Understanding Learners' Motivation and Learning Strategies in MOOCs

MOOCs (Massive Open Online Courses) have changed the way in which OER (Open Educational Resources) are bundled by teachers and consumed by learners. MOOCs represent an evolution towards the production and offering of structured quality OER. Many institutions that were initially reluctant to providing OER have, however, joined the MOOC wave. Nevertheless, MOOCs detractors strongly criticize their high dropout rates. The dropout rate is a commonly accepted metric of success for traditional education, but it may not be as suitable when dealing with OER, in general, and with MOOCs, in particular, since learners' motivations to take a course are very diverse, and certain self -regulated learning strategies are required to tackle the lack of personalized tutoring and keep pace in the course . This paper presents an empirical study on the motivation and learning strategies of MOOC learners. Six thousand three hundred and thirty-five learners from 160 countries answered a self report 7- point Likert-type questionnaire based on the Motivated Strategies for Learning Questionnaire (MSLQ) as part of a MOOC titled Introduction to Programming with Java. Results indicate that learners were highly motivated and confident to do well in the course. Learning strategies, however, can be improved, especially regarding time management.This work has been co-funded by the Erasmus+ Programme of the European Union, projects MOOC-Maker (561533-EPP-1-2015-1-ES-EPPKA2-CBHE-JP), SHEILA (562080-EPP-1-2015-BE-EPPKA3-PI-FORWARD) and COMPETEN-SEA (574212-EPP-1-2016-1- NL-EPPKA2-CBHE-JP), by the Madrid Regional Government, through the eMadrid Excellence Network (S2013/ICE-2715), and by the Spanish Ministry of Economy and Competitiveness, project RESET (TIN2014-53199-C3-1-R) and fellowships FPDI-2013-17411 and PTQ-15-07505

How Academic Self-Efficacy Influences Online Learning Engagement: The Mediating Role of Boredom

Academic self-efficacy and boredom were identified as key predictors of learning engagement in online learning. However, there has been little research designed to examine the mediating role of boredom in the relationship between academic self-efficacy and online learning engagement. To address this gap in knowledge, the present study utilizes social cognitive theory, control-value theory, and the self-system process model to examine the following: (1) the impact of academic self-efficacy on three sub-dimensions of learning engagement in online learning; and (2) whether four sub-dimensions of boredom mediate the relationships between academic self-efficacy and the three sub-dimensions of learning engagement in online learning. Data were collected from 528 university students (Mage = 19.77, SDage = 1.24) who voluntarily completed questionnaires assessing academic self-efficacy, boredom, and learning engagement. The results of the structural equation modeling indicated the following findings: (1) academic self-efficacy can predict online learning engagement; (2) affective boredom mediates the relationship between academic self-efficacy and behavioral and cognitive engagement; (3) cognitive boredom mediates the relationship between academic self-efficacy and cognitive engagement; (4) motivational boredom mediates the relationship between academic self-efficacy and behavioral and emotional engagement; and (5) physiological boredom mediates the relationship between academic self-efficacy and behavioral, emotional, and cognitive engagement. Finally, this study supports the notion that academic self-efficacy can influence learning engagement by addressing boredom in online learning. It also offers significant theoretical and practical implications for promoting students’ release from boredom and enhancing their engagement in online education

Basic Psychological Needs Satisfaction, Autonomy Support, and Mindsets as Predictors of Self-Regulation in University Online Learners

Problem In contrast to more traditional learning environments, it can be difficult to see and hear both the instructor and, more crucially, the students when engaging in online education. This has been one of the most common criticisms leveled against online education for a long time. The COVID-19 disruption and transformation of online learning in higher education underlines the fact that variance among online learners in terms of academic success and psychological well-being are determined by the level and quality of self-regulation. What is the degree of self-regulation among American university students who study online because of the COVID-19 pandemic\u27s impact, and what variables might affect or perhaps predict this level of self-regulation? Purpose of Study The purpose of the present study was to test a theoretical model that explains how autonomy support, satisfaction of basic psychological needs, and mindsets predict self-regulation among university online learners in the United States. Based on the model fit and direct effect results of the first research hypothesis, the second research model was developed to examine the mediating effect of basic psychological needs satisfaction on the relationship between autonomy support and self-regulation, and whether mindsets could moderate the indirect effect of basic psychological needs satisfaction on the relationship between autonomy support and self-regulation. To assess the data, structural equation modeling (SEM) was employed. Method This study used quantitative analysis of non-experimental survey data collected via Alchemer. A model-testing design was used to examine a theoretical model which proposed that basic psychological needs satisfaction (autonomy, competency, relatedness), autonomy support, and mindsets predict online learners\u27 self-regulation. 1257 people in all completed the survey. The number of complete and valid participant responses was a sample of 404. Excel, SPSS version 26, Mplus version 8.3 were used for data analysis. Structural equation modeling (SEM) was adopted as the main statistical technique. Results The first research model of this study hypothesized that autonomy support, basic psychological needs satisfaction, and mindsets predict university online learners’ self-regulation. Analysis of the data indicated that the first hypothesized research model fit the data (X2=464.364, df=200, Normed Chi-Square=2.231, CFI=0.925, TLI=0.913, RMSEA=0.057, SRMR=0.053). The path analysis indices of model one suggested that autonomy support positively affected university online learners’ basic psychological needs satisfaction (b=0.82, p\u3c0.001). Basic psychological needs satisfaction positively affected self-regulation (b=0.44, p\u3c0.001) and mindsets positively affected self-regulation (b=0.23, p\u3c0.001). Overall, research model one explained 44.2% variance of online learners\u27 self-regulation. The model fit indices showed that the second hypothesized research model fit the data (X2=378.398, df=146, Normed Chi-Square=2.259, CFI=0.921, TLI=0.908, RMSEA=0.063, SRMR=0.050). A significant mediator effect of basic psychological needs satisfaction was found between autonomy support and self-regulation. The results indicated that the conditional indirect effect of autonomy support on self-regulation via basic psychological needs satisfaction was significant both when the mindsets score was high (which suggests growth mindset orientation) (β=0.216, 95% CI [0.098, 0.316]) and when the mindsets score was low (which suggests fixed mindset orientation) (β=0.150, 95% CI [0.031, 0.250]). Conclusions Applying SEM technique for data analysis, the model fit indices showed that the first hypothesized research model of this study fit the data and explained 44.2% variance of university online learners\u27 self-regulation. The path analysis indices of model one suggests that basic psychological needs satisfaction and mindsets play a predictive role in self-regulation among university online learners whereas autonomy support could not be used as a predictor of self-regulation among university online learners. In addition, the path analysis indices of research model one indicates that autonomy support and basic psychological needs satisfaction could not be used as a predictor of mindsets among university online learners whereas autonomy support could predict basic psychological needs satisfaction as suggested by the theoretical framework. A significant mediator effect of basic psychological needs satisfaction was found between autonomy support and self-regulation. Furthermore, the results of the second research model indicate that the conditional indirect effect of autonomy support on self-regulation via basic psychological needs satisfaction was both significant when the mindsets score was high (which suggests growth mindset orientation) and when the mindsets score was low (which suggests fixed mindset orientation). The difference (though not significant) between these two slopes suggests that the mediation effect of basic psychological needs satisfaction on the relationship between autonomy support and self-regulation was slightly stronger when the mindsets score was higher indicating a growth mindset

Developing sustainable business models for institutions’ provision of open educational resources: Learning from OpenLearn users’ motivations and experiences

Universities across the globe have, for some time, been exploring the possibilities for achieving public benefit and generating business and visibility through releasing and sharing open educational resources (OER). Many have written about the need to develop sustainable and profitable business models around the production and release of OER. Downes (2006), for example, has questioned the financial sustainability of OER production at scale. Many of the proposed business models focus on OER’s value in generating revenue and detractors of OER have questioned whether they are in competition with formal education. This paper reports on a study intended to broaden the conversation about OER business models to consider the motivations and experiences of OER users as the basis for making a better informed decision about whether OER and formal learning are competitive or complementary with each other. The study focused on OpenLearn - the Open University’s (OU) web-based platform for OER, which hosts hundreds of online courses and videos and is accessed by over 3,000,000 users a year. A large scale survey and follow-up interviews with OpenLearn users worldwide revealed that university provided OER can offer learners a bridge to formal education, allowing them to try out a subject before registering on a formal course and to build confidence in their abilities as learners. In addition, it was found that using OER during formal paid-for study can improve learners’ performance and self-reliance, leading to increased retention and satisfaction with the learning experience

Open educational resources for all? Comparing user motivations and characteristics across The Open University’s iTunes U channel and OpenLearn platform.

With the rise in access to mobile multimedia devices, educational institutions have exploited the iTunes U platform as an additional channel to provide free educational resources with the aim of profile-raising and breaking down barriers to education. For those prepared to invest in content preparation, it is possible to produce interactive, portable material that can be made available globally. Commentators have questioned both the financial implications for platform-specific content production, and the availability of devices for learners to access it (Osborne, 2012). The Open University (OU) makes its free educational resources available on iTunes U and via its web-based open educational resources (OER) platform, OpenLearn. The OU’s OER on iTunes U reached the 60 million download mark in 2013; its OpenLearn platform boasts 27 million unique visitors since 2006. This paper reports the results of a large-scale study of users of the OU’s iTunes U channel and OpenLearn platform. A survey of several thousand users revealed key differences in demographics between those accessing OER via the web and via iTunes U. In addition, the data allowed comparison between three groups: formal learners, informal learners and educators. The study raises questions about whether university-provided OER meet the needs of users and makes recommendations for how content can be modified to suit their needs. As the publishing of OER becomes core to business, we reflect on reasons why understanding users’ motivations and demographics is vital, allowing for needs-led resource provision and content that is adapted to best achieve learner satisfaction, and to deliver institutions’ social mission

The effect of online English learners’ perceived teacher support on self-regulation mediated by their self-efficacy

This study explored the relationships among online English learners’ perceived teacher support, self-efficacy, and self-regulation in online learning based on social cognitive theory. Structural equation modeling (SEM) with bootstrapping estimation was conducted using data from 220 online English learners engaged in blended learning on the Chinese University MOOC platform. The results showed that online English learners’ perceived teacher support positively influenced their self-efficacy and self-regulation. Moreover, self-efficacy was found to mediate the relationship between their perceived teacher support and self-regulation. On the whole, the findings detailed the effect of English learners’ perceived teacher support on their self-efficacy and self-regulation, as well as empirically identifying the mediation effect of self-efficacy in the relationship between perceived teacher support and self-regulation in an online learning environment. Related pedagogical implications for teacher online teaching, student online learning, and the Chinese University MOOC platform, and limitations were discussed.En el presente estudio, basado en la teoría social cognitiva, se explora la relación entre el apoyo docente percibido por los alumnos de inglés online, la autoeficacia y la autorregulación en el aprendizaje online. Se realizó un modelo de ecuaciones estructurales (MES), con la estimación Bootstrap utilizando los datos de 220 alumnos de inglés online de una universidad politécnica que participan en el aprendizaje combinado en la plataforma MOOC de las Universidades Chinas. Los resultados mostraron que el apoyo docente percibido por los alumnos de inglés online influenció positivamente su autoeficacia y autorregulación. Además, se descubrió que la autoeficacia podía mediar la relación entre el apoyo docente percibido y la autorregulación. En general, los resultados describieron con detalle el efecto del apoyo docente percibido por los alumnos de inglés online sobre su autoeficacia y autorregulación, e identificaron empíricamente el efecto mediador de la autoeficacia en la relación entre el apoyo docente percibido y la autorregulación en un entorno de aprendizaje online. Por último, se discutieron las implicaciones pedagógicas para la enseñanza online de los profesores, el aprendizaje online de los alumnos y la plataforma MOOC de las Universidades Chinas, así como las limitaciones del estudio.North University of China and a provincial research grant (No. J2020180) in Chin

El efecto del apoyo docente percibido por los alumnos de inglés online sobre la autorregulación mediada por su autoeficiencia

This study explored the relationships among online English learners’ perceived teacher support, self-efficacy, and self-regulation in online learning based on social cognitive theory. Structural equation modeling (SEM) with bootstrapping estimation was conducted using data from 220 online English learners engaged in blended learning on the Chinese University MOOC platform. The results showed that online English learners’ perceived teacher support positively influenced their self-efficacy and self-regulation. Moreover, self-efficacy was found to mediate the relationship between their perceived teacher support and self-regulation. On the whole, the findings detailed the effect of English learners’ perceived teacher support on their self-efficacy and self-regulation, as well as empirically identifying the mediation effect of self-efficacy in the relationship between perceived teacher support and self-regulation in an online learning environment. Related pedagogical implications for teacher online teaching, students online learning, and the Chinese University MOOC platform, and limitations were discussed.En el presente estudio, basado en la teoría social cognitiva, se explora la relación entre el apoyo docente percibido por los alumnos de inglés online, la autoeficiencia y la autorregulación en el aprendizaje online. Se realizó un modelo de ecuaciones estructurales (MES), con la estimación Bootstrap utilizando los datos de 220 alumnos de inglés online de una universidad politécnica que participan en el aprendizaje combinado en la plataforma MOOC de las Universidades Chinas. Los resultados mostraron que el apoyo docente percibido por los alumnos de inglés online influenció positivamente su autoeficacia y autorregulación. Además, se descubrió que la autoeficacia de ellos podía mediar la relación entre el apoyo docente percibida y la autorregulación. En general, los resultados describieron con detalle el efecto del apoyo docente percibido por los alumnos de inglés online sobre su autoeficacia y autorregulación, e identificaron empíricamente el efecto mediador de la autoeficacia en la relación entre el apoyo docente percibido y la autorregulación en un entorno de aprendizaje online. Por último, se discutieron las implicaciones pedagógicas para la enseñanza online de los profesores, el aprendizaje online de los alumnos y la plataforma MOOC de las Universidades Chinas, así como las limitaciones del estudio

The Relationship Between Motivation and Online Self-Regulated Learning

manage their own learning. The self-regulated learning practices of goal setting, environment structuring, task strategies, self-evaluation, time management, and help seeking are developed through experience and motivation. This study sought to determine the levels of self-regulated learning and identify the motivation constructs that correlated to the levels of self-regulated learning of students in an online agriculture dual enrollment course. Students had the highest self-regulation in the areas of goal setting and environment structuring. The lowest online learning self-regulation was in help seeking. Task value was the motivation construct receiving the highest mean score, while test anxiety received the lowest score. Relationships between online self-regulated learning and the motivation constructs of task value, self-efficacy, intrinsic motivation, extrinsic motivation, control beliefs, and test anxiety were statistically significant. Faculty in online courses are encouraged to aid in the development of help seeking, time management, and meta-analysis strategies. Faculty are also encouraged to incorporate valuable tasks within the online curriculum to increase students’ motivation to learn. Course developers are encouraged to incorporate problem-based learning, authentic assessments, and team-based learning approaches to better engage students. Research should continue to investigate these practices as they relate to increasing student motivation

Investigating self-regulation in the context of a blended learning computing course

PURPOSE: Massive open online courses (MOOCs) provide an innovative educational technology, which has become widely used for distance learning by independent learners. However, there has been little work so far to study the effects of using MOOCs as part of a blended classroom approach in which learning activities take place both online and in a traditional classroom setting. The purpose of this study is to investigate the aspects of blended MOOC usage in the context of a computing course for first-year undergraduates at a UK university. DESIGN/METHODOLOGY/APPROACH: The MOOC was implemented on a purpose-built platform that supports learners to make informed choices about their learning path. This research investigates students’ capacity for self-regulated learning (SRL) and understands their preparedness for independent study, profile the general areas of SRL strength and weakness, which may affect their ability to learn effectively in a self-directed environment. An existing survey instrument, based on a six-dimensional conceptualization of SRL was adapted to investigate the self-regulation in the MOOC study. FINDINGS: The results demonstrate that the dimensions of self-evaluation and time management represent particular areas of weakness for these students. Furthermore, profiles of SRL for individual students show considerable differences in capability within the study. However, the deficiencies in SRL dimensions contrast with the students’ of generally high levels of attainment. This leads us to question the validity of the existing SRL. Furthermore, a high level of social interaction and help-seeking was reported in relation to the MOOC study indicating the increasing importance of social learning and the importance of co-regulation for SRL. RESEARCH LIMITATIONS/IMPLICATIONS: Although this study presents findings from a small data sample, it points to a number of areas for future implementation and exploration. Firstly, in line with the action research approach, students’ SRL could, in the future, be tested early in the course with the MOOC component being ideally placed to provide personalised support for each student in aspects which they may benefit from developing further. Secondly, for students in the cohort studied in this paper, a longitudinal study will track how their SRL develops as they progress through the degree. We feel that it is important to gain further qualitative data to understand how students work in practice and the strategies they adopt when confronted with different modes of learning. Finally, it is necessary to consider the conceptualisation of SRL to understand if existing instruments could be adapted to provide a more accurate assessment of the effectiveness of learners’ self-regulation. ORIGINALITY/VALUE: There has been little research on the effects of using a MOOC as the online component of a blended classroom learning approach. This study has used a theoretical perspective of SRL to investigate the approaches to self-regulation adopted by undergraduate computer science students studying in a blended MOOC environment. The MOOC used for this purpose was developed on the innovative eLDa platform, allowing students to determine, track and visualise their individual path through topics and materials offered in the MOOC

Analysis of Factors influencing the successful use of Massive Open Online Courses (MOOCs) to prepare Digital Talent

One type of e-learning category is Massive Open Online Courses (MOOCs). MOOCs or MOOC promote the "democratization of education" that allows education to be accessed by everyone from anywhere and anytime. The use of MOOCs gives students access to a wide variety of resources. MOOs enable students to have the sufficient storage capacity to store their materials. MOOCs have the potential to improve digital capabilities in the face of digital transformation. The intention to use MOOC is relatively high, however, in terms of class completion rate and motivation to pass on MOOC is relatively low. These conditions need to be examined to increase the success rate of MOOCs usage. This research develops a model and identifies factors that influence the successful use of MOOCs to prepare digital talent. The approach is a mixed method that collects quantitative data using an online questionnaire and qualitative data via interviews. The researcher took data from 91 samples and eight informants for interviews. In the study results, 6 out of 12 hypotheses are accepted in this study. The factors that influence a person in completing MOOC either directly or indirectly include Performance expectancy, willingness to earn certificates, MOOC quality, and Intrinsic motivation. This research also produces recommendations that can be used as consideration for parties related to MOOC