The Power of Massive Informal Learning Environments
- 1. The Power of Massive Informal Learning Environments Donny Tusler, M.Ed. Ph.D Student; dkt124@psu.edu Nicole Wang, MS.Ed, IEDP, Ph.D Student; nicolewang12@gmail.com Penn State University; World Campus, Learning Design & College of Education
- 2. Overview What is M.I.L.Es? p-M.I.LEs? Visual Model of digital environments with technology Theories Case Study Visualization
- 3. Three Digital Learning environments Formal LMS Non-formal MOOCs Informal Social Networks
- 4. What is a Massive Informal Environment(s)? M.I.L.Es The digital learning networks consisting of informal connected learning, composed of the creation and or organization of knowledge and content, through the dissemination of knowledge through social networks. These social networks result in both synchronous and asynchronous interactions with no measurable learning outcome or structure.
- 5. Personal Massive Learning Environments A Personal Massive Learning Environment (p-M.I.L.Es) is the organization of learning portals and affinity spaces, connecting each p-MILEs with the Massive Learning Environment; this includes social media platforms and applications. The tools (such as mobile devices, computers, etc.) and software platforms allow one to create personalized digital learning networks, which varies in level of engagement, seamlessness, and connectivity to M.I.L.E
- 6. Leveraging M.I.L.Es Transformation of API data from p-MILEs to collect and track the big data. This big data will show metadata, personal interests, time, click-by-click, levels of engagement, and more. - Presented NMC Summer 2016 - Donny Tusler and Nicole Wang
- 7. Model is Evolving “The idea is simple yet potentially transformative: analytics provides a new model for college and university leaders to improve teaching, learning, organizational efficiency, and decision making and, as a consequence, serve as a foundation for systemic change.” (Siemens, G., & Long, P. 2011.p. 32)
- 8. Learning Theories & Perspectives Constructivism Constructionism Sociocultural Cognitivism Behaviorism Connectivism The Shift- Karl Fisch- The impact of digital or ethereal dimension or non-tangible. ● 2008- 2.7 billion google searches/month ● 2016- >100 billion google searches/month ● Each search is manifestation of a question or a potential learning moment. Bell- “Life-Wide Learning” Self directed learning based on interest
- 9. Case Study About: I make comedy videos. I also post stuff that I find funny around the internet. I do not profit from any of the direct posts on this page. You have an issue or believe something was not credited correctly then let me know in a message! Observed a Social Experiment conducted by this comedy fan page.
- 10. Qualities of the photo Original Photo: Director present- photoshopped Posing HighResolution At least one highly recognizable actor.
- 11. Case Study Levels of learning- not trackable, but through comments Levels of cognition- how is it measured? Levels of unconscious cognition- how is it measured? Unconscious cognition vs. implicit learning? Measurements of Engagement- digital tracking of likes and shares. Click streams. Meaning behind the shares, likes:
- 12. Analytics Oct 7: 214,271 shares 15,306 likes 13 K comments #Belief of real #Movie recognition First 4,000 shares/likes analysed. April 16: 142,487 shares 15,306 likes 11 K comments # Belief of real # Belief of unreal
- 13. Ethics of Leveraging Data- Private vs. Public? IRB- Non-human study Informed consent Anonymity Risk of harm Terms, conditions and ethical research with social media Privacy and risk Re-use and republication For educators of digital literacy: Ethics need to be taught in digital literacy.
- 14. References Barron, B. (2006). Interest and self-sustained learning as catalysts of development: A learning ecology perspective. Human development, 49(4), 193-224 Bell, F. (May, 2010). Network theories for technology-enabled learning and social change: Connectivism and actor network theory. In Networked Learning Conference 2010: Seventh International Conference on Networked Learning. Bell, Philip, et al. Theoretical Perspectives. Learning Science in Informal Environments: People, Places, and Pursuits.Washington, D.C. NAP. 2009. pp. 27-53 Bransford, John D., et al. Foundations and Opportunities for an Interdisciplinary Science of Learning. Cambridge Handbook of the Learning Sciences. Sawyer, K. ed. New York. Cambridge University Press. 2006. 0521607779. Ch. 2. pp. 19-34. Center for Teaching. (2016). Retrieved May 26, 2016, from https://cft.vanderbilt.edu/guides-sub-pages/blooms-taxonomy/ Cummins, M., Johnson, L., & Adams, S. (2012). The NMC horizon report: 2012 higher education edition. The New Media Consortium. Culter, D. (May 1, 2015). Shift Happens: Karl Fisch On Education. Retrieved October26 , 2015, retrieved from http://www.spinedu.com/shift-happens-karl-fisch-education/ - .VkjtDVNViko Driscoll, M. (2005). Introduction to Theories of Learning and Instruction. In Psychology of Learning for Instruction (pp. 29-68). Boston, MA: Pearson. Ito, M., Gutierrez, K., Livingstone, S., Penuel, B., Rhodes, J., Salen, K., ... & Watkins, S. C. (2013). Connected learning: An agenda for research and design. Digital Media and Learning Research Hub. Gee, James P. (2004) Affinity Spaces. Situated Language and Learning. New York. Routledge.0415317762. pp. 79-89. Statistia., (2016). Leading global social networks 2016. Retrieved June 07, 2016, from http://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/
- 15. References - continued Looi, C. K., Seow, P., Zhang, B., So, H. J., Chen, W., & Wong, L. H. (2010). Leveraging mobile technology for sustainable seamless learning: a research agenda. British Journal of Educational Technology, 41(2), 154-169. Morris, D. Z. (March 27, 2016). Netflix says Geography, Age, and Gender are “Garbage” for Predicting Taste. Retrieved April 14, 2016, from http://fortune.com/2016/03/27/netflix-predicts-taste/ Office of Educational Technology, U.S. Department of Education, "Learning, " Future Ready Learning: Reimagining the Role of Technology in Education, 2016 National Education Technology Plan. Pea, R. D., & Gomez, L. M. (1992). Distributed multimedia learning environments: Why and how?. Interactive learning environments, 2(2), 73-109. Sawyer, R. K. (Ed.). (2014). The Cambridge Handbook of the Learning Sciences (2nd ed.). Cambridge University Press. Siemens, G. (2014). Connectivism: A learning theory for the digital age. Siemens, G., & Long, P. (2011). Penetrating the Fog: Analytics in Learning and Education. EDUCAUSE review, 46(5), 30. Shulman, D. (March 7, 2016). Personalized Learning: Toward a Grand Unifying Theory. EDUCAUSE. Retrieved May 10, 2016, from http://er.educause.edu/articles/2016/3/personalized-learning-toward-a-grand-unifying-theory 21st Century Skills Definition. (2013). The glossary of education reform. Retrieved May 26, 2016, from http://edglossary.org/21st-century-skills/
- 16. References- continued Case Study data source link: https://www.facebook.com/shares/view?id=1595894337124597 Snopes article: http://www.snopes.com/vietnam-veterans-tropic-thunder/ http://www.spinedu.com/shift-happens-karl-fisch-education/#.WAD70pMc6ko http://infed.org/mobi/what-is-non-formal-education/ http://expandedramblings.com/index.php/by-the-numbers-a-gigantic-list-of-google-stats-and-facts/