Chinese Learners’ Attitudes and Perceptions about MOOCs


This study presents a research about massive open online courses (MOOCs) among Chinese learners. As any adoption of educational technology should ultimately benefit learners, understandings of MOOCs from learners’ perspective are important for research and practice. The aim of my study is to find out attitudes and perceptions of Chinese learners from their MOOCs learning experiences and how they learn using MOOCs. The research collected data through an online survey questionnaire and in- depth interviews with two Chinese MOOCs learners. The study examines learner attitudes and perceptions toward MOOCs that based on literature around: competence, motivation, value, effectiveness, difficulties, and self-regulated learning. The results show that most participants in the research expressed positive attitudes towards MOOCs and a range of perceptions are identified. The implications of findings for research and practice are discussed.

Chapter One: Introduction

  1. Will MOOCs change Chinese Higher Education System?

On 7th June, 2016, the annual “Gaokao” (the National Higher Education Entrance Examination) started in China. More than 9 million candidates attended the “Gaokao” examination (Jiang, 2016). Exam scores can indicate the chances of admission to Chinese universities. From the “fever” of Gaokao, it seems that the pathway for Chinese learners of making their way to higher education has not change in decades. However, with the advent of digital technologies, the Internet is changing the economical, social, and political landscape in China. And the Internet will further affect practically all activities in Chinese people’s life (Peng, 2009). In the field of education, is it possible that the importance of traditional higher education will be changed by digital technology? Knowing learner attitudes and perceptions can help for understanding the influence of online learning on China higher education: whether the development of the Information and Communication Technologies (ICT) will greatly affect their decisions. For learners, they may continue learning in traditional higher education or choose online learning as an alternative to achieve success (Liaw and Chen, 2007). Meanwhile, it is also important for the higher education institutions in China to be strategic in utilizing digital technologies to create a rich learning environment that provides supportive education and builds upon learners’ success (Ding, Niu & Han, 2010).

MOOCs offer free and open learning resources to learners who have access to the Internet (Papano, 2012; Siemens, 2012; Mazoue, 2014; Balaji & Sekhar, 2013; Kim, 2015; Zhang, 2013; Boven, 2013). In China, although MOOCs as the latest innovation in online education is still new for many Chinese students, they first recognize that they have opportunities to learn the courses from the world’s most renowned professors and universities. MOOCs open a door that allows Chinese learners to get access to higher education resources that they found difficult to pursue in reality before (Zheng et al, 2015). They also recognize that they can enjoy the

course content for free. Normally, students can learn free online courses using MOOCs, while students need to pay for the certification upon course completion. MOOCs’ degree-granting curriculum provides learners opportunities to gain partial credit towards a degree from accredited higher education institutions. This education model of MOOCs, as a means for democratizing higher education, offers all learners who wish to engage in higher education (Yao, 2014). If MOOCs were highly accepted by Chinese learners, the higher education system in China would dramatically change (Hao, 2013; Liu, 2014; Chi & Yang, 2014).

Daugherty, Biltz and Banerjee (2014) suggest that the Internet-based learning is becoming a popular phrase in the field of educational studies and mass media. Due to limited educational resources in developing countries, like China, online education is increasing faster. According to the official website of the Ministry of Education of People’s Republic of China, the total number of regular universities or colleges is 879 (updated in the year of 2013). A study from Wang and Zhang (2013) shows that the number of higher education institutions in China per 100 thousand people is far behind the average number of developed countries. Furthermore, adopting a particular model of Soviet higher education, for decades, China higher education system was built in order to fulfill the China government’s economical and political objectives (Min, 2004). This highly centrally organized and closed system of higher education generally remains intact in China (Johnes & Yu, 2008; Chang, 2015). In such circumstances, enthusiasts (e.g. Zhao, Wang & Ma, 2014) believe that the advent of MOOCs may challenge the current situation of higher education and the movement is an indicator of higher education evolution (Yuan & Liu, 2014).

Over the last few years, many studies on MOOCs have been published (e.g., Bates, 2014a; Anderson, 2015; Pence, 2012). Much of the literature focuses on the discussion about “empirical evidence from case studies, the impact on higher

education structure, or educational theories relating to MOOCs” (Liyanagunawardena, Adams & Williams, 2013, p.219). Early research about adopting technologies into higher education indicates that MOOCs will make high quality education and

effective learning (e.g. Carey, 2012; De Waard, 2015; Atabi & Deboer, 2014; Thompson, 2011). Conversely, some critics argue that the lack of hands-on experience and interaction is a major disadvantage (Hoy, 2014). Debates also take

issues with the business model of MOOCs. Critics fear that universities and private corporations will decrease academic rigor (Gore, 2014; Marshall, 2014; Rivard, 2013). Liyanagunawardena, Adams & Williams (2013) pointed out that most learners participated in MOOCs research, were from developed countries, very few

participants were from developing countries, such as China and Africa.

The current literature suggests, the questions still remain about MOOCs: how familiar learners are with the concept of MOOCs and how they view MOOCs as a source of learning? How students perceive the influence of MOOCs on the pedagogy positively in an online learning environment? Leaner attitudes and perceptions can help to address difficulties of MOOCs and increase the likelihood of a successful online learning environment (Cole and Timmerman, 2015). This paper reports on a study in MOOCs learning context among Chinese learners, exploring learners’ attitudes and perceptions of the potential of MOOCs for their learning experience and how they use MOOCs to meet their learning needs. The study identifies a range of perceptions among Chinese MOOCs learners. The findings from this study provide insight into the utilization of digital technologies in higher education in China.

  1. Why I chose this topic:

When in the phase of developing a topic for the dissertation, I received advice from my supervisor Dr. Susan Brown that interest in the topic of the dissertation is very important. Interest is regarded as the central criterion in choosing a dissertation topic, because interest can help me throughout all the dissertation plan and completion.

When thinking about my own experience, I found MOOCs a good fit with my intellectual strength and my own life circumstances. First of all, I have been a learner of MOOCs for three years and I have always enjoyed the MOOCs learning experience. Secondly, MOOCs are the latest generation of online learning. The new teaching and learning model of MOOCs is beginning to change higher education (Mazoue, 2014; Welsh & Dragusin, 2013). The study fits my knowledge learning in my master’s degree. Last but not least, as a student from China, I experienced Chinese education. I also witnessed the transformation of everyday life for Chinese people, changed by digital technologies. Although MOOCs are considered as a very positive trend of

online learning development in China, the impact on China higher education is still unclear, with a need for more exploration (Hao, 2013).

  1. Research focus: xMOOCs

The focus of this study is xMOOCs. The current wave of MOOCs is normally referred to xMOOCs model in China. As Wang (2013) pointed out, generally speaking, the most Chinese MOOCs learners are learning in xMOOCs mode. This study tries to investigate Chinese learners’ attitudes and perceptions in xMOOCs teaching mode.

MOOCs are generally divided into two prominent models: cMOOCs and xMOOCs. Originating with the theory of Connectivism, a cMOOC focuses on knowledge construction within an open curriculum with rich sources of content. In cMOOCs, students facilitate the learning process and drive the content and structure themselves. A cMOOC emphasizes knowledge creation in social networks, which is a peer-based learning approach (Luo, Robinson & Park, 2014). In 2008, Stephen Downes, George Siemens, and Dave Cormier announced the first cMOOc course was launched. As cMOOCs model is based on principles that emphasize autonomy, diversity, openness and interaction in the peer learning process, cMOOCs can be seen as “Peer2Peer University” (Ahn, Weng, & Butler, 2013, Cole & Timmerman, 2015). While, xMOOCs are new development of MOOCs based on the theory of behaviorist learning. Compared with cMOOCs, xMOOCs are much closer to traditional education. xMOOCs model is instructors-driven (Bates, 2014b), creating an open online learning ecosystem by using technologies to make an instructional and social learning environment. xMOOCs are open to anyone who can get access to the Internet.

xMOOCs learning model began to explode into the public consciousness in 2011, when Stanford University announced the artificial intelligence (AI) course. It was a 10-week course in a more conventional course structure. It attracted about 160 thousand registered users and approximately 23 thousand students completed the whole learning task. After completion, non-Stanford University students received a letter, with their course grade and class rank in the letter. Since the Stanford University AI course launched in 2011, there has been a rapid increase of xMOOCs

provided (Martin, 2012). Course providers like Coursera have become popular sources of instructor-driven xMOOCs.

I hereby share my own learning experience to show how an xMOOC works. In June, 2015, I registered in a course called “World Art History”. Peking University developed the contents. It was a typical course in xMOOC model consisted of 12 weekly online learning lectures. Each week the course introduced one or two topics. Each topic was divided into about ten mini lessons in short videos. As most MOOCs use quizzes as their main instrument of assessment (Yuan & Powell, 2013), after each video, I was required to answer a question (multiple choice) with automated answers as feedback. My answers were graded immediately when submitted. Meanwhile, the explanation of the right answer also presented for my understanding of the rationale behind this question. The core content of the lectures was in forms of videos with instructors talking and writing. Additionally, like many traditional courses in universities, weekly home works were provided for tracking the lecture material closely with hard deadlines. Overall, I found such learning experience was engaging.

When xMOOCs learning was first introduced into China in 2012, MOOCs received wide publicity attention and MOOCs learners have been increasing rapidly.

According to Wang (2013), the concept of xMOOCs has brought about the revolution for open education in China and will have a profound influence on knowledge learning style. “” is a MOOCs aggregator website and it has the largest number of MOOCs registered learners in China. Till 2015, more than 800,000 MOOCs learners use “” as a portal to select their courses (Zhao, 2015). In China, there are many xMOOC course providers, global ones such as edX, Udacity and Coursera, and local course providers are also emerging, such as iCourse163, Xuetang and CNMOOC. The number of open courses for Chinese learners has been increasing significantly (Wang, 2013; Zheng, 2016b).

  1. Statement of research questions:

Articles published in journal magazine, and news outlets such as China Education Daily, provide many commentary discussions on the development of MOOCs in China (e.g. Li & Wang, 2012; Yuan & Liu, 2013; Liu, 2014). The potential benefits

and advantages of MOOCs are highlighted and discussed in the articles from the perspectives of faculty and government administration (Luo, 2014). Though such discussions can make the greater public get to know the promise of MOOCs for liberating higher education in China, actual learners perceptions and attitudes towards MOOCs learning are still need to further explore (Hao, 2013). As Cole & Timmerman (2015) pointed out, online learning attitudes and perceptions, the analysis of students’ problems and their solutions, are crucial aspects for researchers and practice.

To this end, the current study examines the research question, attempting to extend the current literature on MOOCs:

  • What are Chinese learners attitudes and perceptions about MOOCs from their learning experiences?
  1. Brief summary of the contents

The purpose of this study is to synthesize research results about Chinese learners’ attitudes and perceptions of MOOCs, and analyze the findings with implications on online learning practices in China higher education. The following chapters are organized as:

Chapter 2 is a literature review that addresses the above topics. This chapter reviews existing literature that discusses the development of MOOCs and the theoretical framework of online learning.

Chapter 3 illustrates the methodology of the research design and how data were collected.

Chapter 4 provides data analysis and results.

Chapter 5 is the conclusion. It also contains recommendations and implications based on the findings.

Chapter Two: Literature Review

This chapter proposes an overview of the literature relevant to the study. The application of ICT in the field of education has raised questions in many areas. Academics and practitioners discussed MOOCs from a variety of functional disciplines. For a theoretical understanding, the following literature review provides an overview from diverse knowledge relating to this study.

  • Online education landscape in China
  • What the Gaokao means to today’s Chinese people

For decades, Gaokao examination largely determines if students qualify for admissions of higher education in China (Liu, 2013; Wong, 2015; Wang & Ross, 2010). Only top-performing candidates may enroll in prestigious higher education institutions. After graduation in universities, they have more opportunities to find satisfactory jobs than lower-scored students (Kirkpatrick & Zang, 2011). Therefore, from students and their parents’ perspective, Gaokao impacts on students’ social status in the future. As the so-called “one exam determining the whole life” in China, failing the Gaokao is perceived as resulting to a gloomy life. One popular slogan that was often cited in China society shows the importance of Gaokao of students’ moral: “If there is no Gaokao, how can you compete with the rich second generation?” (The term of “Rich second generation” means sons and daughters of the Chinese rich people. Currently, it is often mentioned in the Chinese media and everyday discussions referring to unfair competition in modern Chinese society).

For decades, Gaokao is still the most important test from the perceptions of many Chinese students and their families (Liu, 2013; Davey, Lian & Higgins, 2007).

According to Zhao (2012), the Gaokao spirit roots in deeper history. Three years after the founding of People’s Republic of China, Gaokao was first established in 1952.

After being suspended during the Culture Revolution during 1966 to 1976, the practice was officially resumed then has continued to the present day. To some extent, as a merit-based test, Gaokao can be seen as the successor of Keju exam that existed in China for thousands of years, a civil service exam for selecting eligible

academicians to serve as imperial officials. Candidates of Gaokao need to prepare certain subjects for the examination. Most provinces of China are currently using the“3+X” examination system: “3” refers to Chinese, Mathematics and English; “X” means that students can choose either Social Sciences or Natural Sciences according to their own interests (Yu & Suen, 2005).

As the most important academic examination in China, Gaokao has no age restriction, although most of the candidates are the students who are in their final year of senior high school. Since the year 2011, when China abolished the age limit of the Gaokao, this exam has attracted many hopefuls who want to fulfill their dreams. Tang (2016) reported a story of Liang, a 49-year-old man, who has been taken Gaokao for the 20th time in 2016. Having a positive attitude, Liang attempts to pass the Gaokao to fill his dream of enrolling in School of Mathematics in Sichuan University. Another story reported by Su (2015), one 86-year-old man from Nanjing, who took the exam for the 15th time in 2015, just wanted to get a degree from universities. For most of the candidates of Gaokao, just as a poem from Tang Dynasty describes the importance: “When a man wishes to fulfill the ambition of his life,

He only needs to diligently study the six classics by the window ( “¾‰fiR

÷   ø ).”

  • Will technologies change the situation?

Recent years have witnessed the rapid ICT development in China, which is becoming a significant force to transform Chinese people’s daily life in every aspect (Yang, 2015). The China government has announced its mission of “Internet Plus” strategy for upgrading China into a “powerful industrial country”. According to 2016 China government annual report, the “Internet Plus” strategy will produce new economic forms to make innovations (Li, 2016). Increasing digitalization is regarded as a revolution, forcing all sectors in China to rethink their operations. Because China higher education is a public service sector administered by the government, educationalists (e.g. Wei, 2016; Chen & Niu, 2015; Yang, 2015) believe the “Internet Plus” plan exerts a profound effect on the digitalization of the China education system.

When leaders of Chinese universities attempt to bring China higher education into the

digital age, MOOCs appear to be a particular method of teaching and learning practice (Chen & Huang, 2013). When the two major MOOC course providers, Cousera and edX, started to partner up with Chinese universities to offer their courses online, MOOCs have made a breakthrough in China (LNO, 2014). Advocates (e.g.

Wang, 2013) of MOOCs in China believe this technology will change how we learn, and force revision of the traditional higher educational system. They also predict that MOOCs will replace more and more internal courses of traditional higher educational institutions. Therefore, for traditional higher educational institutions in China, they need to improve their education quality. More and more online educational organizations have opened courses on MOOCs in China in a variety of domains, such as language, computer science, history and philosophy, and many popular subjects in universities (Hao, 2013).

However, the spread of MOOCs in China is still in the beginning phase (LNO, 2014). Hao (2013) suggests that a certain amount of uncertainty surrounds the future of MOOCs in China. Currently, MOOCs are not well known to those who have not access to traditional universities, especially in rural areas or in the poorer population. Although the current trends suggest a huge potential of MOOCs development in China based on the world’s largest Internet users, concerns are also raised as well. It is heretofore unclear that how positive Chinese student attitudes and perceptions are with the MOOC concept and how they view MOOCs as a source of learning (Chan, 2013). The next section will show the existing studies that address the development of MOOCs in China.

  • Educational studies of MOOCs in China

When MOOCs developed into a significant talking point for educators and administrators in China since 2013, Chinese researchers have attempted to understand the role of the university in the digital age. The MOOC’s format of teaching and learning has received significant coverage in the China higher education literature (e.g., Liu, 2015). Advocates suggest that MOOCs learning model is significant for the higher education system in China because it is opening the door of higher education for all Chinese Internet citizens. They believe that MOOCs create an online learning

environment that can meet Chinese learners’ needs. (e.g. Hao, 2013; Yuan & Liu, 2014; Yang et. al, 2014). Conversely, some critics (e.g. Yao, 2014) take issues with the emerging challenges in MOOCs, such as low completion rates, lack of a sustainable model, and plagiarism.

The positive influence of MOOCs on teaching and learning process has discussed by many scholars in China (e.g. Zhao, Wang & Ma, 2015). The China higher education system should take it as an opportunity to upgrade their online education (Zheng, 2016a). One study conducted by Liu (2015) analyzes the influence of MOOC on Chinese higher education reform. The study explored three main questions that both educators and administrations are concerned with such as: “ a) What is the advantage of MOOC and why does its arrival exert such a huge impact? b) Will MOOC replace the traditional education model? c) What kind of reform higher education will face in MOOC era?”(p.23). The study examines the advantages and drawbacks of MOOCs learning model and gives a comprehensive analysis. Based on the historical and cultural analysis of MOOCs characteristics, the author believes MOOCs learning is an unavoidable trend and provides a new opportunity for China higher education. The author puts forward a new blended learning model as a suggestion to reform Chinese higher education under the wave of MOOC. The study recommends a concept called “MOOCable”, a method of combining MOOC with the traditional teaching. In this frame, utilizing Small Private Online Courses is suggested to provide more suitable courses for a certain group of learners.

The skeptical voices about MOOCs emphasize the challenges. One challenge need to consider is the lack of digital literacy of instructors and learners (LNO, 2014). As Ng (2012) pointed out, the integration of digital technologies into learning require learners to attain a level of digital literacy that is appropriate to enable them to be comfortable in online learning with ease. According to Martin & Grudziecki (2006), digital literacy a prerequisite to acquire the skills and knowledge in the digital age.

Another challenge for Chinese learners using MOOCs is the occurrence of technical problems. Because of the policy of the Internet censorship from China government, Chinese learners have difficulties that page loading speed of a foreign website is very slow, even cannot connect at all. For instance, Youtube, as the most widely used tool to make video courses available, is blocked in China. Besides, some Chinese scholars

are concerned about the western MOOCs pedagogy might not fit for Chinese learners (Zhang, 2013, as cited in LNO, 2014). According to Zhang (2013), MOOCs introduce many foreign ideas, which will affect the Chinese ideology and socialism. When offering online courses rooted in the western ideology on a global level, cultural differences may be disregarded in MOOCs and lead to barriers of understanding for Chinese students.

Some researchers (e.g. Yang et al, 2013) have delved into the extent of Chinese learners’ awareness and their familiarity with MOOCs. Such studies did not account for MOOCs learners’ attitudes and perceptions. A research conducted by Zhou (2016) collected data relating to the self-determination of learning on MOOCs from Chinese university students. The results show that learners’ motivation of learning from MOOCs depends on the effectiveness of course design. Furthermore, the study found that Chinese university students had a common interest in learning in an autonomous learning environment. The study also indicates extra constructs should be measured in future studies, such as “self-efficacy, competence, user involvement and user characteristics” (Zhou, 2016, p. 200).

Currently, little systematic research has been done to examine advantages or limitations associated with MOOCs and learners’ attitudes and perceptions (Hao, 2013). The research areas, such as technology aspects, learner attitudes and facilitator perspectives from MOOCs are still need to be explored. Such understandings can address the variety of concerns that potential learners may raise about the MOOCs learning model (Cole & Timmerman, 2015). Without research from learners’ experiences and attitudes, it is difficult to understand how MOOCs can support learners in pursuit of higher education in China. Based on the limited empirical evidence, some researchers (e.g. Yang et al, 2013) have suggested that further research on MOOCs must achieve a critical mass of learners to understand their attitudes and perceptions toward higher education. The existed volume of data analysis is still limited that restrict understanding of teaching and learning in the MOOCs model. As Siemens (2012) sates, “MOOCs may well be a transitory stage for education. The concerns that MOOCs raise need to be addressed before this course format is accepted broadly” (p.10).

Literature also shows the potential for exploring the possibility of MOOCs learning in

the developing world. As Anderson (2008) suggest, online learning is a tool for developing countries to meet the demand of education by providing a low-cost and flexible alternative. It is believed that online learning in developing countries has huge potential for the raising number of enrollment in higher education (e.g.

Dhanarajan, 2001).

  • Online learning theories:

Generally speaking, online learning refers to the use of ICT to deliver a broad array of solutions in education (Selim, 2007). Online learning has created new opportunities to provide learning options and it is a technique to enhance education through digital media by utilizing ICT on the online context (Bhuasiri et al, 2011). Anderson (2008) suggests, properly designed online learning contents can encourage students and promote effective learning process. It allows flexibility of access through combining digitally delivered materials with learning support and services.

As innovative technology, online learning has been widely predicted to play impact on education. Due to the advantages, online learning is emerging and developing very rapidly around the world, including developing countries, like China. The benefits provided by online learning include cost-saving, increased convenience, consistent delivery of materials, content standardization, and accessibility to information (Mairal et al, 2010; Jolliffe, Ritter & Stevens, 2012). In recent years, many higher educational sectors are concentrating on the online learning environment by using ICT to enhance teaching and learning activities. Online learning has started to embed itself as part of an education environment (Anderson, 2008). Meanwhile, the growth of online learning has fueled the importance of lifelong learning. From online learning, learners have more opportunities to update their knowledge and skills, explore information on the Internet, and improve their skills (Herrington, Oliver & Reeves, 2002). In an online learning environment, learners can determine their interaction and manage their own learning (Milligan & Littlejohn, 2014).

Previous online learning studies have investigated the relationship between models of online learning and student performance (e.g. Picciano, 2002; Davies & Graff, 2005; Stansfied & McLellan, 2004). Such studies have profound instructional implications for educational practitioners in their teaching activities. Some research explored educational settings based on students’ learning abilities and an environment as fixed entities to their learning strategies (Hall, Ramsay & Raven, 2004). The findings provide a distinctive view of initial learning strategies and how instruction can be facilitated to support students’ learning experience and optimize their achievement.

  • Attitudes towards MOOCs:
  • Factors affect attitudes towards online learning

The growth of online learning depends on learners’ attitudes towards it, including their acceptance, enthusiasm and satisfaction (Drennan, Kennedy & Pisarski, 2005). Theories of learning behaviors maps how individuals carry out learning motives and indicate that the effectiveness of using advanced educational technologies depends upon positive attitudes from users. With positive attitudes, learners will have greater behavioral intention and will be in a high engagement in the teaching and learning process. Brock and Sulsky (1994) suggest two beliefs as components of attitudes towards using technologies: a useful tool and autonomous entities. Loyd & Loyd (1985) identified anxiety, confidence, enjoyment, and usefulness in their research scale about attitudes towards computers. Competence perceptions play an important role in learners’ motivation and online learning actions. Chen and Jang (2010) pointed out that students who are feeling competent with tasks are more likely to use strategies to solve problems. Moreover, Link and Marz (2006) suggest that the attitudes towards online learning associated with learners’ digital literacy. Digital literacy involves a large variety of skills that enable learners to engage in an online learning environment. As Alkalai (2004) suggest, digital literacy includes complex cognitive, sociological and emotional capabilities, rather than the mere ability of using digital devices. Studies found that goal-oriented learning has independent and positive effects on students’ learning interest and performance (Davis, Bagozzi and Warshaw, 1992).

Theories of learning behaviors attempt to map how individuals carry out learning motives. These theories indicate that the effectiveness of using advanced educational technologies depends upon positive attitudes from users (e.g., Liaw, Huang, & Chen, 2007). According to Triandis (1972), learning attitudes consists of affective (emotion/feeling), cognitive (beliefs), and behavioral (action/intention) aspects. With positive attitudes, learners will have greater behavioral intention and will be in a high engagement in the teaching and learning process.

Many studies from research have shown the positive aspects of online learning. A study conducted by Fathema, Shannon, & Ross (2015) investigated learners’ attitudes of using the Internet for learning. The result indicates learners have positive attitudes when they use the Internet in academic experience. Liaw (2008) conducted a research to investigate what factors affect learners’ attitudes towards online learning. The results suggest a variety of critical factors, such as digital literacy, instructors’ attitudes, flexibility, high quality of course design, and assessment. Another study from Williams et al (2005) indicates several factors that relate to students’ attitudes of online learning, such as content, personalized feedback, interface and learning communities. The study also suggests that well-designed content needs to be presented in an easy format.

In a computer-mediated learning environment, active learning helps learners achieve their potential goals (Risemberg & Zimmerman, 1992). However, the disadvantages of online learning are also obvious (Jolliffe, Ritter & Stevens, 2012). Learners are isolated rather than closely connected with peers and instructors in a learning community. Although the Internet has strength in delivering information to users directly, the Internet may be more attractive for users in shopping, online games,

messages chatting (Greenfield, 1999), but not that attractive in learning online courses. Furthermore, it seems that web-based instruction is not an ideal learning approach because students may get access to unlimited information rather than problem-based learning (Robey, Khoo & Powers, 2000). Concerning the MOOCs learning, as Rosa,

Sarrico, & Tavares (2016) state in their book, MOOCs learning innovation is still in its infancy and there is a long way ahead before we can assess MOOCs’ long-term impact on higher education.

  • MOOCs learning context:

The MOOCs learning environment offers a highly organized and structured learning context with fragmented information (Siemens, 2012). In such context, instructors or facilitators structure the learning contents under articulated goals and outcomes. A student has access to a web-based learning context where the basic elements are designed and structured to guide their learning tasks, such as lectures, reading, extra learning resources, and activities. Like a traditional course, assignments and assessments are also provided. Although xMOOC’s learning model adopts the traditional education approach by using video presentations, quizzes, homework, and assessment in the courses (Pisutova, 2012), such an environment produces quite different perceptions and behaviors from learners.

When viewing MOOCs learning context, Siemens (2012) describes the specific characteristics as its name: a) Massive, involving an enrolment of a large scale of students; b) Open, in terms of access, learn course contents and participate in guest lectures for free; c) Online, teaching and learning activities are arranged online; d) Courses, schedules are set and the contents are structured. MOOCs model creates an online learning platform through a collection of application of digital technologies (Downes, 2005). In such platform, a variety of knowledge contents are created, authorized and delivered. Learners can choose the topics based on their own needs and interests (Guàrdia, Maina and Sangrà, 2013; Pellas, 2014). The potential of digital technologies provokes fundamental changes of teaching and learning contexts (Siemsen and Jansen, 2014).

The context of MOOCs learning provides a picture that meaningful and sustained learning takes place that learners have choices and control their learning processes (Saadatmand and Kumpulainen, 2013). As in the case of the Internet-based learning, learners can perceive the authentic experience in a way that is informal, engaging and self-regulated. In a study conducted by Katyal and Evers (2014) about students’ perceptions of online learning, the results show that most students can see the connection between their learning courses they selected and the relevance in real-life situations. The study also indicates students’ perceptions about the internet-based learning as the best approach for them. The underlying reason for this is the nature of the Internet as learner-friendly, which makes online learning attractive by providing autonomous learning. In MOOCs, learners can make registration for free and get

access to any course they are interested in regardless of the prior qualifications. Katyal and Evers (2014) argue learners in online settings are self-driven and autonomous, shifting from a qualification outcome to the real knowledge acquisition. However, although the shift to online learning context does not affect the importance of teachers’ influence on learners, educators have to adapt to the new reality in online learning settings.

Theorists (e.g., Vygosky, 1962; Lave, 1988; Rogoff, 1990) presume that cognitive activity is closely contextual bound that one can never distinguish between cognitive ability and affective state. The sociocultural theory of learning from Vygosky (1962) emphasizes the unique context and circumstances concerning an internalization process and the nature of change. According to Vygosky (1962), an individual’s behaviors are consciously constructed in a form of cognitive scheme. Beyond the biological process, Vygosky (1962) believes that an individual’s learning experience is constructed through the interactions and communication in social context, which enormously expand man’s powers and make the wisdom of the past analyzable from “learning to learn strategies and procedures, such as rehearsal, elaboration and metacognitive, awareness such as conscious monitoring of one’s cognitive strategies” (p.215).

Leontief (1975) proposes an idea that in a goal-directed activity, objects themselves become energizers, goals and tools. Out of the context of this system in the activity, they lose their being “as energizer, as goals or as tools” (p.28-29). The concept exceeds the former area of learning environments and learning scenarios. Siemsen and Jansen (2014) emphasize utilization of digital tools in learning. They suggest that, in a digital age, it is important for individuals using technology as a tool to self- organize their knowledge, form information connections, and create knowledge patterns. According to Johnson et al (1998), learning is a self-organizing process because it enables an individual to classify interaction in a learning context and make change. Therefore, MOOCs can help learners to enhance their meaningful learning and the novel features of MOOCs promote the adaptations of conventional courses in higher education (Breslow et al., 2013; Hood, Littlejohn and Milligan, 2015).

  • Self-regulated learning:
  • Theories of self-regulated learning:

Theories and research on self-regulated learning emerged since mid 1980s, addressing the question of how students control their own learning process. Self-regulated learning studies cover a variety of forms of learning behaviors and psychology, including reading, studying, programmed instruction and interaction skills. Self- regulated learning has been studied in traditional education context, referring to the planned thoughts, feelings and actions that are self-generated to achieve learning goals (Zimmerman, 2000).

Current theories show some optimistic perspectives on self-regulated learning, such as systems thinking, brain research in psychology, constructivism and social constructivism, emphasizing connections to transform thinking and behavior to meet the learning needs (Zimmerman, Bonner and Kovach, 1996). Paris and Byrnes (1989) examined the dynamics of self-regulated learning from a constructivist perspective, focusing on how the underlying aspects of self-regulated learning can promote desired actions and identities. According to Paris and Byrnes (1989), generally speaking, self- regulated learners better performed in academic learning because they control their learning process and environment. They are always confident in taking challenges, practice and exert hard work to give rise to academic achievements. Self-related learning is a notion that students have a great deal of responsibility for their own knowledge construction (Kuiper, 2002). Therefore, self-regulated learners develop deep learning of subject matter and they are in higher sense of self-efficacy to exert efforts by directing and regulating their own learning behavior towards their goals.

Promoting students’ self-regulated learning is one of goals of education to help students use learning strategies effectively, appropriately and independently (Azevedo and Hadwin, 2005). Studies about online learning indicate that there is a significant relation between achievement in online environment and self-regulated learning.

Zimmerman and Kitsantas (1999) examined the effects of goals and academic skills. They found that students who are strongly in setting the goals of learning outperformed the students without learning goals. Similarly, the research from Garcia and Pintrich (1991) also found students who had most adaptive motivational beliefs,

high levels of self-regulated learning strategies performed better in terms of course grades. Learners analyze the context to define tasks, set goals and make strategies, monitor the process and evaluate the performance (Printrich, 2000).

Sweller et al (1998) investigated problem solving in self-regulated learning, indicating that the more information with guidance in the conditions, the better students can add solutions to the overall problem. Pressley et al (1990) reported that conditional knowledge for self-regulated learning is rich among learners in higher education.

They differentiate conditions for taking particular types of notes in classes or lectures, recording different types of materials and mange time plan. Solving problems is enhanced when learners can apply operations to reduce the difference between the current state of problems solving and the solutions (Sweller et al, 1998).

  • Self-regulated learning in online education:

Pintrich (2000) pointed out that self-regulation in online learning seems more important than that in a traditional face-to-face learning environment. In a computer- assisted online learning environment, learners need to be more proactive and self- directed. In online learning context, many studies investigated the positive association of self-regulated learning with academic outcomes (Pintrich, 2000). Shih and Gamon (2001) conducted a research to investigate the correlation between online learning strategies and performance. The results show a high correlation between learning strategies and academic achievements. The students who are using their learning strategies in online courses do better than the ones who use the lower frequency of learning strategies. As Shih and Gamon pointed out, the self-regulated learning strategy encourages them to actively memorize, elaborate and organize their learning process. Another study from Brak, Lan and Paton (2001) shows that different levels of distinct profiles of self-regulated learning and such differences significantly impact learners’ academic achievement and outcomes through online learning. The study also suggests further studies need to explore more perceptions from learners.

  • Models of self-regulated learning:

In education research, self-regulated learning has grown out of more general efforts (Zimmerman and Schunk, 1989). According to Zimmerman (1990), self-regulated learning is a fundamental skill in the learning process that learners control over their thinking, effect, and behavior. Zimmerman (1990) characterized a model that includes four phases in self-regulated learning. Phase 1 is defining the task in which learners process the conditions of information to characterize the tasks. For example, a teacher’s guidance and explanation for a homework assignment is a type of task conditions. The role of learners is to generate a task definition that can be monitored relative to their standards. In Phase 2, it is about planning how to reach the goals. The learner frames a goal and assembles a plan, by making up any problem, solving it, and identifying the methods. Learners begin to consider how to apply tactics and strategies in a self-regulated way. Phase 3 is about enacting tactics. Learners use tactics to build up operations and knowledge of the subject area by constructing information to make progress on the task. Phase 4 is adapting meta-cognition, which is optional. In this phase, learners make adaptations to carry out self-regulated learning, by accreting or adding conditions, turning conditions and restructuring to create different approaches to addressing tasks.

Similar to Zimmerman’s scheme, Winne and Hadwin (1998) provide a framework of self-regulated learning through classifying four different phrases of self-regulated learning, with the assumption that self-regulated learning is an active and constructive process following a cognitive perspective. Phase 1 concerns the perceptions of the context and in relation to planning and goal setting. Phase 2 involves meta-cognitive awareness of the self and context. Phase 3 represents efforts to control the tasks.

Lastly, Phase 4 involves reactions and reflections.

Paris and Byrnes (1989) identify some key characteristics of self-regulated learning, such as intrinsic motivations, deep understanding, mental development, progressive refinements, developmental constraints, and reconstruction. Paris and Byrnes (1989) also suggest that learning is contextualized to shape the content and progress of thinking, through which individuals can construct self-regulated learning in their unique environmental circumstances and histories.

Harter (1999) distinguished the self as object into four main meanings, including “self-awareness, self-agency, self-continuity and self-coherence” (p. 16). According to Harter (1999), students understand themselves and construct personalized interpretations of their own learning and actions, partly in relation to their own experiences and anticipated futures that reflect coherence and optimism. In self- regulated learning, learners regulated themselves towards specific practices, identities and goals to promote an individual’s status, success, or well-being.

  • The role of teachers/instructors in online learning:

New technologies provide the opportunity for creating a student-centered environment of learning. In such teaching and learning context, teachers may need to shift their role as facilitators (Maor, 2010). Studies about instructional design also suggest that students provided with metacognitive insights and social supports can use effective strategies in their learning and the learning skills can be taught to promote their learning (Paris, Byrnes and Paris, 2001). As discussed about self-regulated learning, students needs guidance in conditions to solve problems (Sweller et al, 1998).

Several researchers pointed out that attention should be drawn to the role of external regulation in the learning process (Weinert, Schrader & Helmke, 1989). McCombs and Marzano (1990) suggest that external regulation can provide support to learners who are in a lower-level of cognitive awareness and those who lack ability of task control. The students may consider external regulation as essential for their learning. They may rely on teachers’ guidance to help them to extend their knowledge and skills, by expecting teachers to tell them what tasks they need to do, how and when to finish them, rather than self-directed learning by themselves.

Teachers/instructors have the responsibility to scaffold learners become strategic and independent and they can use a constructivist frame to help learners acquire and apply cognitive strategies (Maor, 2010). Dabbagh (2003) pointed out the important role of teachers/instructors in online learning context to provide support to students, changing

from a didactic way. Such transformation requires more knowledge from teachers/instructors in the use of learning technologies.

  • Conclusion: the case of Chinese MOOCs learners

In conventional Chinese culture, students’ opportunities of getting access to universities determine their future with dreams and desires. In Chinese students’ perceptions, higher education in universities is the most important path that can lead them to success. As one student from a working-class family said, when he mentioned about his motivation of going to a university, “This is the only way I can get chance to compete with the second generation of rich people” (Hua, 2012).

With the development of digital technology in China, Chinese people can get much more information and knowledge from the Internet. To investigate Chinese MOOCs learners’ perceptions about this innovative educational technology, the theories provide academic guidance for this research. The potentials of utilizing MOOCs to increase learners’ opportunities in society are still promisingly unfolding. The existing theoretical framework and models provide support for this study.

Chapter Three: Methodology

  • Triangulation methodology:

During the process of research design, I planned the procedures with detailed methods of data collection, analysis, and data interpretation. The aims of this study are to investigate the attitudes and perceptions of Chinese students’ learning MOOCs experience. Through the study I build on the existing literature and consider learners’ perceptions of participation in MOOCs online learning environments.

When it came to the consideration of methodology, I took into account of the ethical and epistemological approaches before embarking on the research design, to ensure the transparency and trustworthiness of this study. Transparency is regarded as sound research practice by many professional organizations (Chatfied and Collins, 1980).

Maxey (1999) suggests that researchers need to engage critically and reflexively with social research. A good approach is attempting to do this from “where I am at” (p.206), which emphasizes critical reflexivity in the whole process. When I started to bring reflexivity into my research, I need to consider expectations, assumptions and beliefs (Watt, 2007) in the design of research methods, instruments, sampling strategies, and data collection and analysis. As Cohen, Manion & Morrison (2007) suggest, in education research, that ethical and epistemological issues need to be considered at each stage of research design. My position in educational research about epistemology is rooted in the idea as stated by Hofer (2001), “knowledge and knowing is a system of more-or-less independent beliefs. Each of these clusters of research is reviewed in turn, followed by alternative views of how we might conceptualize this field…these conceptions of the model inform our thinking about what the educational implications might be.” (p.355). The current research explored learner attitudes and perceptions of MOOCs, an innovative education technology, and this requires a deep understanding of how learners think and behave in this context.

I do acknowledge that rigorous research should address the complexity of aspects in educational settings (Bassey, 1999). There are three main approaches for social science research: qualitative, quantitative and mix methods (Brewer, Newman & Benz, 1999; Creswell, 2013). A research utilizing mixed methods incorporates both qualitative and quantitative methods, which is usually described as triangulation (Mathison, 1988). Although quantitative research can produce findings by means of statistical procedures, it is difficult to produce descriptive data to make sense of actions, intentions, and understandings (Hatch, 2002).

Qualitative and quantitative research methods represent different paradigms (Sale, Lohfeld & Brazil, 2002). Inquires in qualitative approaches focus on the meaning from individuals and make the complexity of the settings (Creswell, 2007).

Qualitative research methods use words or open-ended questions for exploring meaning for individuals or groups to understand a social phenomenon while quantitative research methods are to exploit the potentialities of social observation by testing the validation of results in the form of numbers that can be analyzed in statistical techniques. Both qualitative and quantitative methods are inquiries that can be used for testing theories, protecting assumptions, controlling explanations and

generalizing findings (Campbell, 1955). The combination of qualitative research methods and quantitative research methods can be utilized to provide holistic interpretation in social research (Jick, 1979).

Education research is a fundamental area in social research because education is a basic human process (Shank, 1995). Social research is about people’s behavior and based on everyday knowledge to typify the social reality from situation to situation. According to Burrell and Morgan (1979), meaning interpretation of the social world is dependent on the people identifying the purpose or goal they seek. In social research, the context is crucial because individuals align their actions to others’ actions by making indications to themselves and constructing how others wish or might act in certain circumstances. Arksey and Knight (1999) suggest the research methodology design need to take into account the research approach selection and the specific research methods based on the research questions being addressed, the researcher’s personal experience, resources and audiences for the research investigation.

For the current study, in order to make generalizations of Chinese learners’ attitudes and perceptions, I chose to collect quantitative data from a questionnaire. Many educational researchers (e.g. Richardson & Swan, 2003; Drennan, Kennedy & Pisarski, 2005; Muilenburg & Berge, 2005; Liaw, Huang & Chen, 2007) have employed survey questionnaire to address the topic of student attitudes towards online learning. However, I also acknowledge that it is difficult to address some issues through a quantitative method (Goldstein, 1986). For instance, to explore attitudes and perceptions of MOOCs learners, quantitative data have limitations of deeper insights into learners’ behaviors in MOOCs and it is difficult to depict correspondences and discrepancies in a statistical way (Pope, Ziebland, Mays, 2007). To enhance the credibility of the inquiry, I decided to apply triangular techniques in the current study. As Feuer, Towne, and Shavelson (2002) suggest, properly applied triangular techniques in social research can support stronger scientific inferences and “different perspectives constructively engage with each other around the common goal of advancing understanding” (p.8).

Specifically, based on the research aims, two research methods were used: a survey questionnaire and interviews. Quantitative data collection through the questionnaire

was carried out first to understand patterns. The following interviews for qualitative data collection helped me to gather additional information and interpret the findings.

  • Procedures:

Following RREA approval, I started the data collection to explore attitudes and perceptions among Chinese learners. Before the release of the questionnaire, I discussed with three Chinese postgraduate students of the University of Manchester to test the items. The three students who involved in the discussion had learnt one or more courses from MOOCs. The discussion pre-validated this questionnaire items for clarity, usage of language and comprehensiveness (Churchill, 1979). Such procedure helped me identify some common misunderstandings of the questions (Cohen, Manion, and Morrison, 2007). For example, in the discussion, we found some of the items were in the same meaning, just in different expression. Then, I deleted the redundant items and rearranged the sequence to avoid any confusion. As recommended by many researchers (e.g. Reja et al, 2003), I restricted the completion time within 15 minutes, taking into account that overlong questionnaires may cause a low percentage of answers. After finishing the edits to some of the questions, I launched the final questionnaire for the research.

Quantitative and qualitative data collection took place in the period from June 15th to July 31st, 2016. I sent out a survey invitation email with the online link. Participants were able to click the link, which took them to a web-based survey questionnaire.

Participants filled out optional items and answer one open-ended questions at the end of the questionnaire (See Appendix A). A gentle reminder email message was sent two weeks following the initial mail out for participants who had not yet responded. The in-depth interviews were conducted at the end of July. Each interview was approximately 20 minutes. Data analysis was organized following data collection from interviews. The questionnaire was released in Chinese version.

  • Questionnaire
  • Internet-based survey

An Internet-based survey was conducted to explore Chinese learners’ attitudes and perceptions about MOOCs. I decided to opt for an online survey in this research for several reasons. The foremost one is the purpose of the study. As Sills and Song (2002) state “the Internet is a delivery method for survey research and it can be used for particular populations that are connected and technological savvy” (p.28). As I attempted to investigate MOOCs learners’ attitudes and perceptions, a population of the Internet users, recruitment from an online survey can reach the population with special interests related to the survey (Selm & Jankowski, 2006). In addition to the particular group of study, the advantages of an online survey made me decide to employ the Internet as a tool in this research. An online survey has a variety of advantages mentioned in the literature, such as “reduced cost, convenience, speed of delivery and response, ease of data cleaning and analysis” (Sills & Song, 2002, p.28). The advantages suggest that an online survey is well suited for studies among MOOCs learners.

  • Questionnaire design

A questionnaire can be used for a multivariable survey (Rossi, Wright, & Anderson, 2013), which can help me seek a wide range of information from Chinese MOOCs learners. As a quantitative research instrument, a questionnaire can be used to obtain data on the amount of factual information acquired from responses (Hovland & Weiss, 1953). In the questionnaire design, I tried to find some conceptual frameworks from the literature to identify the variables for measurement of MOOCs learners’ perspective and behaviors, such as their attitudes, feelings, values and beliefs. As Punch (2005) suggests, a clear conceptual map is crucial in questionnaire design, and should be the first step in its development. The conceptual map based on literature helped me generate questions from the general type of variables to the specific ones (See Table 1 Measurements and items in survey questionnaire in Section 3.4).

Furthermore, I also made sure that all the participants who replied to my online questionnaire knew that their responses are confidential. Survey researchers in social science should make privacy assurances to the participants that their information is anonymous and/or confidential (Whelan and Carolina, 2007).

  • Type of questions:

Close-ended questions and open-ended questions were both used in the questionnaire. Generally speaking, close-ended questions yield a higher percentage of answers (Griffith et al, 1999). Open-ended questions produce a more diverse set of answers, allowing respondents to express opinions without being limited to the offered alternatives (Reja et al, 2003).

Likert scale items are mostly used in the questionnaire (See Appendix A) design, ranging from 1 (strongly agree) to 5 (strongly disagree) to explore learners’ attitudes and perceptions. A Likert scale has multiple categories about a particular issue to indicate individuals’ opinions, attitudes, feelings or beliefs (Boone & Boone, 2012). According to Messick (1989), Likert scale instruments are frequently used to measure the psychological constructs, for investigating an individual’s affect or cognition, such as motivation, anxiety and self-confidence. Likert-scale items have some advantages: 1) Data can be collected more quickly; 2) Participants can be encouraged to provide reliable personal estimates; 3) Validity of data interpretations can be provided in a variety of means established already; 4) The data from Likert-scale questions can be profitably compared, and combined with qualitative data collecting techniques (Nemoto and Beglar, 2014).

  • Online survey and sampling:

According to my research aims, the target participants were the Chinese learners who have used MOOCs in the past. I chose Sina Weibo to find the participants. Sina Weibo is the largest online social media in China, which is considered as the Chinese version of Twitter. I searched the posts about MOOCs learning experience and sent out an email for survey invitation with the link of online questionnaire. Emails were sent in a total number of 100. Respondents needed to complete the questionnaire items by clicking answer options or by entering free answers. When finishing all the questions, respondents clicked on a “submit” button to complete the questionnaire.

  • Questionnaire measurements and variables

The measurements of learners’ attitudes and perceptions were developed according to the literature involved in previous studies. Based on the previous literature, the questions were developed with adaptation to the context of MOOCs (See Table 1)

Table 1: Measurements and items in survey questionnaire

Measurements and items
Variables Questions Literature References
    Cognitive competence Digital literacy I am comfortable using a computer to participate in a course. Link and Marz, 2006
I can write/read well through online learning.
Self-efficacy I think I will do well in it then I tend to put more effort. Wang &Baker, 2015; Halawa et al, 2014
I can schedule time well to learn in MOOCs.
Motivation   Interest   I can choose the courses which I am interested in. Hew & Cheung, 2014; Bandura & Schunk, 1981
Self- satisfaction I can enjoy learning at my own pace. Milligan, Margaryan, and Littlejohn, 2016
Future plan Learning in MOOCs is important for my future. Dench & Regan, 2000
MOOCs will benefit my study/career in the future.
Personality It is easier for me to participate in MOOCs because I am shy. Cercone, 2008
Value Usefulness MOOCs are useful to me. Wu & Chen, 2015
Relevance MOOCs have a wide range of courses for me to choose what I want to learn. Davis et al, 2014
Ease of use MOOCs design is easy to use. Billsberry, 2013
  Flexibility MOOCs are flexible. Baturay, 2015
MOOCs provide me learning at my own pace.
Cost-saving MOOCs are cost saving. Ruth, 2012
Effectiveness Meet learning needs MOOCs can meet my learning needs. McLoughlin, 2013
Worth in personal/profe ssional life I improved skills in study/career from MOOCs Liu et al, 2014
    Interaction MOOCs contribute to effective communication online. Garrison & Cleveland, 2005; Stansfield, Mclellan & Connolly, 2004
MOOCs create a sense of community with the instructor and fellow students.
MOOCs promote participation and interaction.
Difficulties Personalized feedback It is difficult to ask/get answers to questions. Daradoumis, 2013
Technical problem/usabi lity issues There are always technical issues occur. (i.e. the Internet connection, lack of technical resources) Sharples et al, 2015
  Personal learning challenge It is hard for me to retain information from online learning.     Hew & Cheung, 2014
I am not interested in studying.
I feel hard to pay attention/stay on task.
Self- regulated learning Importance Self-regulated learning is important to my success in MOOCs learning  
Defining tasks I determine the courses myself.
Setting goals and plans I always make a learning plan of the courses in MOOCs.

Six categories (See Table 1) of variables were measured in five-point Likert scale questions, ranging as “1 Strongly agree – 2 agree – 3 neutral – 4 disagree – 5 Strongly disagree.”

In self-competence, four items were presented including two measurements: digital literacy (Link and Marz, 2006) and self-efficacy (Wang &Baker, 2015; Halawa et al, 2014). For digital literacy, two statements were used to evaluate learners’ opinions of using digital tools for learning: “I am comfortable using a computer to participate in a course” and “I can write/read well through online learning.” For self-efficacy, two statements were involved to ask learners to rate their view of the role of self- confidence in learning, as “I think I will do well in it then I tend to put more effort” and “I can schedule time well to learn in MOOCs.”

Five items were used to examine motivation, including: interest (Hew & Cheung, 2014; Bandura & Schunk, 1981), self-satisfaction (Milligan, Margaryan, and Littlejohn, 2016), future plan (Dench & Regan, 2000), and personality (Cercone, 2008). Specifically, the item “I can choose the courses which I am interested in” was used to examine how learners rate interest as a motivation; “I can enjoy learning at my own pace” asked learners to rate the role of self-satisfaction as a motivation; Two statements “Learning in MOOCs is important for my future” and “MOOCs will benefit my study/career in the future” were used to examine learners’ perceived importance of MOOCs learning for their future plan; The last item in this category was used to indicate if personality affects motivation, “It is easier for me to participate in MOOCs because I am shy”.

Value is referring to learners perceived preference and evaluation of MOOCs. Measurements were associated with the main advantages of MOOCs. Usefulness (Wu

& Chen, 2015) in the item “MOOCs are useful to me” was for learners to rate the overall view if MOOCs are useful for them; “MOOCs have wide range of courses for me to choose what I want to learn” was used to examine learners’ perceived relevancy about course contents (Davis et al, 2014); “MOOCs design is easy to use” was to examine their view of the easiness of using MOOCs (Billsberry, 2013); Two items of “MOOCs are flexible (time, learning methods)” and “MOOCs provide me learning at my own pace” were asked to rate the role of flexibility (Baturay, 2015); Lastly in this category, “MOOCs are cost saving” attempted to see if cost-saving (Ruth, 2012) affects learners’ preference of MOOCs.

In the category of effectiveness, “meet learning needs” (McLoughlin, 2013) in the item “MOOCs can meet my learning needs” was for learners to rate the overall view if MOOCs are perceived as a learning approach that can meet learning expectations; “I improved skills in study/career from MOOCs” was asked to rate the role of MOOCs in worth personal/professional life (Liu et al, 2014) for learners. Three statements were used to measure the perceived effectiveness of interaction (Garrison & Cleveland, 2005; McInnerney & Roberts, 2004): “MOOCs contribute to effective communication online”, “MOOCs create a sense of community with the instructor and fellow students”, and “MOOCs promote greater participation and interaction”.

In terms of difficulties, personalized feedback (Daradoumis, 2013), technical problem/usability issues (Sharples et al, 2015), and personal learning challenges (Hew & Cheung, 2014) were measured. “It is difficult to ask/get answers to questions” and “There are always technical issues occur (i.e. the Internet connection, lack of technical resources)” were used to examine learners’ level of agreement with problems of getting the answers and technical issues respectively.

In the category of self-regulated learning, one item was used to rate learners’ perceived importance of self-regulated learning, and other items were adapted from Zimmerman’s (1990) self-regulated learning framework. Specifically, “Self-regulated learning is important to my success in MOOCs learning” was used for participants to rate their perceived importance of self-regulated learning in MOOCs. According to Zimmerman’s self-regulated learning framework, the statement of “I determine the courses myself” was used to examine how independently learners define tasks; “I

always make learning plan of the courses in MOOCs” was used to indicate if setting goals and plans are important strategic process for learners; The phase of enacting tactics were measured by “I prefer to be in control of my online courses in MOOCs” by rating their monitored and controlled behaviors; Three statements were used to evaluate participants’ opinions of experiences in meta-cognition: “I tend to reflect on how well I have done after each course”, “I tend to go into all aspects of a topic in great depth while learning the courses”, and “I tend to explore new aspects of a topic without being told to do so as instructed”.

3.4 Interviews

In this research, two interviews were conducted with Chinese MOOCs learners. An in-depth interview is a qualitative research method that is commonly used in social

research (Ritchie and Lewis, 2014). Researchers use in-depth interviews for collecting data that reveal interviewee’s values, perceptions, experiences and beliefs under study objectives (Boyce & Neale, 2006).

Sample of interviews:

I used social media to recruit participants in the study. I sent an instant message on “QQ group” (a social media group among QQ users) to find the ones who had experience in learning MOOCs. The users who indicated that they had experience in learning in MOOCs replied to me about their interest in the topic. I sent an email invitation to them for the interview, attached the related information, such as an information sheet explaining the purpose of the study, and the consent form.

According to the response and research schedule, two participants for the interview were recruited in this research. They sent back the signed consent form and interviews were arranged at the end of July, 2016. The interviews occurred through real time video communication by using the software of Tencent QQ.

Semi-structured interviews:

An interview is a conversation between the researcher and the participant. Semi- structured interviews are conversational communication in a relatively open framework for obtaining specific information from a sample of the population and gaining a range of insights on specific issues (Mason, 2002). In this research, the

interviewing was semi-structured. According to Mason (2002), semi-structured interviewing has core features as follows: a) The interactional dialogue of exchanging conversation between two or more participants; b) A topic-centered approach with a flexible structure; c) A contextual perspective from situated knowledge. Therefore, interviews constitute a learning process that allows me to discover the certain aspects of MOOCs learners’ learning experience from the interactional exchange (Snape and Spencer, 2003).

The interview addressed questions in three main areas as follows:

  1. Why the participants use MOOCs and how they evaluated MOOCs as a method to enhance knowledge learning?
  2. How the participants perceive the advantages and disadvantages of learning in MOOCs from their personal experience?
  3. How learners manage their learning process in MOOCs and whether they perceive self-regulated learning as an important factor for achievements?

Thematic analysis of interview data:

The interview data were transcribed and coded into basic themes. Thematic analysis involves content analysis to systemize element characteristics, as well as combining analysis of codes in contextual meaning (Anderson, 2007; Guest, MacQueen and Namey, 2012; Joffe and Yardly, 2003). Thematic analysis provided an opportunity for me to gain a detailed understanding of the MOOCs learners’ experience and provided me with a useful strategy to understand the qualitative data.

Based on content analysis, the themes were identified under the interview topic guide, combing theoretical ideas and inductive raw information itself. The themes were drawn from existing theoretical framework ideas that allowed me to replicate and extend prior discoveries (Boyatzis, 1998). Besides, I also need to check the inter-rater reliability of coding to ensure coding decisions are explicit and consistent. Huberman and Miles (1994) proposed a method that summarizes the sequence of generating ideas from interview transcripts. I followed this suggestion in my study, the sequence includes noting the patterns and themes, discerning the themes, extracting stories that are related to literature, looking at the differences, and confirming the examined evidence.

As Creswell and Clark (2011) suggests, the member-checking in data coding can enhance credibility of the findings. After the identification of the main points generalized from the interview, I showed the key themes of interview data to the two participants, to make sure that the interpretations were well reflected what they mentioned in the interview. Then they confirmed no changes.

Chapter Four: Data Analysis and Results

  • Quantitative data analysis:

A total number of 51 Chinese MOOCs learners completed the online survey questionnaire, at a response rate of 51%. Questionnaire sample description is summarized in Table 2 as follows (see Table 2 in 4.1.1). For reliability, the internal consistency of variable among multi-items was measured by using Cronbach’s alpha in SPSS.

  • Sample description:

Among all the respondents, 25 were males and 26 were female learners. 23 out of the 51(45%) participants had used MOOCs between 1 to 5 years, 28 participants (55%) were less than 1 year. In terms of selection of courses, the percentage of language, social science, science & technology, and others are 25 (49.02%), 26 (50.98%), 17

(33.33%) and 14 (27.45%), respectively. 41 responses indicate that they had plans to continue in learning on MOOCs within one year, at the percentage of 80.39%. (See Table 2)

Table 2: Sample description

Gender of the participants Male 25 49.02
  Female 26 50.98
MOOCs learning starts 1-5 years 23 45.1
  Less than 1 year 28 54.9
  MOOCs Language   25   49.02
  Social science 26 50.98
  Science 17 33.33
  Other 14 27.45
    Want to learn MOOCs     Yes     41     80.39
within one year No 10 19.61
  • Attitudes and perceptions towards MOOCs learning experience:

For the examination of participants’ attitudes and perceptions of learning in MOOCs, five point Likert scales were used in the online survey questionnaire. As Jamieson (2004) states, a Likert scale in quantitative data collection is the most commonly used type of question assessing participants’ opinions of usability. Several likert-type items are combined into a single variable in a Likert scale. In social research, researchers usually use such type of questions to generate a quantitative measure or score that represents a character or personality trait (Boone and Boone, 2012).

In data analysis, according to Hogg and Smith (2007), assessing attitudes and perceptions in social research, the responses from participants may not need to be factually accurate, but need to reflect one possible feeling of the truth. Likert scale variables are fundamentally at the ordinal level of measurement (Cohen, Masion & Morrison, 2000). Cohen, Manion and Morrison (2000) suggest that in data statistics, Likert scale items can be analyzed by using non-parametric test techniques.

Cronbach’s coefficient alpha was used for checking scale reliability for assessing the internal consistency of a multi-item scale (Bland & Altman, 1997).

Cognitive competence:

Likert scales were used to rate the cognitive competence of MOOCs online learning on participants’ attitudes and perceptions from learning experience.

Two statements were used to examine participants’ opinions of their digital literacy (See Table 3). Combining categories show most participants are confident in their digital literacy (See Figure 1). 70.59% participants agree that they can write/read well in online learning and 76.47% participants agree that they are comfortable using computers to learn.

Table 3: Opinions about digital literacy in MOOCs learning experience

  Strongly Agree Agree Neutral Disagree Strongly Disagree
I can write/read well through online learning. 21.57% 49.02% 21.57% 7.84% 0%
I am comfortable using a computer to participate in a course 31.37% 45.1% 19.61% 3.92% 0%

Figure 1: Opinions about digital literacy in MOOCs learning experience

In self-efficacy, participants were asked to rate how they view their self-efficacy in MOOCs learning (See Table 4). When combining the categories of agreement and disagreement, the result shows a very clear indication of overall perceptions from participants (See Figure 2). Most participants perceive they are confident in MOOCs learning environment: they think they can manage time well (72.85%), and they believe they can do well to put more efforts (80.39%). (See Figure 2)

Table 4: Opinions relating to self-efficacy in MOOCs learning experience

  Strongly Agree Agree Neutral Disagree Strongly Disagree
I can schedule time well to learn in MOOCs 31.37% 41.48% 15.69% 11.76% 0%
I think I will do well and I tend to put more effort into a course. 31.37% 49.02% 17.65% 0% 0%

Figure 2: Opinions relating to self-efficacy in MOOCs learning experience


Participants were asked to rate the role of motivation in their learning experience in MOOCs learning. Seven statements in Likert scale rated motivational perceptions of learners on MOOCs (See Table 5).

Table 5: Learning motivations of using MOOCs

  Strongly Agree Agree Neutral Disagree Strongly Disagree
I choose the courses which I am interested in 29.41% 45.10% 15.69% 7.84% 1.96%
I enjoy learning at my own pace. 27.45% 52.94% 19.61% 0% 0%
Learning in MOOCs is important for my future 17.65% 45.10% 31.37% 3.92% 1.96%
MOOCs will benefit my study/career in the future. 29.41% 45.10% 15.69% 7.84% 1.96%
It is easier for me to participate in MOOCs because I am shy. 21.57% 37.25% 23.53% 7.84% 9.80%

From the combined categories in Figure 3, a clear indication can be ascertained. Overall, interest appears to be an important motivation of learning in MOOCs. 74.51% participants agree that they chose courses depended on their interest. Self-satisfaction

is also indicated as an important motivation, with 80.39% admitting that they can enjoy learning at their own pace. Two statements were used to examine how learners future plan impact their learning perceptions in MOOCs: “Learning in MOOCs is important for my future” (62.75% agreement) and “MOOCs will benefit my

study/career in the future” (74.51% agreement). A Cronbach alpha of 0.734 shows a reliable internal consistency between both statements. For the personality, more than half participants (59.82%) choose MOOCs learning because they think they are shy.

Figure 3: Learning motivations of using MOOCs


Participants were asked to rate the perceived value about MOOCs that impacts their preference. Likert scales were used to explore how positively or negatively the Chinese learners viewed MOOCs as valuable learning approaches. (See Table 6)

Table 6: Value of MOOCs from learner perspective

  Strongly Agree Agree Neutral Disagree Strongly Disagree
MOOCs are useful to me. 39.22% 47.06% 11.76% 0.00% 1.96%
MOOCs have wide range of courses for me to choose what I want to learn. 52.94% 35.29% 11.76% 0.00% 0.00%
MOOCs design is easy to use. 19.61% 41.18% 33.33% 5.88% 0.00%
MOOCs are cost saving (travel, materials). 56.86% 29.41% 9.80% 3.92% 0%
MOOCs are flexible (time, learning methods). 39.22% 49.02% 11.76% 0.00% 0.00%
MOOCs provide me learning at my own pace. 41.18% 39.22% 17.65% 1.96% 0%

When combining the categories of agreement and disagreement, a large majority of participants (86.28%) agree MOOCs are useful for them. 88.24% participants agreed with the relevance statement. More than a-half participants perceive easiness of use, with 60.79% agreement. Most participants 86.27% agree MOOCs are cost saving.

Similarly, most participants agree with the two statements (Cronbach alpha 0.734) about flexibility, “MOOCs are flexible” (88.24%) and “MOOCs provide me learning at my own pace”(80.40%). (See Table 7)

Table 7: Value of MOOCs from learner perspective in combined categories

  Agree Neutral Disagree
MOOCs are useful to me. 86.28% 11.76% 1.96%
MOOCs have wide range of courses for me to choose what I want to learn. 88.24% 11.76% 0.00%
MOOCs design is easy to use. 60.79% 33.33% 5.88%
MOOCs are cost saving (travel, materials). 86.27% 9.80% 3.92%
MOOCs are flexible (time, learning methods). 88.24% 11.76% 0.00%
MOOCs provide me learning at my own pace. 80.40% 17.65% 1.96%


Likert scales were used to explore how positively or negatively the Chinese learners viewed MOOCs provide effective learning approaches. Results from combined categories show clearly that most of the participants (82%) believe that MOOCs can meet their learning needs (See Figure 4) and 71% agree MOOCs help them improve skills (See Figure 5).

Figure 4: Opinions on whether MOOCs can meet learning needs

Figure 5: Opinions about whether MOOCs can support to improve skills in study/career

Three statements were used to rate the interaction from perceptions of learners (See Table 8). A Cronbach alpha of 0.855 shows a high internal consistency of the statements.

Table 8: Opinions on the interaction in MOOCs

  Strongly Agree Agree Neutral Disagree Strongly Disagree
MOOCs contribute to effective communication online 7.84% 31.37% 37.25% 19.61% 3.92%
MOOCs create a sense of community with the instructor and fellow students 1.96% 27.45% 41.18% 21.57% 7.84%
MOOCs promote greater participation and interaction 7.84% 27.45% 42.18% 17.65% 5.88%

Figure 6 shows the combined categories. Participant attitudes appear not positive towards MOOCs interaction relating to the learning effectiveness. Neutral opinions are in relatively large proportion. The views on whether MOOCs provide effective communication are almost equally split between agreement and neutral.

Figure 6: Opinions on the interaction in MOOCs


Statements in Likert scale were used to rate the difficulties from perceptions of learners (See Table 9).

Table 9: Perceived difficulties in MOOCs learning experience

  Strongly Agree Agree Neutral Disagree Strongly Disagree
It is difficult to ask/get answers to questions. 19.61% 23.53% 43.14% 13.73% 0.00%
There are always technical issues occur (i.e. internet connection, lack of technical resources…). 15.69% 21.57% 35.29% 21.57% 5.88%
I feel hard to be motivated in MOOCs learning. 5.88% 7.84% 29.41% 47.06% 9.80%
It is hard for me to retain information. 3.92% 9.80% 33.33% 43.14% 9.80%
I am not interested in studying. 0.00% 7.84% 21.57% 47.06% 23.53%
I feel hard to pay attention/stay on task. 7.84% 21.57% 29.41% 33.33% 7.84%

Table 10 shows the combined categories. The results show that personalized feedback “It is difficult to ask/get answers to questions” and technical problems “There are always technical issues occur” appear not commonly perceived as problems, with agreement 43.14% and 37.26% respectively. The views on the two problems above were almost equally split between agreement and neutral. Three statements (Cronbach alpha 0.732) were used to explore whether learners’ personal learning issues were viewed as difficulties. The results show that only small portion of participants take their personal issues of learning as problems: “It is hard for me to retain information” (13.72%), “I am not interested in studying” (7.84%), and “I feel hard to pay attention/stay on task” (29.41%).

Table 10: Perceived difficulties in MOOCs learning experience in combined categories

  Agree Neutral Disagree
It is difficult to ask/get answers to questions. 43.14% 43.14% 13.73%
There are always technical issues occur (i.e. internet connection, lack of technical resources…). 37.26% 35.29% 27.45%
It is hard for me to retain information. 13.72% 33.33% 52.94%
I am not interested in studying. 7.84% 21.57% 70.59%
I feel hard to pay attention/stay on task. 29.41% 29.41% 41.17%

The role of self-regulated learning in MOOCs

One question is to examine the perceptions of importance of self-regulated learning from learners. 82% participants believe that self-regulated learning is very important for their MOOCs learning. (See Figure 7)

Figure 7: Perceived importance of self-regulated learning in MOOCs

Six statements were used to examine how learners self-regulate their learning behaviors in MOOCs. (See Table 11)

Table 11: Role of self-regulated learning in MOOCs

  Strongly Agree Agree Neutral Disagree Strongly Disagree
I determine the courses myself. 49.02% 37.25% 11.76% 1.96% 0%
I always make learning plan of the courses in MOOCs. 23.53% 41.18% 31.37% 1.96% 1.96%
I prefer to be in control of my online courses in MOOCs. 29.41% 52.94% 17.65% 0% 0%
I tend to reflect on how well I have done after each course. 29.41% 29.41% 27.45% 7.84% 5.88%
I tend to go into all aspects of a topic in great depth while learning the courses. 31.37% 49.02% 17.65% 0% 1.96%
I tend to explore new aspects of a topic without being told to do so as instructed. 27.45% 50.98% 21.57% 0% 0%

From the combined categories in Figure 8, an overall indication can be ascertained. 86.27% learners determine their courses themselves. 64.71% learners make plans for their learning and 82.35% participants control their own process. Three statements (Cronbach alpha 0.734) about learners’ metacognitive adaptation in MOOCs: “I tend to reflect on how well I have done after each course” With 58.82% agreement, “I tend to go into all aspects of a topic in great depth while learning the courses” with 80.39% agreement and “I tend to explore new aspects of a topic without being told to do so as instructed.” with 70.43% agreement.

Figure 8: Role of self-regulated learning in MOOCs

86.27%                                  11.761%.9
64.71%                                31.37% 3.92
82.35%                                 17.65%0
58.82%                           27.45%      13.72%
80.39%                                  17.65%1.9
78.43%                                 21.57% 0
  • Open-ended question

The open-ended question in the questionnaire was: “Is there anything else you would like to add about your MOOCs learning experience?”

As Geer (1991) suggests, an open-ended question allows participants to respond freely to the inquiry without limitations, this question attempted to collect rich data about learners’ perceptions that may not be mentioned in the questionnaire. The open- ended question received 19 responses out of 51 totally, at a response rate at 37%. The data were analyzed in thematic coding. According to the answers, 16 general themes were labeled at first. Based on the similarity of concerning issues, they were divided and then four thematic categories were established (See Table 12).

Table 12: Themes and codes extracted from answers of the open-ended question

Thematic categories Number of referneces   Initial coding
    ! convenience
    ! useful information
    ! flexible
Benefits 9 ! rich course content
    ! authorized contents
    ! global perspective
    ! linguistic barrier
    ! without personalized contents
    ! Internet connection problem
Difficulties 6 ! lack of support
    ! lack of interaction
    ! useless certificate
  Learning strategy   5 ! ! ! clear task and plan self-paced learning course preparation
Negtive impact 1 ! ignorance of face to face communication
  1. About learners perceived MOOCs are beneficial for them (9 references), several advantages of MOOCs were mentioned, including convenience, flexibility, rich and reliable contents, and global perspectives. As one response stated, “ MOOCs provide a variety of course contents, so I can select what I want to learn. Besides, MOOCs are very convenient and I can learn when I have time.”
    1. About learners felt there are difficulties in learning from MOOCs (6 references), answers indicated several factors, ranging from linguistic barriers to the lack of interaction. One response raised the issue about useless of the certificates from MOOCs and this reason may even make them stop learning in MOOCs, “I may want to quit learning in MOOCs, because the certificates

are not qualified and not accepted in the whole society. I would rather use the time to get a certificate from a university.”

  • For the perceived importance of learning strategies (5 references), responses revealed the importance of learning strategies in MOOCs. As stated in one response, “The clear goal and plan in MOOCs learning are very important for me. After all, it is a self-paced learning style, no one will require you do to this, or to do that.” Another response stated, “I have to make preparation for each course if I want to learn better.”
    • For the negative impact of MOOCs (1 reference), the response shows that MOOCs may have a negative impact on communication in the real world. The response stated, “If we spend too much time in MOOCs, we may feel difficult to communicate with people in the real world. Then we will live in a very small place…”
  • Qualitative data analysis:

Interview participants included 2 interviewees who have experience of learning in MOOCs. One interviewee was a MOOCs learner who was working, and the other one was a full-time student of a university. The two participants were both Chinese.

Overall, both participants expressed a positive attitude towards learning in MOOCs and they talked about the issues at a high level of enthusiasm. The interviews were recorded in audio and then transcribed in verbal format. The transcriptions were thematically analyzed based on an open-coding approach. The coding themes were derived from interview prompts, with additional open coding to further breakdown the information. Afterwards, to ensure the interpretations were well reflected what the participants had said, coded data in themes were sent in email to the two interviewees for member-checking if there was any differentiation with their meaning. The participants turned back and confirmed the categorized transcriptions. After receiving the confirmation from participants, all the emerging themes were identified and made to reflect the perspectives of MOOCs learners (see Appendix C for a transcription from the interview).

The codes were finally categorized into six main themes. Appendix D is the thematic categories of themes and representative questions as examples (See Appendix D for details of the coded themes). The themes address the research objective directly. The themes are: 1-good feeling from experience, 2-bad feeling from experience, 3- motivations, 4- expectations, 5-perceptions about learning strategies, and 6-future plans. The thematic categories that interviewees raised about dealt with a range of issues. The following reports the overall findings addressing different areas from interviews.

  • Motivations and satisfaction

Both participants expressed strong motivation in learning through MOOCs. The main motivations mentioned are interest and perceived usefulness. They agreed that the MOOCs learning supported their life or academics by providing useful knowledge learning.

“I am the kind of person with very clear target… it is from my interest that I choose MOOCs learning. And some courses are also helpful for my career knowledge enhancement.”

“I chose a lot of MOOCs…I felt them very useful, and very interesting from the introduction…It is based on my very clear learning goal setting…”

The interviews reveal that interviewees have positive attitudes in their learning experience and they perceived MOOCs are useful learning approach. In general, both participants appear to believe that MOOCs online learning plays a positive role in their life, career and academics improvement.

“…MOOCs are helpful for me. Not only MOOCs provide me an opportunity to learn the topics that I think interesting, but also I can learn something that is useful for my career.”

“…many courses I have finished already, which I think very specific and targeted. When I have finished, I really learnt a lot.”

  • Feelings and expectations on MOOCs:

The positive feelings of MOOCs learning reflect MOOCs’ characteristics as an online learning approach. The main innovative features of MOOCs, such as openness, a wide range of course selections, and flexibility, are the main reasons that attract learners.

For example, one interviewee stated:

I think MOOCs provide a very good opportunity for me to choose the courses that I want to learn.” “I can arrange my own pace not bothered by time and place.”

About flexibility of MOOCs:

“Compared with traditional education, I think MOOCs learning is very convenient. I’m free to choose time and class locations.”

“…It is a good way of learning… But also on the time schedule for learning, I can make more independent arrangements. So for me, in working condition, the flexible of time arrangement is very appropriated and helpful.”

About the variety of courses for selection, they mentioned:

“Course selection range is very wide and I can choose the courses in rich course resources. For example, I can choose any course according to my own interest or on my own learning objectives.”

“The main thing is that I can choose my interested favorite courses. Because there are so many courses provided, a lot of courses for selection.”

Both participants also mentioned the perceptions about bad feelings from MOOCs learning experience. Participants appear to feel uncomfortable and frustrated when they encountered with questions regarding the professional area. Difficulties of getting feedback for professional guidance were mentioned as:

“I think how to communicate with the instructor is difficult… no access to get touch with professionals in the related area to communicate with. I think that without these interactions I have no way to get further help if I have some problems in professional knowledge learning…”

“The biggest difficulties… if I have a question… Sometimes when I encountered with problems from MOOCs learning, I do not know whom I should turn to solve the problem. I was very confused and frustrated at that time.”

Both participants also concern with the online communication tool, such as the discussion forum, where they can share their issues and comments. However, they both said they “rarely use” this communication tool, because it is “not effective”, as they described it as “chaotic”, “overloaded information”.

In terms of expectations, both participants mentioned the two areas that MOOCs need to be improved. Their expectations are related to their difficulties. One aspect from their expectations for improvement is interaction with instructors/professionals, and the other one is further specialized knowledge for expert cultivation.

About the interaction, as stated:

“…communication with professors and feedbacks need to be strengthened… I also wish MOOCs can recommend more books and theories for further self-learning deeply…”

For specialized knowledge learning support, interviewees mentioned:

“…but the professional knowledge learning is still relatively weak, it is hard to cultivate a learner with strong theoretical background on MOOCs… I think there is a need to strengthen the professional teaching and learning…”

“but the professional knowledge learning is still relatively weak, it is hard to cultivate a learner with strong theoretical background on MOOCs…I think there is a need to

strengthen the professional teaching and learning in a systematic way, not just provide entry-level knowledge.”

  • Learning strategies:

Both participants were aware of the importance of self-regulated learning in MOOCs, and they enjoyed independent learning in such an autonomous learning environment. They expressed strong support for the role of self-regulated learning to the success of goal achievements. They both agreed that the self-regulated learning ability is crucial for online learning, and they both make learning strategies to ensure they can complete the courses:

“Basically, I don’t spend too much time on preparation, but I indeed to find something, which is relevant to the content. I think this will help me for the understanding. I do many notes in the learning process. I review and reflect after each online class. More important for me is the practice…”

“During the course period, I arrange time on learning on MOOCs everyday… I prefer to learn using my fragmented time to complete these course contents…”

One interviewee mentioned the important role of practice as an effective learning strategy:

“More important for me is the practice. For example, after the finance management course, I use the models that were introduced in the class, and I tried to do a real investment following the professor’s advice.”

  • MOOCs and future plans:

Both interviewees admitted that MOOCs learning is important, and they stated their strong intention of using MOOCs in the future. Although the two interviewees were in different status, one was working and the other was a college student, they both plan to continue higher education in traditional institutions in the future. They

perceived MOOCs learning to compensate knowledge acquisition when they have spare time and MOOCs cannot take place of university education. As interviewees stated:

“And there are many courses in MOOCs, so that I can choose what I want to learn in my spare time. Then I tried some courses in MOOCs that I am personally interested in. I think MOOCs provide a very good opportunity for me to choose the courses that I want to learn. For instance, I am interested in personal finance, so I found a course about personal finance then I started learning.”

“…it is still relatively limited because the course content is superficial…If I want to be an expert in a specific area, it is impossible to learn enough specialized knowledge from MOOCs… I hope to have the opportunity to go overseas study in famous university for further education, to upgrade myself.”

“My current plan is to continue higher education. I am preparing for further studies in higher education after my graduation in my university. I am planning to pursue a degree in business administration in United States. In the long-term future I want to make run business as an entrepreneur, I think the degree in business administration will be very helpful for me.”

4.3. Findings and Discussions:

As the quantitative and qualitative data indicate, Chinese learners’ attitudes and perceptions are in an array of views concerning the potential of MOOCs for their learning context. Data analysis yielded several categories of learner perspectives: satisfaction, challenges, motivations, expectations, and self-regulated learning. The

following content of this report further interprets these findings. Satisfaction:

Most participants in this research believe that MOOCs are valuable and effective. Their perceived value in usefulness, easiness, relevance, and worth in personal/professional life shows positive attitudes of learning in MOOCs. 86% of questionnaire responses agreed that MOOCs learning is useful for them, and 71% responses believe they improved skills in study/career from MOOCs. Chinese learners’ perceived effectiveness and they believe MOOCs can meet their learning needs.

Learning effectiveness is a fundamental factor (Liaw, 2008) that influences learners’ attitudes in their online learning experiences. The interview data support this finding, as one interviewee mentioned: “MOOCs are helpful for me. Not only MOOCs provide me an opportunity to learn the topics that I think interesting, but also I can learn something that is useful for my career.”

However, participants expressed their less satisfaction of interaction in MOOCs, with questionnaire responses disagree (23.53%) or neutral (42.18%) in “MOOCs promote participation and interaction”. Less than half of the responses (29.41%) think MOOCs create a sense of online community. As one interviewee argued, the means of interaction through MOOCs are very limited in depth and width, thus it is very hard to feel an online learning community as traditional settings in a university. The opinion indicated a need to re-structure the discussion board or other alternatives that will allow effective communication in MOOCs learning context.


Although MOOCs advantages generate considerable attention and interest from Higher Education institutions (e.g. Yao, 2014; Yi, 2014; Yao, 2014), students also perceive issues of challenges ranging from technical problems to learning resources. The survey results show that: 37.26% of the learners expressed their technical issues in MOOCs and 43.14% reported the difficulties to get personalized feedback from instructors. This might be a need to find an appropriate tool to make effective communication between instructors and learners on MOOCs.

The interview data provide additional insights into the Chinese learners’ difficulties in

MOOCs learning. Both interviewees spoke about the technical problems, explaining that the Internet censorship policy in China block many foreign websites, for instance, they cannot open “”, which is the most widely used tool to make video courses available in MOOCs. The Internet censorship policy in China restricts course selections. Therefore, for learners in China, their course selections are Chinese courses, translated English courses by Chinese course providers, and those are not blocked from foreign course providers. When asked about the linguistic issues in MOOCs instruction, the two interviewees asserted that instructions in English as a foreign language was not a problem to stop them choose MOOCs taught in English.

For instance, one interviewee stated: “I think in terms of the language, learning is not a barrier for me, my English is good enough for MOOCs learning”. The other interviewee said: “… learning an English course…I needed to stop taking notes and looked up the meaning of unfamiliar words in the whole process. But I think I can handle this aspect of language difficulties encountered.”


The results from the survey questionnaire show that most participants (80.39%) plan to continue learning in MOOCs within one year. In the survey, most participants reported that they have interest in course contents, and believe MOOCs can support life-long learning in individual competence (74.51%). As one interviewee said about motivation of learning in MOOCs is “a good way of learning”. The survey results also raise a question regarding the learners’ personalities and how it might influence their motivation to choose MOOCs as learning approach. More than half of the participants (59%) reported that they felt ease in MOOCs learning because they are shy.


When asked which areas of MOOCs were in need of improvement, the interviewees identified several expectations. They suggested that the instructors/facilitators should provide feedback to learners when they encounter academic problems. Comments from interviewees also indicated that instructors/facilitators should recommend more content materials that related to the topic for their learning. The following statements illustrate this expectation: “I think there is a need to strengthen the professional teaching and learning in a systematic way, not just provide entry-level knowledge.” “I also wish MOOCs can recommend more books and theories for further self-learning. Some online resources with links can also be very helpful.”

The interviews data indicated student concerns on the qualified certificate from MOOCs. Although students commented on the benefits of MOOCs to lifelong learning, students were aware that a certificate from MOOCs is unofficial and not appropriate for inclusion on a resume. They commented that the certificates from MOOCs are useless when they want to find a good job in the society. Learners viewed MOOCs as a learning tool that could assist them in their life. The interviews show that the certificates from traditional higher education institutions will help them to have a good life in the future. Both interviewees expressed strong motivation to study in traditional higher education.

Learning strategy:

The study shows that participants largely believe in the important role of self- regulated learning in MOOCs learning experience. Responses from the survey questionnaire showed strong support for self-regulated learning as a strategic approach to learn well in MOOCs. 82% of the responses from the questionnaire agreed that self-regulated learning is important for their learning in MOOCs. 64.17% of the responses preferred to make plans for their strategies. Most participants (more than 80%) controlled and monitored their learning behavior in the process. The interview data support this attitude of self-regulated learning. Both interviewees explained how they use self-regulated learning in order to acquire knowledge, as stated: “Generally, I spend 40 minutes up to one hour. At the weekend, it would be longer, might be 2 to 3 hours per day… I do many notes in the learning process. I review and reflect after each online class. More important for me is the practice.” “During the course period, I arrange time on learning on MOOCs everyday…I prefer to learn using my fragmented time to complete these course contents. If I use more chunk of time to concentrate on the MOOCs learning, I think that will be a lot pressure for me and not effective.”

MOOCs and traditional higher education:

The survey results indicate that Chinese learners were highly motivated to learn in MOOCs in the future, with 80.39% participants expressed that they plan to learn in

MOOCs within one year. Furthermore, the interview data provide additional insights into the Chinese learners’ attitudes and perceptions of MOOCs. Both interviewees spoke about the role of MOOCs learning as informal, explaining that MOOCs were used to compensate traditional teaching and learning. They attempted to use MOOCs to compensate the shortcomings of traditional higher education.

Interviews data reveal that Chinese learners appear still prefer traditional higher education. When asked about their learning plans in universities, both interviewees claimed that they had a clear plan to continue higher education in universities, concerning the use of MOOCs disadvantages, and thought that it was difficult to become an expert with specialized knowledge from MOOCs learning. Given that the certificates from MOOCs were not qualified and accepted in the society, certificate attainment seems not an important factor that drives learners’ determination of learning in MOOCs. As Davis et al (2014) suggest, it is still very early to claim MOOCs as formalized education. MOOCs and other Silicon Valley initiatives have some common aspects in business model. Like Google and eBay, the profit-driven business model of MOOCs provides free services to learners through early investments, and course providers want to make money for sustainable development ultimately. MOOCs’ sustainability and the impact on higher education seem still unclear to see from the current stage.

Chapter Five: Conclusion


In this study, I have examined Chinese learners’ attitudes and perceptions about participating in MOOCs and recognized several aspects as difficulties or opportunities that seem to affect their attitudes. As previously discussed, much of the literature sees MOOCs provide a powerful tool to make fundamental changes in higher education (Yuan & Powell, 2013). The findings contribute to understand MOOCs’ potential as an innovative educational technology in online education. Learners’ point of views can contribute to discussions on the role of MOOCs for China higher education.

The results reveal that Chinese MOOCs learners largely expressed positive perception towards MOOCs. The positive perceptions are as following: 1) MOOCs are useful tool to enrich professional knowledge and satisfy personal interest; 2) MOOCs have advantages to provide opportunities for higher education; 3) MOOCs are useful in promoting self-regulated learning; 4) Learners have strong motivation to continue their learning in MOOCs in the future. Equally, as clear are concerns identifying limitations from Chinese MOOCs learners, they perceived difficulties and expected to improve in those areas: 1) instructors/facilitators provide little feedback and they should provide more support when students have academic problems; 2) discussion board has overloaded information and need to be restructured; 3) the Internet policy in China restrict learners’ course selection and they expect to change; 4) certificates from MOOCs are not appropriate for inclusion in a resume. These views suggest that perhaps researchers and MOOCs course providers should pay more attention to how learners should be served better, rather than focus on MOOCs learning features. The findings also allow Chinese higher education institutions, administers and researchers think about how to utilize MOOCs’ capability to support higher education effectively and appropriately.


As with any research effort, this study does have several limitations that should be considered. First, due to its small number of participants in this research, the set of participants is not possible to generalize the results to form a broader picture of the MOOCs use of online learning. Therefore, the findings should be considered as appropriate for understanding the initial classification of opinions about MOOCs among Chinese learners. Second, this study focuses on attitudes and perceptions about MOOCs, without a specific course context. In a single case within one course learning experience, it is possible that learners might have more sophisticated feelings. An additional limitation is that the cross-sectional data. Such data analysis was limited to interpret the individual differences in different groups, for instance, different learner personalities, age and generations, and careers.

The implications for further studies:

The categories identified from this research might enable researchers to extend the understanding of issues in further studies about the implementation of MOOCs in higher education. Due to the limited number of research studies in China concerning MOOCs development, as well as a transformation of higher education by digital technologies, future efforts should seek to address the concerns indicated in this research, in order to have a comprehensive body of research as references for the implementation of higher education transformation.

Furthermore, as Drew and Watkins (1998) suggest, student personality and characteristics could potentially affect students’ participation in teaching and learning activities. The findings from the survey also show that more than a-half participants chose MOOCs learning because they are shy. The MOOCs learners’ personalities might also have roots in a cultural and historical context. This area needs further exploration. Additionally, future studies can place efforts in understanding what are the political effects on MOOCs and how politics impact these educational technologies. As Thomas (2016) states, “politics and education live in a symbiotic relationship, with each influencing the fate of the other.”(p.1). In order to create a plan to implement MOOCs in higher education in China, it is important to examine whether political forces affect the utilization of digital technologies in higher education.


Panadero, E., & Alonso-tapia, J. (2014). How do students self- regulate!? Review of Zimmerman ‟ s cyclical model of self-regulated learning, 30, 450–462.

Paper, C. (2016). MOOCs for teacher professional development!: investigating views and perceptions of the MOOCS FOR TEACHER PROFESSIONAL DEVELOPMENT!:, (August).

Pardos, Z. A., & Schneider, E. (2013). AIED 2013 Workshops Proceedings Volume 1 Workshop on Massive Open Online Courses ( moocshop ), 1.

Paris Scott, & Byrnes James. (1989). The Constructivist Approach to Self-Regulation and Learning in the Classroom. In Self-Regulated Learning and Academic Achievement (pp. 169–200). London: Springer.

Park, A. J., Choi, H. J., Park, J., & Choi, H. J. (2016). International Forum of Educational Technology & Society Factors Influencing Adult Learners ’ Decision to Drop Out or Persist in Online Learning Published by!: International Forum of Educational Technology & Society Linked references are available on JSTOR, 12(4), 207–217.

Pintrich, P. R. (2004). A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students, 16(4), 385–407.

Pressly, M., & Ghatala, E. S. (1990). Self-regulated learning Monitoring learning from text.

Prof, A., & Isman, A. (2004). Attitudes of Students Towards Internet, (October), 4–9.

Punch, K. F. (2005). Introduction to Social Research: Quantitative and Qualitative Approaches.

Introduction to social research quantitative and qualitative approaches (Vol. Second).

Puzziferro, M. (2016). Online Technologies Self-Efficacy and Self- Regulated Learning as Predictors of Final Grade and Satisfaction in College-Level Online Courses, 3647(June).

Reja, U., Manfreda, K. L., Hlebec, V., & Vehovar, V. (2003). Open-ended vs. Close-ended Questions in Web Questionnaires. Developments in Applied Statistics, 19, 159–177.

Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Network, 7(1).

Risemberg, R., & Zimmerman, B. J. (1992). Self‐regulated learning in gifted students. Roeper Review, 15(2), 98–101.

Ritchie, J., & Lewis, J. (2014). Qualitative Research Practice: A Guide for Social Science Students and Researchers.

Rivard, R. (2013). Measuring the MOOC dropout rate. Inside Higher Ed, (March).

Robey, D., Khoo, H. M., & Powers, C. (2000). Situated learning in cross-functional virtual teams.

Rogoff Barbara. (1990). Apprenticeship in thinking: Cognitive development in social context. New York: Oxford University Press.

Rosa Maria, Sarrico Cláudia, Tavares Orlanda, & Amaral Alberto. (2016). Cross-Border Higher Education and Quality Assurance: Commerce, the Services Directive and Governing Higher Education. London: Springer.

Rose, G. (2016). Situating knowledges!: positionality , re ¯ exivities and other tactics, 3(1997), 305– 320.

Saadatmand, M., & Kumpulainen, K. (2013). Content aggregation and knowledge sharing in a personal learning environment:

Sale, J. E. M., Lohfeld, L. H., & Brazil, K. (2002). Revisiting the quantitative-qualitative debate: Implications for mixed-methods research. Quality and Quantity, 36(1), 43–53.

Selim, H. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models.

Selm, M. V. A. N., & Jankowski, N. W. (2006). Conducting Online Surveys, 435–456.

Shank, G. (1995). Semiotics and qualitative research in education: The third crossroad. The Qualitative Report, 2(3), 1–9.

Sharples, M., Kloos, C. D., Dimitriadis, Y., Garlatti, S., & Specht, M. (2015). Mobile and Accessible Learning for MOOCs. Journal of Interactive Media in Education, 2015(1), Art. 4.

Shih, C.-C., & Gamon, J. (2001). Web-Based Learning: Relationships Among Student Motivation, Attitude, Learning Styles, And Achievement. Journal of Agricultural Education, 42(4), 12–20.

Siegel, H. (2012). Epistemological Diversity and Education Research!: Much Ado About Nothing Much?, 65–84

Siemens, G. (2005). Connectivism!:(2000), 1–15.

Siemens, G. (2012). Massive Open Online Courses!: Innovation in Education!? What Are MOOCs!?

Siemsen, S., & Jansen, R. (2014). Connectivism and Interactionism Reloaded Knowledge Networks in the Cloud: A Theoretical Approach to a Shift in Learning through Connectivism and MOOCs. In Communications in Computer and Information Science (Vol. 446 CCIS, pp. 1–12).

Sills, S. J., & Song, C. (2002). Innovations in Survey Research: An Application of Web-Based Surveys. Social Science Computer Review, 20(1), 22–30.


Snape, D., & Spencer, L. (2003). The Foundations of Qualitative Research. Qualitative Research Practice: A Guide for Social Science Students and Researchers, 2–10.

Stansfield, M., Mclellan, E., & Connolly, T. (2004). Enhancing Student Performance in Online Learning and Traditional Face-to-Face Class Delivery. Journal of Information Technology

Su Yang. (2015, June 8). 86-year-old man attends in his 15th Gaokao. China Daily.

Sun, P., Tsai, R. J., Finger, G., & Chen, Y. (2008). What drives a successful e-Learning!? An empirical investigation of the critical factors influencing learner satisfaction, 50, 1183–1202.

Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), 251–296.

Tan, C. T. (2013). Towards a MOOC game. Proceedings of The 9th Australasian Conference on Interactive Entertainment Matters of Life and Death – IE ’13, 1–4.

Tang Xiaojun. (2016, June 24). The strongest candidate of Gaokao. Chengdu Economic Daily.

Thomas R. (1983). Politics and Education: Cases from Eleven Nations. Oxford: Pergamon Express. Thompson, K. (2011). THINGS YOU SHOULD KNOW ABOUT … TM MOOC s. EDUCAUSE

Learning Initiative, 1–2. Retrieved from

Thompson, L., Ku, H. Y., Thompson, L., & Ku, H. (2016). Chinese graduate students ’ experiences and attitudes toward online learning Chinese graduate students ’ experiences and, 3987(July).

Van Selm, M., & Jankowski, N. W. (2006). Conducting online surveys. Quality and Quantity.

Vygotsky, L. S. (1962). The Genetic Roots of Thought and Speech. In Thought and language (pp. 33– 51). US: MIT Press.

Waard, I. De, Abajian, S. C., Hogue, R., & Gallagher, M. S. (2011). Exploring the MOOC format as a pedagogical approach for mLearning. mLearn 2011, 138–148.

Wang Chunchun, & Zhang Nanxing. (2013, December 16). The seven trends of China higher education. China Education Daily.

Wang Ping. (2013). The Latest Development and Application of Massive Open Online Course: From cMOOC to xMOOC. Distance Education Studies, 3, 13–19.

Wang Wenli. (2013). MOOCs impact on higher education. Education Studies, 02, 53–57.

Wang, Y., & Baker, R. (2015). Content or platform!: Why do students complete MOOCs!? Journal of Online Learning and Teaching, 11(1), 17–30.

Wang, Y., & Ross, H. (2010). Experiencing the Change and Continuity of the College Entrance Examination: A Case Study of “Gaokao” County, 1996-2010. Chinese Education and Society, 43(4), 75–93.

Wang, Z., Anderson, T., Chen, L., & Barbera, E. (2016). Interaction pattern analysis in cMOOCs based on the connectivist interaction and engagement framework, 00(00).

Watt, D. (2007). On Becoming a Qualitative Researcher!: The Value of Reflexivity. The Qualitative Report, 12(1), 82–101.

Wei Erxiao. (2016, February). The influence of Internet Plus on libraries. Daguan, 229.

Weinert, F. E., Schrader, F. W., & Helmke, A. (1989). Quality of instruction and achievement outcomes. International Journal of Educational Research, 13(8), 895–914.

Welsh, D. H. B., & Dragusin, M. (2013). The New Generation of Massive Open Online Course (MOOCS) and Entrepreneurship Education. Small Business Institute Journal, 9(1), 51–65.

Wen, M., Yang, D., & Rosé, C. P. (2014). Sentiment Analysis in MOOC Discussion Forums!: What does it tell us!?, (Edm), 130–137.

Whelan, T. J., & Carolina, N. (2007). Anonymity and Confidentiality!: Do Survey Respondents Know the Difference!? Society of Southeastern Social Psychologists, (2006), 1–11.

Whitworth, A. (2012). Computers & Education Invisible success!: Problems with the grand technological innovation in higher education. Computers & Education, 59(1), 145–155.

Wiles, R., & Crow, G. (2013). What is Qualitative Interviewing!? “ What is!?” Research Methods series Edited by Graham Crow , University of Edinburgh.

Williams, P., Nicholas, D., & Gunter, B. (2005). E-learning: what the literature tells us about distance education: An overview. Aslib Proceedings, 57(2), 109–122.

Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In Metacognition in educational theory and practice (pp. 277–304).


Wong, T. (2015). China’s gaokao: High stakes for national exam – BBC News. BBC News.

Wu, B. (2008). Briefing Series – Issue 36 EXPANSION OF HIGHER EDUCATION IN CHINA!:,

Xiong, Y., So, H., & Toh, Y. (2015). Assessing learners ’ perceived readiness for computer- supported collaborative learning ( CSCL ): a study on initial development and validation. Journal of Computing in Higher Education, 27(3), 215–239.

Yang, L. (2015). Dilemma and Development Strategy of MOOC Localization. 2015 7th International Conference on Information Technology in Medicine and Education (ITME).

Yang Peifang. (2015, December). The Internet Plus: power of development. Shishi Baogao, 58–67. Yang, S., Guo, L., Shao, F., Zhao, Y., & Chen, F. (2015). Research Article A Systematic Evaluation of

Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing

Yang Zhentao, Li Yushun, Qing Zhujun, & Sang Yuxia. (2014). Chinese learners acceptance on MOOCs. The Chinese Journal of ICT in Education, 11, 16–17.

Yanmei, L. I. U. (2015). Chinese Higher Education Reform Under the Wave of MOOC, 9(3), 23–27.

YAO, Z. H. E. (2014). MOOC: Challenges and Opportunities of Higher Education. Applied Mechanics & Materials, (651-653), 2469.

Yu, L., & Suen, H. K. (2005). H i s t o r i c a l a n d C o n t e m p o r a r y E x a m – d r i v e n E d u c a t i o n F e v e r i n C h i n a, 2(1), 17–33.

Yu Lan, & Suen Hoik. (2005). Historical and Contemporary Exam-driven Education Fever in China.

Yuan, B. L., Powell, S., Yuan, L., Powell, S., & Cetis, J. (2013). MOOCs and Open Education!: Implications for Higher Education A w hite p aper.

Yuan, L., & Powell, S. (2013). MOOCs and Open Education: Implications for Higher Education. Cetis,

Yuan Songhe, & Liu Xuan. (2014). Status and Common Problems of MOOC Practice in China’s Universities. Distance Education Studies, 130, 3–22.

Zhang, Y. (2013). Benefiting from MOOC. World Conference on Educational Multimedia, Hypermedia and Telecommunications, 2013(1), 1372–1377. Retrieved from

Zhao Chenting. (2015). Guoker, received 20 million dollars venture capital.

Zhao Haitao, Wang Shan, & Ma Dong Tang. (2014). Impacts of MOOC on Higher Education and the Suggested Response. Advances in Education, 4, 104–111. Retrieved from

Zhao Yong. (2012). Reforming Chinese Education: What China Is Trying to Learn from America. Solutions, 2(2), 38–43.

Zheng, C., Liang, J., Yang, Y., & Tsai, C. (2016). The relationship between Chinese university students ’ conceptions of language learning and their online. System, 57, 66–78.

Zheng, L. (2016a). The effectiveness of self-regulated learning scaffolds on academic performance in computer-based learning environments!: a meta- analysis. Asia Pacific Education Review, 17(2), 187–202.

Zheng L. (2016b). Challenge and Chance from MOOCs. Computer Education, 1(19), 19–20.

Zheng, S., Rosson, M. B., Shih, P. C., & Carroll, J. M. (2015). Understanding Student Motivation , Behaviors , and Perceptions in MOOCs, 1882–1895.

Zhou, M. (2016). Computers & Education Chinese university students ’ acceptance of MOOCs!: A self- determination perspective. Computers & Education, 92-93, 194–203.

Zimmerman, B. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist.

Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemp Educ Psychol, 25(1), 82–91.

Zimmerman, B. J., & Kitsantas, A. (1999). Acquiring writing revision skill: Shifting from process to outcome self-regulatory goals. Journal of Educational Psychology, 91(2), 241–250.

Zimmerman, B. J., & Martinez-pons, M. (1988). Construct Validation of a Strategy Model of Student Self-Regulated Learning, 80(3), 284–290.

Zimmerman, B. J. (2016). Becoming a Self-Regulated Learner!: An Overview Becoming a Self- Regulated Learner!: An Overview, 5841(July).

Zimmerman Barry, & Schunk Dale. (1989). Self-Regulated Learning and Academic Achievement: Theoretical Perspectives. London: Springer.

Zimmerman, B.J.; Bonner, S.; Kovach, R. (2008). Developing self-regulated learners: Beyond achievement to self-efficacy. In Teoria Social Cognitiva: conceitos básicos (pp. 149–164).

Zvacek, S., Teresa, M., Uhomoibhi, J., & Helfert, M. (2014). Computer Supported Education.