Implications of connectivist pedagogy for online learning environments Betul C. Czerkawski, PhD. The University of Arizona South
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Abstract: In the recent years, e-learning gained wide acceptance in learning communities mostly because of its capability of reaching audiences by collapsing time and space, encouraging interaction and promoting learning. However, for learning to be effective, we now know that learning must use sound instructional design principles (Ally, 2008). This paper centers on connectivism, a new theory of learning, and discusses how connectivist principles are used in online learning environments.
Introduction: Connectivism is labeled as a learning theory of the digital age, for its emphasis on computer networks, networked communities, and technology. With its roots in computer science, connectivists believe that knowledge exists in the networked communities rather than individual brains. In his seminal article, Siemens (2004) defined connectivism as follows: Connectivism is the integration of principles explored by chaos, network, and complexity and selforganization theories. Learning is a process that occurs within nebulous environments of shifting core elements – not entirely under the control of the individual. Learning (defined as actionable knowledge) can reside outside of ourselves (within an organization or a database), is focused on connecting specialized information sets, and the connections that enable us to learn more are more important than our current state of knowing (para. 27). In addition to Siemens, Stephen Downes also contributed to the formation of this new theory. According to him, connectivism implies “a pedagogy that (a) seeks to describe 'successful' networks and (b) seeks to describe the practices that lead to such networks, both in the individual and in society (which is characterized as modeling and demonstration (on the part of a teacher) and practice and reflection (on the part of a learner)) (Downes, 2007, para.8). In 2006, Plon Verhagen responded to Siemens and Downes in another article arguing that connectivism is not a learning theory but a pedagogical view. According to Plon Varhagen, Siemens poses questions “regarding the influence of technology and chaos and network theory on learning, followed by listing some characteristics and properties of these developments” (p. 2), however, there is nothing at all new in these ideas. “Moreover, he is not convinced that learning can reside in non-human appliances.” (Kop & Hill, 2008, p.7). Regardless it is a learning theory or not connectivism offers many insights to those, who are designing online learning. Kop & Hill (2008) agree with the fact that a paradigm shift is happening in educational landscapes but this doesn’t confirm that connectivism is a separate learning theory of itself. It, “however, continues to play an important role in the development and emergence of new pedagogies, where control is shifting from the tutor to an increasingly more autonomous learner” (p. 10). This paper will present a list of suggestions along with the design principles.
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Online Learning Environments and Connectivism Emerging educational technologies present effective learning opportunities for the students, but this effectiveness is mostly because there are teaching strategies and learning principles built into those technologies. The research shows that using learning theories and principles in the design process promotes learning (reference). Today, there are many established learning theories as well as new and emerging theories, models and perspectives that try to guide the learning process by helping the students in the learning process. Connectivism is a new theory that emphasizes recent developments in the information society by claiming that learners are not in full control of their learning, due to massive developments in digital era. Theoretically, connectivism is heavily influenced by social constructivism, chaos theory and network theories. Some of the implementations of this theory for online learning can be summarized below: •
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When information is available and abundant to learners from all directions, one of the major skills today’s learners need to have is to be able to search, find and retrieve current information from a variety of networks. According to connectivism, developing “metaskills” in students is a very important purpose of education because this is how students evaluate and manage information and network connections. Therefore, online courses should include search engines, links to the major library sources, and wider community of knowledge networks, online or offline. Current course or learning management systems may not be best options for such an open learning concept, so opening individual courses to a wider community of learners using various online platforms such as wikis, discussion lists and blogs might be considered. In addition to the importance of learning new information, rapid changes in today’s information society requires that learners also need to be able to unlearn what they know because some of the information they know might become outdated quickly (Siemens, 2004). In the online learning environments, it is important that learners are introduced to a body of knowledge where change can occur immediately, and so flexibility in the course content should be provided and explained to the students. This way, learners wouldn’t feel uncomfortable with the changes in the content but know that this is the nature of knowledge, and that they are responsible for seeking for the most recent information continuously. The best way to encourage learners to stay up-to-date with the current developments is that to keep them responsible and part of the content determination process in the online courses. This definitely represents a major shift from traditional teaching or teacher-oriented environments. Siemens (2004) stresses the importance of global networks where information resides in any community or network in the world. With the use of internet-based technologies the world is connected more than ever, so learners should be encouraged to share information, review a variety of diverse opinions and perspectives and be allowed to communicate with the larger community of information. To do this, online course designers and instructors should find diverse networked communities for their learners and open communication channels with those communities so their students can communicate and connect with the larger information communities. One of the controversial ideas of Siemens is that he supports the fact that some knowledge in the information age may reside in machines. The best example of this is intelligent agents, where “an agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors” (Russell & Norvig, 1995, p.31). In education, intelligent agents are used to help learners to find and use information with little effort, they help reducing repetitive tasks or they monitor internet for the users so they can retrieve certain information they are looking for. In e-learning environments, some of the intelligence agents such as GoogleAlerts, Copernic Summarizer, FireFly, Copernic Search agent can be easily integrated in web-based learning systems. According to Siemens (2004), "the value of pattern recognition and connecting our own “small worlds of knowledge” are apparent in the exponential impact provided to our personal learning” (para. 32). Influenced by the chaos theory, Siemens believes that meaning exists in the networks, but learners’
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challenge is to recognize patterns, which seem to be hidden by them. Therefore, information pattern recognition can be used as a learning strategy (Couros, 2009) in e-learning courses. Learners can be asked to identify major trends on a certain topic or asked to create concept maps to make sense of new knowledge learned. All the information retrieved from various sources can be put together meaningfully if the learner uses this strategy effectively. Because pattern recognition requires uses to see the relationships between concepts, understand sequences, processes, connections and combinations in a given topic or field. As a matter of fact Siemens sees nodes as patterns of connections, which in turn get together and form networks of information. One of the important implications of connectivism is the beginning of personal learning environments (PLE). PLEs are basically systems where learners create their learning goals, control and manage their learning, and connect to the other information networks. A PLE can be any web-based technology that provides such a space to the learners. For instance, one of the early products of PLE is Elgg, which offers blogging, microblogging, file sharing, presentations, networking, groups and some other features. In traditional course or learning management systems, it is always the instructors who create the features for learners to use but in PLEs it is the learner, who is given a variety of tools so that they can be in control over what to include in their learning space. It is clear that traditional e-learning systems were not created such a goal in mind. However, a number of design criteria can be formulated for next generation e-learning environments using PLES. According to Schneider (2010) “future learning environments have to be PLEs in at least some regards, since the whole history of educational technology demonstrates, that the most popular applications in education always have been professional tools, not software made specifically for education” (para.10).
Discussion It is clear that connectivism as a new learning approach requires more empirical research data to support its claims. However, with its emphasis on networked communities, learner-controlled online learning environments, and open content/open education ideas, it also supports the need to shift from traditional course-based closed elearning systems to a more open, global and connected communities of learning. In addition, this pedagogy fosters design and development of online learning environments, where the guidance of a bold pedagogy is very much needed. More specifically connectivism has following implications for the future of e-learning: Personal learning environments. The idea of personal learning environments should move higher education institutions to a direction where they “provide a central access point to loosely coupled services within a web services-based architecture” (Schneider, 2010, para. 7). This doesn’t necessitate barriers on the usage of course management systems where traditional assessment and grading approaches are implemented but presents a new collection of tools for students who can connect to a wider community of knowledge through active participation. Instructors. Instructors can eliminate textbooks and traditional lectures and bring learners to the forefront in locating, presenting and making sense of relevant knowledge, thus allowing a fluid, social networking model the freedom to emerge (Darrow, 2009, p.53). Such a support would help higher education faculty to start experimenting with a variety of new web-based systems so they can provide more flexible online learning environments, while meeting the demands of digital age learners. Learners. In connectivist learning environments, “value is placed on student contributions and spontaneous, collaborative, student-generated curriculum; learners create their own knowledge in their own space (Darrow, 2009, p.53). More specifically on the learners’ part, connectivism stresses the following behaviors: “staying focused despite distractions, efficiently manage and navigate the flow of knowledge, extract relevant information, connect with others through network-building, stay current and informed, relate at a human level to form social spaces,
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ensure validity, recognize patterns and trends, and accept uncertainty. Connectivist learners should also display confidence, independence and discipline in accepting responsibility for their participation in online coursework.” (Darrow, 2009, p.56).
References: Ally, M. (2008). Foundations of educational theory for online learning. In T. Anderson. The theory and practice of online learning (pp. 14-44). Athabasca, Alberta: Athabasca University Press. Couros, A. (2009). Open, connected, social: Implications for educational design. Campus-wide Information Systems. 26 (3). (pp. 232-239). Darrow, S. (2009). Connectivism learning theory: Instructional tools for college courses. Published Masters’ Thesis. Western Connecticut State University. Retrieved from http://library.wcsu.edu/dspace/bitstream/0/487/1/Darrow,+Suzanne_+Connectivism+Learning+Theory_Inst ructional+Tools+for+College+Courses.pdf Downes, S. (2007). What connectivism is. Retrieved from http://halfanhour.blogspot.com/2007/02/whatconnectivism-is.html. Kop, R. & Hill, A. (2008, October). Connectivism: Learning theory of the future of vestige of the past? International Review of research in Open and Distance Learning. 9(3). (pp.1-13). Plon Verhagen, B. (2006). Connectivism: A new learning theory? Retrieved from http://www.surfspace.nl/nl/Redactieomgeving/Publicaties/Documents/Connectivism%20a%20new%20theo ry.pdf Russell, S. & Norvig, P. (1995). Artificial intelligence: A modern approach. Prentice-Hall, Inc. Retrieved from http://www.cs.berkeley.edu/~russell/aima1e/chapter02.pdf. Siemens, G. (2004). A learning theory for digital age: Connectivism. Retrieved from http://www.elearnspace.org/Articles/connectivism.htm Schneider, D. (2010). Personal learning environment. Retrieved from http://edutechwiki.unige.ch/en/Personal_learning_environment
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