Digital Citizenship in the eLearning Ecosystem, social science homework help

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Digital Citizenship in the eLearning Ecosystem

Citizenship in a social network requires a person to abide by certain societal norms, rules, regulations, and laws. The web allows for persons to participate in many social networks with individuals around the world. It provides you opportunities and the freedom to speak your mind and show off your talent through text, images, and videos. This freedom, while wonderful, is loaded with potential pitfalls. A person’s behavior on the web is open for the world to see. It can also be easily duplicated and passed on to millions of people in a matter of seconds. For this Discussion, your role is as a leader within the eLearning ecosystem. Your task is to decide what behavior is appropriate on the web and how it should be taught to children and peers.

To prepare:

View the Anatomy of eLearning: Conceptual Framework interactive media presentation, with a focus on the “Theories” section. Review Ribble’s nine elements of digital citizenship with regard to technology use in “Digital Citizenship for Educational Change.” Read “Bridging Learning Theories and Technology-Enhanced Environments: A Critical Appraisal of Its History,” and reflect on Lowyck’s statement that “learning theories and technologies are connected and intertwined by information processing and knowledge acquisition” (p. 3).

Post the following by Day 6 of Week 1:

Rank Ribble’s nine elements of digital citizenship in order of importance for eLearning in your workplace for “peak learning performance.” Using at least one learning theory, justify your ranking of the elements of digital citizenship for the purpose of learning. Support your response from personal experience and at least one research study (PhD and EdS students).


I ranked Ribble’s (2012) nine elements of digital citizenship in order of importance as applied to eLearning in my workplace.  Cross (2004) defined eLearning as “learning on Internet time, the convergence of learning and networks” (p. 104).  Digital citizenship was defined in the Ribble (2012) article as, “norms of appropriate, responsible behavior with regard to technology use” (p. 149).  I considered the learning environment of physicians utilizing distant learning technologies in the healthcare marketplace.

The locus of control has changed from system to learner (Lowyck 2014). Realizing that learning theories cannot be precisely applied (Lowyck 2014,) and considering the general principles of the Constructivism and Connectivism (Siemens, 2014), I ranked Ribble’s elements as follows:  Digital Literacy, Digital Communication, Digital Etiquette, Digital Health and Wellness, Digital Commerce, Digital Rights and Responsibilities, Digital Law, Digital Security, Digital Access.  I aim to teach others with digital technologies; specifically:  templates, knowledge sharing, engagement, cloud authoring, time saving, collaboration, video, and workflow management systems. 

Several years ago, I observed the power of templates to successfully guide users towards standardization of healthcare practice norms.  Dobozy & Dalziel (2015) call this phenomenon “implementing learning designs across disciplinary boundaries” p. 183.  After my experience, I have been motivated to standardize and then scale my expertise across domains of which I am familiar.


Cross, J. (2004). An informal history of eLearning.On the Horizon,12(3), 103-110.

Dobozy, E., & Dalziel, J. (2015). The Use and Usefulness of Transdisciplinary Pedagogical Templates.Learning Design: Conceptualizing a Framework for Teaching and Learning Online, 183.

Lowyck, J. (2014).Bridging learning theories and technology-enhanced environments: A critical appraisal of its history. In J. M. Spector, M. D. Merrill, J. Elen, & M. J. Bishop (Eds.), Handbook of research on educational communications and technology (4th ed., pp. 3–20). New York, NY: Springer

Ribble, M. (2012). Digital citizenship for educational change.Kappa Delta Pi Record,48(4), 148-151.

Siemens, G. (2014). Connectivism: A learning theory for the digital age.

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-E11nrironments: A Cr'itkal Appraisal of Its History Joost Lowyck Abstract In education, retrospection is often used as a method for better understanding emerging trends as documented in many books and articles. In this chapter, the focus is not on a broad description of the history of educational technology but on the interplay between learning theories and technologies. However, neither learning theories nor tools are monolithic phenomena. They are composed of multiple attributes, and they refer to many aspects and facets which render the history of educational technology highly complex. Moreover, ·evoJution in both theory and technology reflects no clear successive .breaks or discrete developments-rather, waves of growth and accumulation. When looking_clOser·at learning and technology, it becomes clear that many interactions occur. TheSe interactions will be documented following continuous development after World War· II. We do not follow a strict timeline but cluster the critical appraisal in the following observations: (1) evolutions in society and education have influenced the selection and use of learning theories and technologies; (2) learning theories and technologies arc situated in a somewhat vague conceptual field; (3) learning theories and technologies are connected and intertwined by information processing and knowledge acquisition; (4) educational technologies shifted learner support from program or instluctor control toward more shared and learner control; and (5) learning theories and findings represent a fuzzy mixture of principles and applications. The history reflects an evolution from individual toward community learning, from contentdriven learning toward process-driven approaches, from isolated media toward integrated use, from presentation media toward interactive media, from learning settings dependent on place and time toward ubiquitous learning, and from fixed tools toward handheld devices. "" These developments increasingly confront learners with complexity and challenge their responsibility to become active participants in a learning society. ,.,..--. , Ke}'Wo'rdS I Learning theories • Educational technology • Technology Introduction l. Lowyck(181) Centre for Instructional Psychology and Technology (CIP & T), The Education and Training Research Group, Leuven University, Dekenstraat 2, Box 3773, B-3000 Leuven, Belgium e-mail: According to Gagne (1974) the main question of educational technology is: How can "things oflearning" best be employed to promote learning? In most discussions of technology implementation, learning issues remain relatively tacit (Bransford, Brophy, & Williams, 2000). Searching the relationship between learning theories and technologies is at first J.M. Spector et al. (eds.), Handbook of Research on Educational Communications and Technology, DOI 10.1007/978-1-4614-3185-5_1, © Springer Science+Business Media New York 2014 3 4 glance an attractive endeavor given its possible relevance for both educational theory and practice. However, dealing with this issue is quite complex. Indeed, a number of questions arise about the relationship of learning theory and technology, sometimes called a marriage (Perkins, 1991; Salomon & Ben-Zvi, 2006). Do learning theories refer to hybrid constructs or are they rather eclectic containers of more modest models or even common sense practice? How should technology be conceptualized? If a link exists between learning and technology, what is the nature of the relationship? Can we best label developments in the knowledge-base of learning and technology as paradigm shifts (Koschmann, 1996), sequential events (Sloan, 1973), or waves (Toffler, 1980)? In this chapter we will not reiterate broad accounts of evolutions in educational technology (see amongst others De Corte, Verschaffel, & Lowyck, 1996; Januszewski, 1996; Kozma, 1991; Mayer, 2010; Molenda, 2008; Reiser & Gagne, 1983; Saettler, 2004). We start the quest for linking learning theories and technologies at the moment explicit learning theory enters educational technology. The critical appraisal of the link between learning theories and technologies is structured around the following observations to reduce complexity and fuzziness in that interdisciplinary field: (1) evolutions in society and education have influenced the selection and use of learning theories and technologies; (2) learning theories and technologies are situated in a somewhat vague conceptual field; (3) learning theories and technologies are connected and intertwined by information processing and knowledge acquisition; (4) educational technologies shifted learner support from program or instructor control toward more shared and learner control; and (5) learning theories and findings represent a fuzzy mixture of principles and applications. Observation 1: Evolutions in Society and Education Have Influenced the Selection and Use of Learning Theories and Technologies Educational technology influenced in many and often centrifugal ways educational innovation as part of societal development. Successive behaviorist, cognitive, constructivist, and socio-constructivist approaches to learning and the concomitant use of technologies suggest a clear, straightforward contribution to education based on the internal dynamics of that field. However, one may wonder why in the 1960s and 1970s behaviorallearning theory, but no others, was selected as the focus of educational technology. Examples of more cognitively oriented theories available at that time are the work of Bartlett (1958) on "Thinking, an experimental and social study;' of Bruner (1961) on "The act of discovery," of de Groot (I 965, originally published in 1946) on "Thought and choice in chess;' of Dewey (1910) on "How to think;' of J. Lowyck Piaget (1952) on "The origins of intelligence in children," and of Vygotsky (1962, originally published in 1934) on ''Thought and language." These theories inspired school curricula and teaching methods but not technology use. Even though Newell and Simon (1972) contend that the appearance of modern computers at the end of World War II gave researchers the courage to return to complex cognitive performances, there was no relationship between early cognitive research and technology for education. It is clear that more than learning science controls the selection and use of peculiar learning theories and tools. This points to the impact of society on educational technologies in that learning theories are selected to support the technology implementation society drives us to employ (Boyd, 1988). Indeed, society holds strong expectatiSns to solve learning~ problems with technology. Expectations function as macrohypotheses that are progressively shaped and falsified during implementation, often resulting in more difficulties and less productivity than initially expected. One waits for the next, more powerful learning theory or tool (Lowyck, 2008). The influence of the Zeitgeist can be illllstrated with some examples. At first, audiovisual tools were expected to bring reality into the stuffy classroom and to bridge the gap between school and the world outside the classroom. Mass media (radio, film and television) were proclaimed to refresh education with real-world information presented just-in-time (Dale, 1953; Saettler, 2004). The audiovisual movement was grounded on communication theories that model the flow of interaction between sender and receiver, regulating the transport of information (Kozma, 1991; Levie & Dickie, 1973; Saettler, 2004; Tosti & Ball, 1969). While this movement nicely illustrates the impact of societal expectations on education, no explicit learning theory provided a foundation, so it is not part of our critical appraisal of linking learning theories and technology. At the end of the 1950s in the aftermath of the Sputnikshock, Western societies aimed at improving education quality especially in mathematics and science to compensate for the supposed failure of the progressive education movement and teachers' deficient classroom behaviors (Skinner, 1968). In line with the back-to-basics movement (Boyd, 1988), curricula were revised and proper, programmed design and delivery of subject-matter was expected to contribute to educationa1 quality based on a genuine science of instruction (Glaser, 1965; Lockee, Larson, Burton, & Moore, 2008). In a similar vein, democratization of education was aimed at giving increased access to education responding to the post-war baby boom which led youngsters in a prosperous economic period to mass education. This, however, raised concerns about individual development though interpreted in multiple ways by Rousseau-inspired romantics to more mechanistically oriented empirical behaviorists (Grittner, 1975). Computer-assisted instruction (CAI) ---Bridging Learning Theories and Technology-Enhanced Environments: A Critical Appraisal of Jts History claimed to realize individualization which brought Suppes (!969) to expec\ that computers could offer individualized instruction, once possible for only a few members of the aristocracy, to all students at all levels of abilities. However, the limited capacity of computers and reductionist instructional design at Iha! time hindered lhe full implementation of individualization. In the late 1970s, increasing use of personal computers in professional settings responding to the challenges of an information society created a new argument for the integration of computers in education and emphasis on acquiring computer skills (Dillemans, Lowyck, Van der Perre, Claeys, & Bien, 1998; Mandinach, 2009). This is why policy-makers in most Western countries launched extensive national programs to introduce new technologies in schools (Kozma, 2003). Learning to program computers, for example, was seen as a main task for education in a growing technology-rich society. Teachers and other computer savvy practitioners built instructional materials based on common sense knowledge of classroom teaching and content delivery with simple question-answer-feedback loops, vaguely inspired by behavioral principles (Saettler, 2004). This led to a proliferation of small and isolated CAI-programs, mostly in algorithmic subjectmatter domains with little theoretical underpinnings or fundamental goals to achieve (McDonald & Gibbons, 2009). The interplay between behaviorist learning lheory and technology ultimately resulted in inflexible and didactic instruction (Shute & Psotka, 1996). During the 1980s, a cognitive orientation in education was strongly supported by Western governments struggling with increasing worldwide competition in commerce, industry, science and technology. Enhancing learners' common understandings of complex issues, deep learning and complex skillfulness instead of mere subject-matter delivery was perceived as a strategic approach to societal survival (NCEE, 1983; Sawyer, 2006)_ This shift resulted in more complex forms of cognitive behavio!' embedded in school curricula, increasing interest jn the role of knowledge in human behavior, and an interactionist view of learning and thinking (Resnick, 1981). The ambition to tune education by means of technology to complex changes in society gave hirlh to a new wave of investments in research and development not only in supplying funds and resour<;;esfor equipment and network connectivity (Jones, 2003). Many computer microworlds, cognitive tools and instructional programs were produced at research centers, universities and enterprises (Duffy, Lowyck, & Jonassen, 1993). However, most of lhese computer-based educational systems were not widely adopted or embraced. This was due to both the not-invented-here syndrome and the increasing cost of commercial products (Boyd, 1988; Jonassen, 1992)_ Intensive electronic networking, and social media reflect more recent changes in society that are expected to add value 5 through a common purpose and deliberate collaborative action in a community of learners and practitioners (Center for Technology in Learning, SRI, 1994). Increasing miniaturization, integrated functionalities, and wireless use comprise a communication hyperspace in a global world that call for new ways of technology use in education. This is why socio-constructivist theories and technology-supported communities of learning and practice have become dominant, at least as a frame of reference within the community of educational technologists. Summary Evolutions of learning theories and technologies show internal and autonomous dynarnicS that lead toward mutual fertilization. Pressure in Western countries to survive in a scientifically and economically changing, competitive world activates governmental initiatives to support technology in schools through financial support and stimulation of research and development However, policy makers often formulate unrealistic expectations due to lacking knowledge of lhe multidimensionality of technological solutions for education. Commercial organizations respond to societal demands with little concern about efficiency, effectiveness and relevance of educational products and processes, an observation that brings researchers to request grounded evaluation (Clark, 1983; Salomon, 2002). Schools and educational institutions are involved in lasting and difficult processes of innovation through technologies that impact aII organization components (curricula, personnel, finances, infrastructure, etc.), while teachers and learners are chalJenged to cultivate new competencies, unlearn dysfunctional behaviors and conceptualizations, and build new perspectives on technologies for learning. Observation 2: Learning Theories and Technologies Are Situated in a Somewhat Vague Conceptual Field Exploring links between learning theories and technology is dependent on agreed upon conceptual frameworks and concepts wilhin research traditions. Each field of study is filled wilh ill-defined concepts and terminology that is inconsistently used and leads toward different starting positions. A basic science of learning starts from the insight that little is known and that much has to be discovered, while applied science and technology focus on what is known and applicable in practice (Glaser, 1962). Despite continuous efforts to calibrate conceptual issues (Januszewski & Persichitte, 2008; Reiser & Ely, 1997), and unlike the natural sciences, concepts in the behavioral sciences are rarely standardized 6 (Halliday & Hasan, 1985). That concepts arc used in various ways becomes especially problematic when central theoretical importance is involved (Frenzel & Mandi, 1993). learning Theories Leaming as a relatively permanent change in motor, cognitive and psychodynarnic behavior that occurs as a direct result of experience is shared by all learning theories. Despite this largely accepted definition, ''learning theory" remains a broad term with many perspectives "ranging from fundamental exploratory research, to applied research, to technological development, through the specification of work-a-day methods of practice" (Glaser, 1965, p. 1). Conceptual confusion originates partly from an over-generalization of successive ways of thought that are perceived as the way things are. Observable behavior, mind, information processing, sociocultural theories, genetics and brain research are changes that signal scientific progress but the tendency to over-generalize is often driven by other than scientific considerations (Bredo, 2006). Given the intrinsic limitations of educational research, no single theory encompasses all aspects of learning and learners (Gage, 1972). Consequently, various theories that emerged as researchers focused on different kinds of learning only represent a limited part of the knowledge-base of psychology as a discipline (Bransford et al., 2006). In addition, learning theories do not constitute a monolithic, coherent system but each school of thought represents a collection of distinct theories that are loosely connected (Burton, Moore, & Magliaro, 1996; Dede, 2008) a fact that led to the balkanization into smaller communities with different research traditions and largely incommensurable views of learning (Koschmann, 1996). While behavioral theory and early information processing theory use definitions that are instrumental to experimental research, socio-constructivist theory is complex, eclectic, and multifaceted (Lowyck & Elen, 1993). A possible solution is to take a pragmatic position defining learning theories as an interrelated set of facts, propositions, rules, and principles that has been shown to be reliable in many sitnations (Spector, 2008). Though this may be helpful to avoid conceptnal fuzziness, it seems hard to define valid and precise criteria to differentiate between evidence-based and common sense knowledge in an educational context. J. and Technology; http://www/aect.orgJ refers to the "disciplined application of scientific principles and theoretical knowledge to enhance human learning and performance" (Spector et al., 2008, p. 820), which is very close to instructional design as defined by Gagne (1974) as a "body of technical knowledge about the systematic design and conduct of education, based upon scientific research" (p. 3). Technology as the mere application of research findings was highlighted in the years of programmed instruction with procedures for behavioral modification to reach terminal behaviors (Glaser, 1965). Along with an increasing variety of learning theories, different genres of technology-based learning environments covered different functions of educational technology, including intelligent tutoring systeips, interactive simulg.tions and games, animated pedagogical agents, virtual environments, and computer-supported collaborative learning systems (Mayer, 2010). Others focus on the physical aspects of technology via which instruction is presented to the learners. McDonald and Gibbons (2009) refer to this as the tools approach which holds the expectation that using technological tools will affect learning outcomes. This led to various gimmicks being introduced in schools as extras not necessarily well aligned with the teaching-learning process (Husen, 1967). Machines on their own will not bring about any change (Stolurow & Davis, 1965). This statement is close to Clark's (1983) view that method, not media, detennines effectiveness. This claim also pertains to the comparison of computer-based environments (e.g., desktop simulation and virtual reality simulation) (Mayer, 2010). The question, however, is not if tools can contribute to learning but how instructional materials in various forms can enhance learning and allow the manipulation of the properties of instruction that impact learning (Lumsdaine, 1963). This reflects the position of Kozma (2000) who emphasizes a nexus of media and method. Indeed, technology allows for methods that would not otherwise be possible, such as interactive multimedia simulations that support the ability to act on the environment and not simply observe it (Winn, 2002) or hypermedia that challenge cognitive flexibility while crisscrossing the information landscape (Spiro, Feltovich, Jacobson, & Coulson, 1992). In times when information and communication technologies deeply penetrate society, the dichotomy between applied science and tools technology has been in favor of synergy. Educational technology involves a broad variety of modalities, tools, and strategies for learning (Ross, Morrisson, & Lowther, 2010). Technology ' ' Educational technology holds a double meaning: (a) application of scientific know-how, and (b) tools or equipment (Glaser, 1965; Molenda, 2008; Reiser & Gagne, 1983). AECT (the Association for Educational Communications linking Learning Theories and Technology Given the complexity and diversity of conceptnalization, it seems difficult to ...
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School: UCLA



Digital citizenship
Student’s name
University affiliation

According to Collier, 2009, it is referred to as the “critical and ethical choices about the
content and impact on oneself or others and the society as a whole of what one sees, says and
produces with media, devices and technologies. Due to continuous use of digital technology,
most of the educators have applied the use o intense technological knowhow to advance on their
learning process (Siemens, 2014). Regardless of th...

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