computational execution time and solution quality [33]. Gregori et al. analyzed five massive open online courses (MOOCs) coordinated by Catalonian universities, to explore learner support strategies that assist students in completing MOOCs [34]. Behavioral data belonging to 24,789 participants were analyzed using semi-supervised extreme learning machine (SSELM) in the study. ...
Article
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Three different examinations for any course are primarily defined in higher education in Turkey: midterm, final and make-up exams. Whether a student has passed a course is decided by using the scores of midterm and final exams. If this student fails the course as a result of these exams, he can take a make-up exam of this course, and the score of the make-up exam is replaced with the final exam. However, some of the students do not take the make-up exam although it is expected that they take the make-up exam, due to different reasons such as average score, distance, low score of midterm exam, etc. Because the make-up exam plans and schedule have been performed in accordance with the number of students who failed the course, some resources such as the number of classrooms, invigilators, exam papers, toner are wasted. In order to reduce these wastages, we applied artificial neural networks, ANN, trained by different approaches for predicting the number of students taking make-up examinations in this study. In the proposed framework, some features of students and courses have been determined, the data has been collected and ANNs have been trained on these datasets. By using the trained ANNs, each student who fails the course is classified as positive (taking the make-up exam) or negative (not taking the make-up exam). In the experiments, the data of ten different courses are used for training ANNs by random weight network, error back propagation algorithm, some metaheuristic algorithms such as grey wolf optimizer, artificial bee colony, particle swarm optimization, ant colony optimization, etc. The performances of the trained ANNs have been compared with each other by considering training accuracy, testing accuracy, training time. BP achieves the best mean training accuracy on both unnormalized and normalized datasets with 99.36% and 99.7%, respectively. GWO achieves the best mean testing accuracy on both unnormalized and normalized datasets with 80.39% and 82.39%, respectively. Moreover, RWN has the best running time of less than a second for training the ANN on both normalized and unnormalized datasets. The experiments and comparisons show that an ANN-based classifier can be used for determining the number of students taking the make-up exam.
... Daniel et al. (2015) stated that there is a need to consider five dimensions in future studies, which are the teaching model, monetisation, certification, adaptive learning and MOOCs for developing countries. Furthermore, literature stresses that MOOCs are designed for autonomous learning and the current approaches to the quality assurance of MOOCs are limited (Langen & Bosch, 2014;Margaryan et al., 2015;Fernández et al., 2015;Gregori et al., 2018). ...
Article
Both innovation and quality assurance are prominent concerns in higher education institutions but research is ambiguous with respect to the relationship between quality assurance and innovation. Specifically, it is unclear whether quality assurance supports innovation or, conversely, acts as a hindrance. As a relatively new innovation, massive open online courses (MOOCs) yield insights into the relationship between quality assurance and innovation in higher education institutions. This article explores how quality assurance is adapted to accommodate MOOCs based on case studies in five universities in the United Kingdom. Our findings suggest that quality assurance does not support innovations such as MOOCs because most universities use a relatively superficial approach that focuses on technical requirements rather than academic quality. The study provides suitable empirical evidence to support a cogent argument that universities should evaluate MOOCs through quality assurance, both to identify strengths and to expose weaknesses that need to be developed.
... Tutors, in specific, are of vital importance and their constructive interaction with the learners within the first few weeks of the study marks a significant contributor to the reduced rate of dropout [10]. In the context of online learning platform, the quality of the videos was found to be specifically essential [11]. ...
... Despite benefits, MOOC providers are confronting with learner's high attrition rate. The MOOC completion rate is around 10% (Gregori et al., 2018). Students' incessant exit from courses puts learning and education in danger and blocks the formative advancement of MOOCs. ...
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This investigation is done during COVID-19 to identify, rank, and classify MOOC (massive open online course) key acceptance factors (KAFs) from an Indian perspective. A systematic literature review identifies 11 KAFs of MOOC. One more novel factor named ‘contingent instructor' is proposed by the authors considering pandemic and new normal post-COVID-19. The paper implements two popular fuzzy MCDM (multiple-criteria decision-making) techniques, namely fuzzy TOPSIS and fuzzy AHP, on 12 KAFs. The fuzzy TOPSIS approach is used to rank factors. Affordability, performance expectancy and digital didactics are found as the top three KAFs. Fuzzy AHP classified KAFs into three groups, namely high, moderate, and low influential. Examination of the literature indicates that this study is among the first attempt to prioritize and classify MOOC KAFs using fuzzy TOPSIS and fuzzy AHP approach. The results offer managerial guidance to stakeholders for effective management of MOOC, resulting in higher acceptance rate. Likewise, this investigation will upgrade the comprehension of MOOC KAFs among academicians.
... Lecturers have a responsibility in creating a learning environment that can provide emotional security and higher opportunities for student involvement and resp onsibility through self-assessment activities, so that self-efficacy and motivation in student learning increases. This self -a ssessment is v ery helpful in building students' sense of responsibility in learning, self -monitoring in learning activities, instilling awareness to improve self-efficacy, and building logical arguments [13]. Table 3. Self-Reflection and metacognition process ...
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The learning model in the digital era has changed from traditional face-to-face learning to online learning. This causes stuttering and uncertainty for educational institutions, including the State Islamic Religious University (PTKIN), especially the readiness of lecturers. Each lecturer has different models, strategies and learning media in managing the class according to their understanding and ability in online learning. This study aims to see the readiness of PTKIN lecturers for online learning through MOOCs media with a heutagogy approach using the e-learning system at their respective universities.The quantitative research method uses 5 elements of heutagogy and 1 element of MOOCs with 52 sampling data on PTKIN lecturers.The results show that lecturers have competence and readiness in using online learning technology, but there are weaknesses in lecturers' understanding in using the heutagogy approach in learning.
... This claim has been supported by the study of Hew et al. (2018) wherein student reflections in 18 highly rated MOOCs were analyzed, and interaction was found to be one of the most important design characteristics of MOOCs. Other studies (e.g., Hone and El Said, 2016;Gregori et al., 2018) also identified interaction as a key factor in learners' completion of MOOCs and online courses in general. ...
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Interaction has been regarded as a key design component in online and distance learning. In this study, we convened a student-led, blended mode (face-to-face and online/Facebook discussions) massive open online course (MOOC) study group to facilitate interactions for learning. Multiple data, including voice recordings, one-on-one interviews, video recordings, and artifacts were collected and analyzed to detect patterns of interaction in both face-to-face and online/Facebook settings, as well as student perceptions of the blended MOOC study group. Findings indicated that, overall, the blended mode MOOC study group was helpful for promoting communication, providing help, resolving problems, and exchanging ideas and information among group members. Moreover, face-to-face meetings and online discussions both might have exerted their unique strengths and functions in different learning situations for different learners. We recommend future studies continue to explore the tenability of the blended mode MOOC study group in different contexts, subject areas, and age groups, as well as examining group dynamics and interactions that transform MOOC learning into interactive, motivating, and fulfilling journeys among study group members.
... A review of MOOC literature showed that social factors such as social presence, social support(Aldowah et al., 2020), interactions(Gregori et al., 2018;Hone & El Said, 2016), meeting new people(Uchidiuno et al., 2018), friends taking a course, and connection with others(Bayeck, 2016;Xiong et al., 2015) affect MOOCs users' decisions to choose a course and complete it. Social motivations in MOOCs make the course more attractive for learners and improve the level of participation, engagement, performance, and attitude toward using MOOCs which are important factors in MOOCs completion (e.g.,Alraimi et al., 2015;Barak et al., 2016;Buhr et al., 2019;Khan et al., 2018;Kyewski & Krämer, 2018;Tang & Chaw, 2019).Technological motives: Technological types of motivation speak about to what extent technology motivates learners to participate in MOOCs and complete it. ...
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Although MOOCs platforms offer a unique way to provide information for a large cohort of participants, only a small percentage of participants complete MOOCs. The high number of dropouts in MOOCs is a key challenge, and the literature suggests that it can be affected by participants' motivation. However, it is not known how and to what extent motivation influences participants’ dropout in MOOCs. There is a need to provide an overview of the role of motivation in MOOCs’ retention. In this study, we aimed to identify motivational factors and theories that affect participants’ retention in MOOCs and explain how does motivation supports participants to complete MOOCs. To do so, a systematic review was conducted using specific inclusion and exclusion criteria and a set of relevant keywords and databases which resulted in 50 relevant publications. Our analysis led us to identify six main motivational factors that influence participants’ MOOCs completion including academic, social, course, personal, professional, and technological motives. These factors were divided into two main categories including need-based motivation and interest-based motivation. The results showed that academic motives play the most important role in participants’ MOOCs retention compared to the other factors. It was also found that self-determination theory was used as the most dominant theory to support participants’ motivation for MOOCs completion. In addition, the results revealed that the motivational factors not only impact participants’ MOOCs retention directly, but also this impact is mediated by participant satisfaction, self-regulation, attitude toward using MOOCs, performance, engagement, and level of participation. Based on the results, further implications for practice and future research are provided.
... Also, Santoso et al. (2019) mention that the design of MOOCs must allow sending the messages to the instructor, conducting the discussion forums, paying for certificates, submitting the assignments and taking the exams online. Finally, teachers have the opportunity to improve the teaching-learning conditions through technology (Broeck et al, 2020;Gregori et al., 2018;Medina-Labrador et al., 2020;Shen, 2018). In particular, the use of MOOCs in the educational field facilitates the active participation of students (Broeck et al, 2020;Chen et al., 2020), increases the motivation during the learning process (Hsu et al., 2018;Lee & Chung, 2019) and improves the academic performance (Xing, 2019;You, 2019). ...
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Technological advances such as Massive Open Online Courses (MOOCs) and Information and Communication Technologies (ICT) allow the construction of new spaces where students consult the information at any time, take the online exams and communicate with the participants of the educational process from anywhere. This quantitative research analyzes the perception of the teachers about the organization of the school activities in MOOCs and use of ICT considering machine learning and decision tree techniques (data science). The participants are 122 teachers (58 men and 64 women) from the National Autonomous University of Mexico who took the “Innovation in University Teaching 2020” Diploma. The academic degree of these educators is Bachelor (n = 35, 28.69%), Specialty (n = 4, 3.28%), Master (n = 58, 47.54%) and Doctorate (n = 25, 20.49%). The results of machine learning (linear regressions) indicate that the organization of the school activities in MOOCs positively influences the motivation, participation and learning of the students. Data science identifies 3 predictive models about MOOCs and ICT through the decision tree technique. According to the teachers of the National Autonomous University of Mexico, the organization of the school activities in MOOCs and use of ICT play a fundamental role during the COVID-19 pandemic. The implications of this research promotes that educators use MOOCs and ICT to improve the educational conditions, create new remote school activities and build new virtual learning spaces. In conclusion, universities with the support of technological tools can improve the teaching-learning process and update the course during the COVID-19 pandemic. In particular, MOOCs represent a technological alternative to transform the school activities in the 21st century.
... As audio quality has been named as one of the most influential factors for the success of videos used in distance learning [18], [19], high-quality microphones and a professional audio interface were obtained for the studio setup. ...
... Insufficient learner support reduces student completion rates. Interaction between peers and students and educators can improve student engagement (Gregori et al., 2018). We identified the importance of educators/facilitators who will support the learners via email and forums. ...
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In this paper, we present a structured approach to developing an outreach program aimed at improving the coding abilities of pre- and in-service teachers. The paper presents the design and development decisions made using the ADDIE model. External evaluators assessed the material's quality, confirmed the estimated workload, and examined the material's relevance to the educational goals. Learners’ active participation was encouraged through multiple quizzes, and learners were assisted in their learning activities by means of practical examples. Based on the number of people who actually logged into the course, a completion rate of 70.84 percent is achieved. The paper presents and discusses the findings of an evaluation conducted with the assistance of experienced teachers and course participants.
... Related to interest, students who are interested in using the social web tools in online courses have been shown to be more likely to put forth more effort through active learning [12]. And a stronger teacher presence in online courses can help students believe that they can succeed and increase their beliefs that the teacher cares about their learning, both of which could lead to more effort and persistence in a course [13]. ...
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The primary purpose of this study was to examine the extent to which students’ course perceptions (i.e., perceptions of empowerment, usefulness, success, interest, and caring) and cost beliefs predict their effort and grades in an online course. We surveyed 1,446 students in an online geography course. Students completed closed- and open-ended items and we used structural equation modeling and qualitative coding to analyze the data. Students’ course perceptions predicted their course effort, which then predicted their final course grade. The quantitative findings demonstrated that students’ situational interest and perceptions of instructor caring were statistically significant predictors of their effort and achievement. The qualitative findings indicated that students’ perceptions of the usefulness of the course content and their interest affected their effort, as did the amount of time that they had available for course activities. The findings were moderated by students’ perceptions of course ease. Students reported decreased effort when they believed that they could succeed and the course was easy, and when they believed it was going to take a lot of time and the course was difficult. This study highlights the importance of designing courses that (a) interest students in the course activities, (b) foster perceptions of caring between the instructor and students, (c) are at an appropriate level of difficulty, and (d) provide a reasonable workload with considerations for students with time constraints. Researchers may use the findings to develop interventions and strategies that instructors can use to encourage students to put forth more effort in online courses.
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The growth in online professional development opportunities for teachers, due to the COVID-19 pandemic, prompts us to question what the most effective practices of facilitating professional development online are and what design elements of online professional development (OPD) programs improve teachers’ content and pedagogical content knowledge (PCK). These questions are critical to the successful design and delivery of OPD for teachers. To date, there is no systematic review that provides answers to these questions. Hence, this review presents a synthesis of 11 studies that systematically examine experimental and observational studies that tested or evaluated formal OPD programs for teachers. Eight studies were quantitative and three were mixed methods detailing evidence of teachers’ OPD program effectiveness, including design elements, that lead to teachers’ improved: content knowledge; PCK; beliefs about teaching; self-efficacy; and instructional practices. Design elements identified included a focus on learner supports, further acquisition or development of PCK, engagement, flexibility, individual difference in learners and learning styles, practical learning activities, reflection, relevance and application of knowledge and skills. The analysis uncovers a primary issue that few available publications of teachers’ OPD are strong methodologically. This systematic review’s findings report on design elements that lead to effective OPD learning experiences for teachers.
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The high dropout rate from Massive Open Online Courses (MOOCs) has been a major concern of researchers and educators over the years. Although academic papers on MOOCs have mushroomed over the past ten years, few studies have focused on MOOC dropout and retention. In particular, research on hospitality and tourism MOOCs has remained nascent despite the field’s significant contribution to international business and global employment. Because of the lack of relevant literature on hospitality and tourism MOOCs, this study conducts a systematic review of the MOOC literature on the broader education field, examining the MOOC dropout phenomenon and retention strategies. The results of a content analysis based on journal articles’ main research topic show four clusters: prediction, continuance intention, motivation, and attrition. Thematic analysis is used to categorize the dropout factors into seven major themes: learning experience, interactivity, course design, technology, language, time, and situation. This paper concludes with a summary of the results, recommendations, practical implications, limitations, and directions for future research.
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Hybrid learning is an intentional integration of traditional and online learning in order to provide educational opportunities that maximize the benefits of each mode of delivery to facilitate students' learning. Institutions of higher learning are being challenged to adopt such modality to deliver quality instruction. This descriptive-exploratory research assessed hybrid learning as a technology-aided tool employed in Freshmen Orientation Seminar (FOS) C101, known as "Strategies for Academic Success in College," a distinct and unique course offered among first year students of a private, non-sectarian university in the Philippines. This study involved 40 students from various courses. Results showed high assessments of the hybrid learning dimensions, namely, learning design, learning objectives and outcomes, learning materials, technology, learning support, administrative and organizational commitment, amount and quality of interaction between teachers and students, and quality and amount of learning experience. Further, the null hypothesis stating that no significant differences exist in the assessment of student-respondents about the aforementioned dimensions of hybrid learning when they are grouped according to their profile variables was confirmed. Generally, the findings may contribute to the enhancement of the modality of instruction of FOS C101. Several recommendations are made to maximize hybrid learning as a tool of teaching.
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The dropout rates of open e-learning platforms are often cited as high as 97%, with many users discontinuing their use after initial acceptance. This study aims to explore this anomaly through the lens of affordances theory, revealing design–reality gaps between users' diverse goals and the possibilities for action provided by an open IT artefact. A six-month case study was undertaken to investigate the design implications of user-perceived affordances in an EU sustainability project which developed an open e-learning platform for citizens to improve their household energy efficiency. Thematic analysis was used to reveal the challenges of user continuance behaviour based on how an open IT artefact supports users in achieving individual goals (e.g. reducing energy consumption in the home) and collective goals (lessening the carbon footprint of society). Based on the findings, the authors inductively reveal seven affordances related to open e-learning platforms: informing, assessment, synthesis, emphasis, clarity, learning pathway and goal-planning. The findings centre on users' perception of these affordances, and the extent to which the open IT artefact catered to the goals and constraints of diverse user groups. Open IT platform development is further discussed from an iterative and collaborative perspective in order to explore different possibilities for action. The study contributes towards research on open IT artefact design by presenting key learnings on how the designers of e-learning platforms can bridge design–reality gaps through exploring affordance personalisation for diverse user groups. This can inform the design of open IT artefacts to help ensure that system features match the expectations and contextual constraints of users through clear action-oriented possibilities.
Chapter
With more than 100,000,000 learners from around the world, massive open online courses (MOOCs) are a popular online learning resource. Because this type of online teaching and learning is relatively young, published MOOC research is not as voluminous as traditional educational research. This presents both a challenge and an opportunity. The challenge is that best practices are not always clear, and there is not much MOOC research upon which to draw for specific instructional design strategies. The opportunity is to harness the power of MOOC platforms themselves to conduct research that examines and identifies effective digital pedagogy. In this chapter, the authors describe some of these challenges and opportunities. Specifically, they draw upon a multivariate experimental research study that examined the effects of pre-tests and feedback on learning and persistence in a MOOC. They offer practical implications that are related to study findings.
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In the last decade, Language MOOCs have attracted a lot of interest for their potential to enhance language learning. However, how learners engage with MOOC environments and realise their benefits, remains unclear. The current study adopts activity theory (Engeström in J Educ Work 14:133–156, 2001) as a lens to comprehend the affordances and limitations in an LMOOC dealing with English presentation skills called Presentation@work. Data were collected via semi-structured interviews with 22 participants. The data were then analysed using thematic content analysis and triangulated with the participants’ profiles using learning analytical procedures. The results showed that peer learning, personalisation, and social interaction opportunities were perceived as affordances by the participants, while lack of proficiency, lack of affinity, course content, and lack of teacher presence were seen as limitations. Relationships between the perceived affordances and limitations and different types of participants were also found. The findings demonstrate that the LMOOC activity system is dynamic and complex and that the learners play a central role in interacting with different aspects of the system. We conclude with a number of suggestions and implications for future LMOOC design, implementation and research.
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Background: Student support services are a broad and important concept in education, each of which is related to a specific set of hypotheses related to the subject. This lack of theoretical and conceptual ambiguity has led to poor understanding and communication between researchers and policymakers and problems in comparing studies in different fields. The purpose of this study is to explain the student support system in virtual learning environment for medical education. Methods: This study was a qualitative research. An extensive search in scientific databases was carried out based on predetermined strategies, and 53 documents were reviewed from 1996 until 2019. Data were analyzed based on Hugh McKenna’s nine-step approach. Results: According to the literature review, determining the support services of students in virtual learning, providing academic and non-academic services is the responsibility of students' cognitive, emotional and social needs. These services lead to greater student participation in the process of self-learning and academic achievement, which is done at three levels: (pre-program, learning process and post-graduate support services). Student support services were categorized into conceptual areas (level, dimensions, and purpose) and the relationship between these conceptual areas was identified. Conclusions: Based on the findings of this study, student support services in virtual learning can be divided into two categories: academic and non-academic with relevant subcomponents. It is recommended that educators and policy makers use these results to facilitate student support for different types of virtual learning.
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MOOC platforms have seen significant membership growth in recent years. MOOCs are leading the education world that has been digitized, remote, and highly competitive, and the competition is intense in the MOOC world. Based on the observation for top-rated MOOCs, this study proposes a research question, “What makes a great MOOC? What makes a hit?” To explore the answers, this study applies a crowdsourcing approach and interprets the semantics of reviews for the top-rated courses on Coursera.org. The paper has multiple steps and findings relevant to MOOC programs at universities worldwide. First, through exploratory analysis of learner reviews and expert judgment, this study identifies two distinct course categories focusing on learners' outcome intent, namely knowledge-seeking MOOCs and skill-seeking MOOCs. Further, this study uses a topical ontology of keywords and sentiment techniques to derive the intent of learners based on their comments. Through sentiment analysis and correlation analysis, it shows that knowledge-seeking MOOCs are driven by the quality of course design and materials. Skill-seeking MOOCs are driven by the instructor and their ability to present lectures and integrate course materials and assignments. This crowdsourcing method obtains the insights from large samples of learners’ reviews without the priming or self-selection biases of open surveys or interviews. The findings demonstrate the effectiveness of leveraging online learner reviews and offer practical implications for what truly “makes a hit” for top-rated MOOCs.
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Son zamanlarda küresel ve ulusal ölçekte hissedilen ihtiyaçlar ve zorunluluklar nedeniyle teknolojiye dayalı öğretim yaklaşımlarının kullanılmasına ilişkin beklentiler artmış; üniversiteler bu beklentileri karşılamak için farklı uygulama arayışı içine girmişlerdir. Ders Yakalama Sistemi (DYS) bu uygulamalardan birisidir ve amacı, öğretim elemanının, çevrimiçi olarak ya da ders kayıtlarında gerekli gördüğü değişiklikleri yaptıktan sonra dersini, öğrenci erişimine açarak öğrencinin kendi ihtiyacı doğrultusunda bilgiye ulaşmasını ve tekrar etmesini sağlamaktır. Bu çalışmada, bir yükseköğretim kurumundaki öğrencilerin DYS’yi kullanım amaçları, DYS’ye ilişkin yarar algıları ve DYS kullanımı ile ilgili algıladıkları kısıtlılıklara ilişkin görüşlerinin betimlenmesi amaçlanmıştır. Araştırma sonuçları, öğrencilerin DYS sistemini işlevsel ve yararlı bulduklarını, en çok sınavdan önce konuları gözden geçirmek, derste kaçırdığı ya da derse gelemediği durumlarda öğrenme eksikliklerini kapatmak için kullandıklarını ancak sisteme ulaşımda yaşadıkları en önemli kısıtlılığın teknik aksaklıklar olduğunu göstermiştir. Bu çalışma, teknolojiye dayalı öğretim yaklaşımlarının daha fazla önem kazandığı ve kullanıldığı günümüzde söz konusu yaklaşımların pedagojik değerini ön plana çıkaran araştırmaların yürütülmesini önermektedir.
Learning analytics (LA) has the potential to generate new insights into the complexities of learning behaviours in language massive open online courses (LMOOCs). In LA, the collective attention model takes an ecological system view of the dynamic process of unequal participation patterns in online and flexible learning environments. In this study, the ‘Oral Communication for EFL Learners (spring)’ on XuetangX was selected as an example with which to examine the allocation of learner attention in the context of LMOOCs. The open-flow network of collective attention was used to model the dynamics of learning behaviours to understand how different cohorts of second language (L2) learners allocated their attention at the collective level. The results showed that what distinguished high-performing L2 learners was related less to where they started with LMOOC resources or how much attention they allocated to certain learning units and more to the extent to which their attention could be maintained and circulated into other learning units. In addition, learners’ attention typically followed the pre-designed course structure each time they entered the online space. No learning resources offered in the selected LMOOC were found to dominate the collective attention flow, which suggested that L2 learners’ online engagement followed classroom learning patterns. The use of LA to understand the allocation of L2 attention at the collective level provides new perspectives on digital behaviour in LMOOCs, which may facilitate the design of cost-effective L2 resources that prevent learner overload in the information-rich age.
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Through a translanguaging lens, trans-semiotizing emphasizes the entanglement of language and other semiotic resources to negotiate meaning. Recent studies have begun to recognize the pedagogical functions of translanguaging/trans-semiotizing by optimizing the use of multisemiotic resources. The present study contributes to this growing body of literature by exploring the relationship between translanguaging/trans-semiotizing and learner agency (the initiative to learn) in a course of content and language integrated learning (CLIL) under everyday and crisis contexts. Firstly, the patterns of trans-semiotizing were analyzed in social media interactions between 2121 undergraduate students and three teachers over three semesters. Secondly, the process of trans-semiotizing for learner agency was examined through multimodal conversation analysis. Thirdly, perceptions of the four semiotic resources were explored via chat-log-stimulated interviews and a follow-up questionnaire. The convergent results show that trans-semiotizing was a common practice both under everyday and crisis contexts, being closely associated with the fluctuation of learner agency. Significantly, trans-semiotizing between texts and pictures fosters learner agency by facilitating learners' exploration of the learning opportunities, while trans-semiotizing to emojis indicates the fluctuant learner agency. These findings indicate that trans-semiotizing makes learner agency more visible and achievable, and teachers' trans-semiotic competence to differentiate and deploy multisemiotic resources is critical.
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Online learning is a powerful option for professional development in various careers, including marketing. However, massive open online courses (MOOCs) tend to face an issue of course dropouts, and this cannot only be attributed to factors like course content or value. Social interactions among students and interest-generating elements of MOOCs are equally important elements of online learning ecosystems. Therefore, this study approaches the problem from the perspective of the social exchange theory with insights into the cognitive evaluation theory to predict the effects of social interactions and gamification rewards on the process of studies. The data from an experiment and a subsequent survey of marketing course participants were used to analyze student satisfaction and dropouts through the lens of the social exchange theory and to see the effects of expected and unexpected gamification rewards. This contributes to the knowledge about factors that influence online course discontinuation, provides managerial and educational insights on dropout reduction, and specifies directions for further studies on the use of gamification elements in MOOCs.
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In massive open online courses (MOOCs), recommendation relationships present a collection of associations that imply a new form of integration, such as an interdisciplinary synergy among diverse disciplines. This study took a computer science approach, using the susceptible-infected (SI) model to simulate the process of learners accessing courses within networks of MOOC offerings, and emphasized the potential effects of a network structure. The current low rate of access suggests that a ceiling effect influences learners' access to learning online, given that there are thousands of courses freely available. Interdisciplinary networks were created by adding recommended courses into four disciplinary networks. The diversity of interdisciplinarity was measured by three attributes, namely variety, balance, and disparity. The results attest to interesting changes in how the diversity of interdisciplinary knowledge grows. Particularly remarkable is the degree to which the diversity of interdisciplinarity increased when new recommended courses were first added. However, changing diversity implied that neighbouring disciplines were more likely to come to the forefront to attach to the interdisciplinarity of MOOC offerings, and that the pace of synergy among disparate disciplines slowed as time passed. In the absence of domain experts, expert knowledge is not sufficient to support interdisciplinary curriculum design. More evidence-based analytics studies showing how interdisciplinarity evolves in course offerings could help us to better design online courses that prepare learners with 21st-century skills.
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The objective of this paper is the design of a predictive model of students’ desertion in Educational Institutions based on the Analytic Hierarchy Process (AHP). The proposed model is based on a weighted sum of individual probabilities of deser- tion associated with various factors (explanatory variables) by experts in the com- bined use of the AHP and the Ratings technique for the evaluation of the explanatory variables of the model. This proposal was applied in an Institution of Higher Education in Chile. To evaluate the predictive performance of the method, the results were compared with those obtained using Logistic Regression (RL) and with the actual retention of the students in one year. It was found that the proposed method had a 64.6% level of predictability, whereas the model with logisticregression had a 69.9%. It is concluded that it is possible to predict student desertion with a simple model based on the Analytical Hierarchy Process.
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In spite of the high impact of Massive Open Online Courses (MOOCs), learners frequently disengage from the course contents and activities due to unexpected problems of different natures, such as content‐related or technical issues. Feedback has been identified as an important aspect of the learning process directly connected with learners' engagement. However, the massive and impersonal nature of MOOCs hinders the provision of efficient and timely feedback to those learners facing problems. This paper examines how MOOC practitioners identify and support learners facing problems, what challenges they encounter, and what strategies they apply to overcome such challenges. Additionally, the current study aims to compare the learners' problems and practitioners' experiences between engineering‐related and nonengineering related MOOCs. A qualitative phenomenological study has been conducted through semistructured interviews with 14 MOOC practitioners. The evidence gathered shows diverse learners' and practitioners' problems shared among engineering and nonengineering courses and a general concern on how to address individual learners' needs in time. A common practice of problem identification regards checking the self‐reported issues in communication forums. Identification strategies with the use of learning analytics are limited due to platform restrictions or lack of practitioners' skills in interpreting the provided information. The synthesis of MOOC practitioners from both engineering and nonengineering disciplines may provide insights that are either globally applicable to all disciplines or specific to engineering. The results could be shaped into conceptual and technological solutions to help MOOC stakeholders (e.g., researchers, practitioners) identify potential learners facing difficulties and support them during the course process.
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Due to changing needs at global and national level, there are currently greater than ever expectations from technology-enhanced teaching approaches. To meet these expectations, universities have been experimenting with different teaching approaches and applications. One of these approaches and applications is Lecture Capture (LC). LC is used to enable students to access their lectures both synchronously and asynchronously, and to use them in a way that best meets their needs. The aim of this study is to identify the current situation at a university in which the lecture capture approach is in use, by investigating students’ perceptions on three areas of the LC system: its usefulness, its purpose, and its constraints/difficulties. Results indicated that students find LC approach functional and useful, especially for reviewing the content before exams, and making up for missed classes. The results also showed that the most commonly perceived constraint was technical problems in accessing the videos. The study suggests that further research should focus on pedagogical values of technology-enhanced teaching approaches. Keywords: Lecture capture system; simultaneous lecture record; video lecture; student opinion; higher education
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Introduction: Process of e-learning in universities because of coronavirus (Covid- 19) outbreak was developed. Since the success of students in this type of education requires appropriate and effective support, the present study has been done to develop a model of support system in virtual learning environment in medical universities. Methods: This is an applied qualitative research. To design the model, data obtained from searching information sources in the period of 1990 to 2020 was used as well as thematic analysis to analyze the results of interviews with experts. The validity and reliability of the interview data were confirmed based on Lincol & Guba evaluative criteria. Based on the data, the model of the student support system of medical universities in the virtual learning environment was developed by creative mental synthesis. Results: In this model, seven key supports have been introduced as important dimensions of the student support system in the virtual education environment. in addition to student support, professors and staff need to be supported. Also, student support before, during, and after graduation is required for students' success in this model. Conclusion: According to the research findings, since the necessity of student support system in the environment of e-learning and virtual learning is inevitable for students' academic success, therefore, it is recommended that university officials and administrators use the results of this study to implement a student support system in the virtual learning environment at their university
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The current study assesses the effect of using Massive Open Online Courses (MOOCs) with the specific goal of providing remedial education. The data refer to an Italian flagship university, Politecnico di Milano, where a MOOC platform was launched following the strategy ‘MOOCs to bridge the gaps’. Hence, the study aims at assessing the effect of students completing a MOOC taken as a foundation course in physics on their ability to pass the subsequent on-campus exam in physics (N = 2,830). The research used Propensity Score Matching (PSM), basing the propensity scores on personal and academic information about the students. The results show that completers are 7 to 16 percentage points more likely to pass the related exam than the other students enrolled in the same MOOCs. These findings support the idea that using MOOCs for remedial purposes is effective in terms of student achievement within a formal education context.
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In this paper, we explore student dropout behavior in Massive Open Online Courses(MOOC). We use as a case study a recent Coursera class from which we develop a survival model that allows us to measure the influence of factors extracted from that data on student dropout rate. Specifically we explore factors related to student behavior and social positioning within discussion forums using standard social network analytic techniques. The analysis reveals several significant predictors of dropout.
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In this work, we explore video lecture interaction in Massive Open Online Courses (MOOCs), which is central to student learning experience on these educational platforms. As a research contribution, we operationalize video lecture clickstreams of students into cognitively plausible higher level behaviors, and construct a quantitative information processing index, which can aid instructors to better understand MOOC hurdles and reason about unsatisfactory learning outcomes. Our results illustrate how such a metric inspired by cognitive psychology can help answer critical questions regarding students' engagement, their future click interactions and participation trajectories that lead to in-video & course dropouts. Implications for research and practice are discussed.
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Recently, a multi-objective Sensitivity-Accuracy based methodology has been proposed for building classifiers for multi-class problems. This technique is especially suitable for imbalanced and multi-class datasets. Moreover, the high computational cost of multi-objective approaches is well known so more efficient alternatives must be explored. This paper presents an efficient alternative to the Pareto based solution when considering both Minimum Sensitivity and Accuracy in multi-class classifiers. Alternatives are implemented by extending the Evolutionary Extreme Learning Machine algorithm for training artificial neural networks. Experiments were performed to select the best option after considering alternative proposals and related methods. Based on the experiments, this methodology is competitive in Accuracy, Minimum Sensitivity and efficiency.
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Massive Open Online Courses (MOOCs) are successful in delivering educational resources to the masses, however, the current retention rates—well below 10 %—indicate that they fall short in helping their audience become effective MOOC learners. In this paper, we report two MOOC studies we conducted in order to test the effectiveness of pedagogical strategies found to be beneficial in the traditional classroom setting: retrieval practice (i.e. strengthening course knowledge through actively recalling information) and study planning (elaborating on weekly study plans). In contrast to the classroom-based results, we do not confirm our hypothesis, that small changes to the standard MOOC design can teach MOOC learners valuable self-regulated learning strategies.
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This article reports two studies undertaken at The Open Polytechnic of New Zealand, a vocational distance education (DE) provider, where course completion rates have risen to match those of face-to-face technical institutions. A simple model of student engagement is presented, which reflects the triality between the student, institution, and external environment. The first study investigated institutional factors, from the perspectives of staff who have contributed toward this improvement; the second study focused on student perceptions of factors that fostered engagement. Both staff and students considered helpful tutors and clear learning materials essential; as is student motivation, which is enhanced if courses are relevant and achievable. Reasons for non-completion included inappropriate course advice and competing life demands. Staff participants believed student engagement can improve with appropriate interventions, while students tended to situate the lack of engagement within themselves. Findings emphasize the triadic nature of factors relating to student engagement in DE. http://dx.doi.org/10.1080/01587919.2016.1184398 http://www.tandfonline.com/eprint/DfBiGwRbbu3PPQJsCfAr/full
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This paper aims to present the most important findings of a study conducted in the context of a research project entitled "e-learning conceptual framework". The main objective of this research was to analyze perceptions of online university staff about e-learning and to create an inclusive definition of its concept, which could set the boundaries for their future activity in this sector. For this purpose, a literature review of the e-learning concept in peer-reviewed journals, web pages, reports and books was carried out. Once the most important definitions were collected and categorized in different groups, according to their approach, four focus groups were organized with the participation of twenty-five academics and managers from the Open University of Catalonia (UOC), in an attempt to understand how they interpret the concept of e-learning. This study provides a valuable definition, which enables us to advance in the identification and analysis of how e-learning is carried out in different models. © Common Ground, Albert Sangrà, Dimitrios Vlachopoulos, Nati Cabrera.
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Four generally accepted definitions of distance education are analysed and from them six components of a comprehensive definition are chosen. The forms of education that are considered to fall within the concept of distance education as outlined are considered from the point of view of choice of medium, institutional type and didactic model. Various forms of education that bear some similarities to distance education but are not to be identified with it are described. The term ‘distance education’ is proposed as the most satisfactory solution to the problem of terminology.
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In an earlier issue of ETR&D, the editors provided an hierarchical framework of components to support learning and instruction. That hierarchy included information objects, knowledge objects, learning objects, instructional objects, courses, programs and ongoing efforts, with each subsequent component building on the former components. For example, a course is a structured collected of instructional objects, which in turn are structured collections of learning objects with learning activities, feedback, and assessments (both formative and summative). Based on that hierarchical perspective, most of the current massive open online courses (MOOCs) are not actually courses. This article proposes taking what is good about the MOOC concept and transforming it into something that could be considered a course—namely, a mini-MOOC.
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Massive Open Online Courses (MOOCs) have been a prominent topic of recent educational discussion and debate. MOOCs are, in essence, university-affiliated courses offered to large groups of online learners for little or no cost and are seen by many as a bellwether for change and reform across higher education systems. This study uses content and discourse analysis methods to examine how understandings of MOOC-related ‘change’ were presented in US, UK and Australian newspapers. Drawing on detailed analysis of 457 newspaper articles published between 2011 and 2013, the findings point to a predominant portrayal of MOOCs in relation to the massification, marketization and monetization of higher education, rather than engaging in debate of either ‘technological’ or ‘educational’ issues such as online learning and pedagogy, instructional design or student experience. The article then considers the reasons underpinning this restricted framing of what many commentators have touted as a radical educational form—not least the apparently close association between MOOCs and the economics of higher education.