Blended Learning in Higher Education: Framework, Principles, and Guidelines - D. Randy Garrison, Norman D. Vaughan Measuring all-time greatest hits with Google Analytics Connectedness Helping people link to results. Friday, November 25, 2005 Measuring all-time greatest hits with Google Analytics Google released its web analytics as a free service about a week ago. Posted by Bruce Hoppe at 10:12 AM No comments: Post a Comment Newer PostOlder PostHome Subscribe to: Post Comments (Atom) Useful Links Popular archives SNA search engine <font size="-1">check out the <a href=" href=" at <a href=" Connectedness Tag-o-meter bookmark this on Delicious Related blogs SNA Publications Other resources Online SNA Textbooks SNA Software Blog Archive ► 2012(1) ► June(1) ► 2010(3) ► June(2) ► May(1)
The Online Learning Idea Book: Proven Ways to Enhance Technology-Based and ... - Patti Shank Social Interaction Design by Adrian Chan: SXD: The construction This piece has been adapted from a white paper I have in progress on the social web and social media. The paper concerns the deep relationality of social media. This is an excerpt on the construction of relations. ConnectionsThe world of the web is built on data that has neither fixed position nor place in terms of physical reality, but which exists by dint of its accessibility. All relations are constructed and subject to modification as those relations themselves develop (or lose) connections. In social media, participation in this world is always a construction of the world at the same time as it is a mode of consumption. Operations capture relationsSocial media systems, like any computer-based application, perform a variety of functions. These operations indeed make use of calculations and algorithms, but in the social web they usually appear quite socially meaningful. Sometimes a pair remains just a pair. But there are more operational orders available in the real world world.
ELI Discovery Tool: Blended Learning Workshop Guide 7 Things You Should Know About The 2016 Key Issues in Teaching and Learning February 11, 2016 Since 2011, ELI’s Key Issues survey has been a way for the higher education teaching and learning community to discover the common ground that cuts across differences such as Carnegie Classific… 2016 Horizon Report February 4, 2016 Produced by ELI and NMC each year, the Horizon Report describes six areas of emerging technology that will have significant impact on higher education and creative expression over the next one to… 7 Things You Should Read About Data Visualization for Instruction January 14, 2016 Developments in the tools for data visualization and increases in the types and amount of data available for visualizations offer new opportunities in pedagogy. 7 Things You Should Know About the Evolution of the Transcript January 11, 2016 Efforts are under way to capture a broader range of learning experiences and create frameworks to curate them, providing a more holistic view of student learning.
Predicting Tie Strength With Social Media - Social Media Group H Eric Gilbert and Karrie Karahalios of the University of Illinois at Urbana-Champaign have begun to study how social media can be used to predict tie strength in a sample of 2,184 Facebook relationships: They asked 35 people to rate a number of their Facebook friends that were randomly selected. Then they looked at the Facebook behavior of these people to see if could accurate predict the strength of their ties as reported by the participants. Dimensions such as the use of words associated with intimacy and intensity, duration of communication, social distance, and other factors were looked at for their predictive power. The complete set of variables was combined to form the predictive model that worked in 85% of the instances. The authors used 74 predictive variables, spanning connection intensity, intimacy, duration, reciprocal services, structure, emotional support, social distance, demographics, and usage: We identified 74 Facebook variables as potential predictors of tie strength.
The Technological Dimension of a Massive Open Online Course: The Antonio Fini University of Florence, Italy Abstract In 2008, a new term emerged in the already crowded e-learning landscape: MOOC, or massive open online course. Lifelong learners can now use various tools to build and manage their own learning networks, and MOOCs may provide opportunities to test such networks. This paper focuses on the technological aspects of one MOOC, the Connectivism and Connective Knowledge (CCK08) course, in order to investigate lifelong learners’ attitudes towards learning network technologies. Findings from a survey of CCK08 participants show that the course attracted adult, informal learners, who were not concerned about course completion. Connectivism and Connective Knowledge Course Multi-tool learning environments are gaining momentum. This paper focuses on the course Connectivism and Connective Knowledge (CCK08), facilitated by George Siemens and Stephen Downes in the fall of 2008 (Siemens & Downes, 2008). Background Method Results and Discussion
Connectivism: Learning theory of the future or vestige of the pa Rita KopUniversity of Wales Swansea Adrian HillOpen School BC, Canada Abstract Siemens and Downes initially received increasing attention in the blogosphere in 2005 when they discussed their ideas concerning distributed knowledge. Keywords: e-Learning; online learning; open learning; distance education; pedagogy; learning theory; educational theory Introduction To what extent do existing learning theories meet the needs of today’s learners, and anticipate the needs of learners of the future? If older theories are to be replaced by connectivism, then what are the grounds for this measure? With the changes that have occurred as a result of increased accessibility to information and a rapidly evolving technological landscape, educators in higher learning institutions have been forced to adapt their teaching approaches without a clear roadmap for attending to students’ various needs. Overview of Connectivism Connectivism is a theoretical framework for understanding learning. Figure 1.