Connectivism Learning Theory: Instructional Tools for College Courses. Suzanne Darrow. A Thesis Submitted in Partial Fulfillment for a

Transcription

1 Connectivism Learning Theory: Instructional Tools for College Courses by Suzanne Darrow A Thesis Submitted in Partial Fulfillment for a Master s Degree in Education ED 591 Independent Thesis Research Western Connecticut State University Danbury, CT Spring 2009 COPYRIGHT 2009 SUZANNE DARROW CONTACT: SUZANNEDARROW@GMAIL.COM THIS WORK IS LICENSED UNDER A CREATIVE COMMONS LICENSE

2 ii Abstract This qualitative thesis explores the work of George Siemens and connectivist learning theory, A Learning Theory for the Digital Age. Findings are based on a literature review which investigated the foundations, strengths and weaknesses of connectivism and synthesized conclusions into a knowledge base of practical applications for the college level, Instructional Technology classroom. The half-life of knowledge is shrinking, especially in the field of Instructional Technology; connectivism helps to ensure students remain current by facilitating the building of active connections, utilizing intelligent social networking and encouraging studentgenerated curricula. Connectivism allows the future of education to be viewed in an optimistic, almost utopian perspective, as individuals co-create knowledge in a global, networked environment.

3 iii Table of Contents Abstract..ii I. Introduction...1 Background/Overview...1 Statement of the Problem 8 Research Questions.8 Definition of Terms.8 Limitations of the Study.9 Need or Significance...9 Researcher s Perspective...10 II. Review of Literature..11 III. Methodology.29 Research Design and Rationale.34 IV. Findings.38 V. Discussion..50 References...63

4 Connectivism Theory 1 I. Introduction There is continuous and significant online discussion, theoretical research and interest in the literature regarding the theory of connectivism and the development of connectivist instructional tools for college classes. This thesis will focus on the development of the connectivist learning theory and the compilation of connectivist instructional tools to help practitioners inform their college teaching in the area of Instructional Technology coursework. Connectivism learning theory, properly applied, has the potential to significantly improve education through the revision of educational perspectives and generate a greater shift toward learner-centered education (Siemens, 2004). The theory allows for instructors to step back from controlling course content, bypass textbooks and traditional lecture presentations and bring learners to the forefront in locating, presenting and making sense of relevant knowledge. When knowledge is no longer expert-centered and content and conversations are continuous, growth and learning can occur for all classroom participants, including the instructor. Background/Overview George Siemens, Associate Director of Research and Development with the Learning Technologies Center at the University of Manitoba, and founder and president of Complexive Systems Inc., proposed connectivism learning theory in December, His interest in technology s potential to transform teaching, learning and society drove his research into the area of e-learning. Based on his research and experience, Siemens explained existing learning theories did not provide for the changing nature of learning and learners due to the influence of technological advances, Connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories (2005). He described learning as messy, chaotic,

5 Connectivism Theory 2 social, collaborative, and connected with other activities and interests. Formal education, in contrast [is] artificial and structured (2006). In his groundbreaking paper, Connectivism: A Learning Theory for the Digital Age, Siemens (2004) outlined the following principles of connectivism: Learning and knowledge rests in diversity of opinions. Learning is a process of connecting specialized nodes or information sources. Learning may reside in non-human appliances. The capacity to know more is more critical than what is currently known. Nurturing and maintaining connections is needed to facilitate continual learning. The ability to see connections between fields, ideas, and concepts is a core skill. Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities. Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision. While Siemens held to the validity of three major learning theories, behaviorism, cognitivism, and constructivism, he argued these theories have inherent limitations. The theories do not reflect the type of learning that occurs in today s digital age nor do they meet the needs of today s students (2004). He agrees established theories and techniques should not be summarily dismissed as their value is still appropriate for certain learning tasks that require a more formal and structured environment. Siemens acknowledges, No one concept or theory is universal in its application (2006).

6 Connectivism Theory 3 Another supporter for revitalizing education through the effective use of technology and connectivism practices is Marc Prensky. Prensky is a speaker, author and consultant in the area of education and learning, and has focused on digital game-based learning as one solution to the issue of waning student engagement. In his article, Engage Me or Enrage Me, Prensky (2005) explained that today s learners are no longer interested in or even capable of learning in environments that do not reflect their real-world experiences. Students today come to class equipped with a myriad of wired devices such as cell phones, laptops and ipods. They are constantly in touch, motivated by and responding to their changing world with the spontaneous exchange of knowledge. Instructors that teach with an old-fashioned, chalk and talk approach will have difficulty in significantly reaching these students. Prensky further explained that students lives are rich in media, communication and creative opportunities outside of school: Rather than being empowered to choose what they want and to see what interests them and to create their own personalized identity as they are in the rest of their lives in school, they must eat what they are served. And what they are being served is, for the most part, stale, bland, and almost entirely stuff from the past. Yesterday s education for tomorrow s kids [sic]. While to some, it may appear that today s learners have short attention spans, Prensky points out that students only have, short attention spans for the old ways of learning. They don t have short attention spans for their games, movies, music or Internet surfing (2005). Prensky coined the term Digital Natives which refers to today s students as native speakers of the digital world while others not born into this digital world can be considered Digital Immigrants. Prensky (2001) explains:

7 Connectivism Theory 4 As Digital Immigrants learn to adapt to their environment, they always retain their "accent," that is, their foot in the past the single biggest problem facing education today is that our Digital Immigrant instructors, who speak an outdated language are struggling to teach a population that speaks an entirely new language. Digital Natives are used to receiving information really fast. They like to parallel process and multi-task. They prefer their graphics before their text rather than the opposite. They prefer random access.they function best when networked. They thrive on instant gratification and frequent rewards. They prefer games to serious work. Within connectivism theory, learning is considered to be a process in which, the role of informal information exchange, organized into networks and supported with electronic tools, becomes more and more significant. Learning becomes a continuous, lifelong system of network activities, embedded into other activities (Bessenyei, 2007). Bessenyei further stated: The motivation for gaining and contextualizing information becomes stronger if searching and evaluation become a cooperative, network activity. Thus the collective knowledge once again becomes a source of individual knowledge. As the number of cooperative activities increases, personal social networks become the scene of informal exchange of expertise, and communities of practice develop. Besides the questions of how and what to learn, we now have the question of where to learn. Instead of institutions and publishers holding the keys to knowledge, learners can become active participants in the creation of knowledge. At the heart of the matter is that of networks, where, as stated in the John Guare play, Six Degrees of Separation, every person is a new door opening up into other worlds ( Essentially, each person provides others with varying learning experiences and the community as a whole becomes the

8 Connectivism Theory 5 curriculum and the classroom. Six degrees of separation is intriguing because it suggests that, despite our society s enormous size, it can easily be navigated by following social links from one person to another-a network of six billion nodes (Barabasi, 2002). Another facet of established learning theories that clashes with modern-day education is the premise that established theories do not take into consideration the information explosion and the half-life of knowledge (Gonzalez, 2004) that exists in today s digital environment. Essentially what one learns today may be completely irrelevant and useless tomorrow. There are very few things that change more rapidly than technology. Gonzalez explains: One of the most persuasive factors is the shrinking half-life of knowledge. The half-life of knowledge is the time span from when knowledge is gained to when it becomes obsolete. Half of what is known today was not known 10 years ago. The amount of knowledge in the world has doubled in the past 10 years and is doubling every 18 months according to the American Society of Training and Documentation (ASTD). To combat the shrinking half-life of knowledge, organizations have been forced to develop new methods of deploying instruction. Connectivism learning theory places emphasis on the importance of instructing students to search for, filter, analyze and synthesize information in order to obtain knowledge. Siemens stated, When knowledge is needed, but not known, the ability to plug into sources to meet the requirements becomes a vital skill. As knowledge continues to grow and evolve, access to what is needed is more important than what the learner currently possesses (Siemens, 2004). Siemens compared the flow of information in a knowledge economy' to the equivalent of the oil pipe in an industrial economy. Creating, preserving, and utilizing information flow should

9 Connectivism Theory 6 be a key organizational activity. The pipe is more important than the content within the pipe. Our ability to learn what we need for tomorrow is more important than what we know today (2004). When looking at the history of e-learning it becomes clear that there was a need to develop a new learning theory that would encompass the type of learning that takes place online. In the late 1990 s the Internet was evolving and content was shifting from the controlled distribution of information to include end-user generated materials. As the barriers to developing network content continued to fall, end-users found they were able to create, collaborate and share with relative ease (Siemens, 2007). As a result, this information revolution had significant impact on traditional education as educators, no longer tied to textbooks, were able to offer students collaborative, online learning opportunities. The emergence of personal Websites and Web 2.0 tools such as blogs, wikis, mashups and podcasts, provided a global medium for discussion and the presentation of varying points of view. The edublog movement gained significant ground in the early 2000 s and created a community for educators interested in utilizing evolving technologies. Edublogs provided a forum for reflections on pedagogical methodology, practical applications and best practices. In general, online community members started to learn from each other rather than depend on official, published works. This distributed learning resulted in the co-formation of understanding and learning became a network creation process (Siemens, 2007). Web 2.0 tools that support online interactivity are unlimited, with new tools emerging on a daily basis. The open source movement and rapid enhancements in social networking allow for the free sharing of information and form the basis of e-learning 2.0, with its traits of network, self organization and embedment in activity. Bessenyei (2007) states:

10 Connectivism Theory 7 It has become possible to construct personally reflected knowledge adapted to one s individual needs from information represented in cyberspace.[students] will only be able to keep up with the challenge of global knowledge exchange and be able to use interactive networks if they become familiar with these tools and opportunities at an early stage. The most important competencies should be searching for and evaluating information and making connections between different fields of knowledge, ideas and concepts. Educators have been applying connectivist teaching and learning strategies long before the emergence of the formal theory of connectivism. This thesis will examine the early theoretical roots and practical applications that led to the theory s development and will consider emerging applications that build upon the theory s foundation. Connectivist learning theory can and should have a major impact on traditional educational institutions. The utopia of network learning as first proposed by Ivan Illich in 1970 may soon become a reality. The connectivist teaching and learning model can eventually lead to a greater unification of the global community of life-long learners. Perhaps John Seely Brown (2000) draws the best conclusion: The Web helps build a rich fabric that combines the small efforts of the many with the large efforts of the few. By enriching the diversity of available information and expertise, it enables the culture and sensibilities of a region to evolve. Indeed its message is that learning can and should be happening everywhere-a learning ecology. All together, a new, self-catalytic system starts to emerge, reinforcing and extending the core competencies of a region. [there is] an interesting shift that I believe is happening: a shift between using technology to support the individual to using technology to support relationships between individuals. With that shift, we will discover new tools and social protocols for helping us help each other, which is the very essence of social learning.

11 Connectivism Theory 8 Statement of the Problem By reviewing the history of connectivism from 2000 to 2008, this paper will provide examples of how connectivism learning theory has been translated into college teaching. These examples can help practitioners inform their teaching practice by incorporating connectivist instructional tools and methods into Instructional Technology college courses. Research Questions 1. What is connectivism? 2. Who developed connectivism? 3. How can connectivism be applied by practitioners in Instructional Technology college classes? 4. Which connectivist learning tools would be effective in Instructional Technology college classes? 5. What are the instructional weaknesses and strengths of connectivism? Definition of Terms The following is a list of definitions for terms and concepts about or related to connectivism that has significant meaning for my qualitative study: Instructional Technology Coursework. For the purpose of this thesis, this term refers to undergraduate, college level courses geared towards teacher education students. Networked Learning. In this thesis, this term is used to describe connected, online, digital learning that occurs between learners, instructors, learning communities and learning resources. Interactions can be synchronous, asynchronous or both and can occur through a variety of digital media including digital text, audio, graphics, video, etc. Web 1.0/e-learning 1.0. This term refers to the state of the Internet and e-learning in a time

12 Connectivism Theory 9 before user interaction with online content became the norm. Characteristics of Web 1.0/elearning 1.0 include static Web pages, content that is not interactive and the use of proprietary software. Web 2.0/e-learning 2.0. This term refers to second generation Web developments that have been designed to facilitate online communication and collaboration; examples include social networking, video sharing sites and the use of wikis, blogs, and podcasting. Web 3.0/e-learning 3.0. This term can also be referred to as the semantic Web. Web 3.0 technologies build upon Web 2.0 technologies and refer to a vision of digital data that is understandable by computers, so that the technology can assist in finding, sharing, and combining online information. Limitations of the Study This paper will focus on the theory of connectivism and the practical application of connectivism instructional tools and techniques as they apply to the undergraduate, college-level, Instructional Technology classroom. It will not cover applications designed for the pre-k-12 learning environment, college graduate level or courses outside of the Instructional Technology area. This study will not attempt to evaluate the suggested practical applications of connectivism; it will merely present them in relation to their affiliation with connectivism learning theory. Need or Significance Connectivism provides an ideological framework that can impact how practitioners design and develop instructional tools for college courses. This framework places emphasis on building the learner s ability to navigate and connect current information beyond knowledge of the existing linear curriculum. The selection of a qualitative methodology contributes to college

13 Connectivism Theory 10 teaching because it will help to develop a knowledge base of practical applications of connectivist instructional tools. Researcher's Perspective As an educator who works with college students, the researcher will document biases and assumptions as related to the potential findings of research.

14 Connectivism Theory 11 II. Review of Literature The review of literature for this thesis involved a thorough synthesis and analysis of available literature, in English, related to the study. The review was developed in two phases following the procedures in the Qualitative Research Framework for ED 591 and The Publication Manual of the American Psychological Association, Fifth Edition. The literature selected for review focused on the research questions previously outlined in the Introduction. The first section of this literature review will focus on the problem exploration-definition stage of research to substantiate the choice of topic and methodology, and will provide a sound theoretical and conceptual basis for this study. The review will highlight the rise and development of connectivist learning theory, which bases its foundation on the following theories: network, chaos, complexity and self-organization. This review will depict how the established theories of behaviorism, cognitivism and constructivism are inadequate to fit today s college learning environments, thus reflecting the need for the development of new learning theories. The social learning theories of rhizomatic knowledge and learning ecologies will be explored within the review, along with a history of the social Web, the development of Web 2.0, e- learning 2.0, and the open educational resource movement. The second part of the literature review will be a synthesis with the following questions in mind: What is missing from the literature? What was learned from putting the literature review together? What are the theories which are supported by the literature? What questions does the literature review suggest/generate? Connectivism learning theory is often referred to as networked learning but connectivism is about more than just the technology used to achieve the end result. Connectivism can be seen as

15 Connectivism Theory 12 a networked construct encompassing neural, conceptive and external processes. While neural and conceptive processes take place within the individual, technology is the only external construct that lends itself to the learning process. The modern day shift in the cognitive process itself is what is significant and different, and this shift requires new theoretical perspectives. The principles of networking and networked learning have been in place long before modern day digital technology emerged. For example, farmers in agrarian societies have been sharing knowledge amongst themselves for thousands of years. Younger generations of farmers would build upon the work of others and continue to make small advances in tools and techniques. New technologies have allowed us to extend beyond our own humanity in order to formulate the continuous, global networks we employ today. One of the first references to the networked learning model of education can be found in Ivan Illich s description of educational and learning webs. He suggested that with webs, we can provide the learner with new links to the world instead of continuing to funnel all educational programs through the teacher (1970). His views were several decades ahead of digital technology developments. George Siemens found through research and literature review, five stages that led to the modern day conception of digital networked learning. To begin, there was the development of infrastructure-the actual, physical and technical structures required to store and distribute content including software, hardware and connectivity. In the area of education, this was realized through the initial investment in the wiring of classrooms and the purchase of stand-alone computer work stations. Siemens (2008) explains: As such, early definitions of learning networks were focused on infrastructure: Learning networks are composed of hardware, software, and telecommunication lines (Harasim et.

16 Connectivism Theory 13 al., p. 16) and as groups of people who use CMC [computer-mediated communication] networks to learn together, at a time, place, and pace that best suits them and is appropriate to the task (p. 4). The second development towards digital networked learning occurred when the physical, technological structures merged with existing and established research bases such as those in the mathematics, sociology, and physics fields. This merger provided connectivity between schools, universities, and students with computer mediated communication (viewed) as a transformative agent (Siemens, 2008). Third, individuals accessed and interacted with established, digital research bases resulting in theoretical and transformative views of learning, knowledge, and cognition. Cognition occurred in a more collaborative fashion and at a global level due to rapid computer technology growth and surging interest in social networking. Technology aids in the distribution of cognition as it enables us to project ourselves outward digitally (de Kerchove, 1997, p. 38), or, more boldly, to treat the Web as the extension of the contents of one s own mind (p. 79) (Siemens, 2008). Barabasi explained: Network thinking is poised to invade all domains of human activity and most fields of human inquiry. It is more than another helpful perspective or tool. Networks are by their very nature the fabric of most complex systems, and nodes and links deeply infuse all strategies aimed at approaching our interlocked universe (2002). To take this development to the next level, Haythornthwait and Wellman (2001) use the term, networked individualism, where people use personal, digital networks, to obtain information, collaboration, orders, support, sociability, and a sense of belonging.

17 Connectivism Theory 14 The fourth development in digital technology that led to the rise in networked learning was the emerging popularity of personal and social networking sites. In 2003, MySpace and Facebook brought social networking into the mainstream. While social networking was in place for the academic community prior to the launch of these sites, academic social networking had limited wider appeal. Personal and social networking participants quickly learned how to navigate these new systems. They discovered ways to locate people and information and how to solve problems using newly developed network thinking skills (Siemens, 2008). Statistics reported on the Facebook site, ( state there are currently 175 million active Facebook users. Clearly, this points to an established trend in digital networking. The fifth and final development in networked learning occurred when educators started to explore various networked learning models and looked to them to enhance the education processes. Collaborative online learning combined with mobility-learning anytime, anywhere, with anyone-resulted in the digital network systems currently in use. Current definitions of network no longer only refer to the wires and boxes that create physical online connections. Siemens (2008) explains: By 2005, the definition of learning networks (in this instance, asynchronous) advocated by experts reflected a greater emphasis on people: ALN's [asynchronous learning networks] are people networks for anytime anywhere learning (Hiltz & Goldman, 2005, p. 5). Connectivism, as a theory of learning, is developed against the backdrop of physical network infrastructure, development of the social learning theory, and distributed conceptions of cognition and knowing learning networks have always accompanied the development of

18 Connectivism Theory 15 human knowledge. Connectivism reflects these developments in suggesting the need to craft new views of learning more reflective of the daily reality of learners. With connectivism learning theory, the flow of information is compared to a pipeline, where the pipe itself is more important than the content within the pipe. Learning becomes a sequence of inputs and the network itself evolves and learns as it, builds better pipes, relations and connections to high-priority resources (Siemens, 2008). Siemens felt the need to develop connectivist learning theory as the established theories of the day did not adequately match modern day, digital learning environments. While earlier learning theories of behaviorism, cognitivism and constructivism have general aspects that can apply to many learning situations, each holds that knowledge is an objective that can only be attained through reasoning or direct experience. These theories fail to address learning that occurs outside of the individual, in particular, that which can be stored and manipulated by technology. Additionally, the theories do not explain how learning can happen in networks and organizations, they tend to focus on learning processes and not the value of what is being learned. Behaviorism states that learning is unknowable; there is no way to understand what is going on inside of a person when learning is occurring, learning is only a change in behavior. The theory explains that understanding observed behavior is more important than understanding the actual, internal processes that occur and that human behavior is controlled by a simple stimulus and response process. With cognitivism theory, our minds are viewed as similar to computers; we accept input and data, manage it in short-term memory, archive in long-term memory, retrieve into short-term

19 Connectivism Theory 16 memory as needed and generate output. It is also held that the human mind, or black box should be opened and understood. Constructivism theory states that learners create knowledge in their attempt to understand experiences. Unlike cognitivism and behaviorism which view learners as empty vessels waiting to be filled with knowledge, constructivism states that learners actively construct meaning as they select and pursue learning. In today s digital age, information is continually being developed, distributed and acquired. Connectivism theory takes this fact into consideration. For learners, The ability to draw distinctions between important and unimportant information is vital. The ability to recognize when new information alters the landscape based on decisions made yesterday is also critical (Siemens, 2008). Individuals are constantly making connections to ever changing and evolving networks. Siemens (2004) explains: in a networked world, the very manner of information that we acquire is worth exploring. The need to evaluate the worthiness of learning something is a meta-skill that is applied before learning itself begins we need to act by drawing information outside of our primary knowledge. The ability to synthesize and recognize connections and patterns is a valuable skill. Rapid advances in technology have required the development of entirely new approaches to thinking and learning about the knowledge building process. Connectivism theory also states, We derive our competence from forming connections (Siemens, 2004). Since we cannot possibly experience everything ourselves as the cognitive load would be too great, other people, (the network), become our source of knowledge.

20 Connectivism Theory 17 Connectivism is also the integration of principles based on the following theories: chaos, complexity and self-organization. ScienceWeek (2004) quotes Nigel Calder's definition that chaos is a cryptic form of order. Chaos is the breakdown of predictability, evidenced in complicated arrangements that initially defy order (Siemens, 2004). In chaos theory, meaning exists, but it is the learner s challenge to recognize hidden patterns. Complexity refers to the learning process as being complex, not complicated. Within complex learning theory, learning is influenced by innumerable, unpredictable factors. Whereas complicated learning can eventually lead to a clear result or end product, like the solving of a difficult jigsaw puzzle, complex learning can only be interpreted based on underlying factors and the outcome is greater than the sum of its parts. Siemens (2004) explains self-organization with the following information: Luis Mateus Rocha (1998) defines self-organization as the spontaneous formation of well organized structures, patterns, or behaviors, from random initial conditions. Learning, as a self-organizing process requires that the system (personal or organizational learning systems) be informationally open, that is, for it to be able to classify its own interaction with an environment, it must be able to change its structure. Connectivism can be referred to as networked learning. To explore this description, a closer look at networks is required. Networks are inherently simple; at the minimum they require two elements, nodes and connections. Nodes are elements that can be connected to other elements and connections are the links between nodes allowing for the flow of information. The stronger the connection between nodes, the faster information can travel. Siemens (2005) explains that nodes can take any shape or form including, thoughts, feelings, interactions with others new data and information. Collections of nodes create networks and