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Innovation: Big Data and Analytics
George Siemens, PhDNEASC
December 9, 2015
This system is being unbundled & rebundled,
creating new power and influence structures
We don’t have the data or the models for understanding how dramatic changes now occurring
will impact higher education
Lack of data-informed decision making
culture
Macfadyen, L., & Dawson, S. (2012). Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan. Educational Technology & Society, 15(3), 149-163.
Siemens, Long, 2011. EDUCUASE Review
The WHY of learning analytics
“If the ladder of educational opportunity rises high at the doors of some youth and scarcely rises at the doors of others, while at the same time formal education is made a prerequisite to occupational and social advance, then education may become the means, not of eliminating race and class distinctions, but of deepening and solidifying them.”
President Truman, 1947
Pell Institute, 2015
McKinsey Quarterly, 2012
Student profiles
Diversifying(OECD)
Less than 50% now full time(US Census Bureau)
http://www.oecd.org/edu/skills-beyond-school/EDIF%202013--N%C2%B015.pdf http://www.census.gov/prod/2013pubs/acsbr11-14.pdf
Favours women over menMore learners as % (up to 60%)Average entrance age increasingTop three countries for entering students:
China, India, USATraditional science courses waning in popularityGreater international student
OECD 2013
Enrolment: “perfect storm of challenges ahead”
University Business, January 2015
To understand what tomorrow’s education system will look like, we have to understand the architecture of information today:
how is it createdhow is it sharedhow is it iterated
how is it controlled?
Parallel developing partners: Adaptive and personalized
learningPlatform Publisher
Knewton PearsonSmart Sparrow McGraw-HillDesire2Learn adaptcoursewareLoudCloud CMU OLI
Knowledge development, learning, is (should be) concerned with learners understanding relationships, not simply memorizing facts.
i.e. naming nodes is “low level” knowledge activity, understanding node connectivity, and implications of changes in network structure, consists of deeper, coherent, learning
Granularization of assessment
Cracking the credit hour (New America Foundation)
Badges(Mozilla & others)
http://newamerica.net/publications/policy/cracking_the_credit_hour http://openbadges.org/
Educational Quality through Innovative Partnerships (EQUIP)
Certificates
Fastest growing form of credentialing (800% increase in 30 years)
Industry-facing
Carnevale, Rose, Hanson 2012
Competencies
Competency-based degrees(Chronicle, 2014)
Prior learning assessment(Insider Higher Ed, 2012)
http://chronicle.com/article/Competency-Based-Degrees-/144769/ http://www.insidehighered.com/news/2012/05/07/prior-learning-assessment-catches-quietly
Knowledge in pieces
diSessa, 1993
“The world is one big data problem”Gilad Elbaz
The WHAT of learning analytics
In: Siemens, Gasevic, & Dawson (eds), 2015
Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs.
LAK11 Conference
Learning analytics is about learning
Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71.
Once size fits all does not work in learning analytics
Gašević, D., Dawson, S., Rogers, T., Gašević, D. (2016). Learning analytics should not promote one size fits all: The effects of course-specific technology use in predicting academic success. The Internet and Higher Education, 26, 68–84.
“a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better”
Douglas Bowman
What will LA do for learning science & education
Add a new research layerPersonalizationOptimization (move from negative orientation)Organizational insightImproved decision makingNew models of learningIncrease competitivenessImprove marketing/promotion/recruitment
Blending physical and digital spaces
WearablesAmbient computingIoT
…biometric/physiological data needed to answer complex questions around social and affective being and learning
The HOW of learning analytics
This system is being unbundled & rebundled,
creating new power and influence structures