Introducing
Your new presentation assistant.
Refine, enhance, and tailor your content, source relevant images, and edit visuals quicker than ever before.
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Individual characteristics:
physical - emotion - cognition - history
Global - national - regional
Family - friends - colleagues - professionals
AND MORE IMPORTANT
The knowledge community with special language, concepts & practices
Epistemological Sources:
Explanatory - Deductive - Conceptual Analogical - Perceptual
Qualitative-Complex Systems-Quantitative
...tests, observations, examining artifacts...
Cognitivism
Adjacency matrices are used to create network maps of brain states
Data is transformed to represent time slices of interest via adjacency matrices
Sensors capture 128 records per second during digital media performance and learning
Contructivism
Adaptive Digital Media
“Network-Based”
Online data gathering +
Distributed interoperating web services
The sensors provide simultaneous multi-channel data
"Assessment"
Measures and feedback for improvement of performance and evaluating learners, that are “multidimensional, integrated, and revealed in performance over time” (Walvoord & Anderson, 1998)
Next stops on the path are examples of "semantic data" generation
Personalization
Analytics
Prediction
Intervention
See George Siemans blog re: Learning Analytics
http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/comment-page-1/#comment-68911
http://www.niusileadscape.org/mp/City/N1709930?year=2005
Imagine teaching an online course and mapping the distribution of grades on the last assignment.
A design for any
digital media learning experience...with computational representations of assessment functions
http://www.equityallianceatasu.org/ea/equity-matters
Emerging capabilities in metadata generation offer the potential for identifying the problem-solving strategies of learners.
Complex performances can be supported and documented in network-based assessments via multimedia, multileveled, and multiply connected bases of knowledge.
Analysis of expert-novice differences can be facilitated across groups, across space and time, drawing from an evolving common knowledge store.
Network-based assessments can include statistical analysis and displays of information to assist learners and teachers in making inferences about performance.
The interactive potential of network-based assessment opens up new possibilities for fostering and determining metacognitive skills of the learner.
With many instances of the learner interacting with applications in different times, places and contexts, network-based assessments can build a long-term record of documentation, showing how learners change over time.
Decisions & Dilemmas of Assessment
Community
Imagine these as performance levels in the skills to be acquired...
http://stackoverflow.com/badges
Assessment
Your unique
solution suite of
tools & practices
Behaviorism
NY TIMES (Mixing traditional and new methods, the journal posted online four essays not yet accepted for publication, and a core group of experts — what Ms. Rowe called “our crowd sourcing” — were invited to post their signed comments on the Web site MediaCommons, a scholarly digital network. Others could add their thoughts as well, after registering with their own names. In the end 41 people made more than 350 comments, many of which elicited responses from the authors. The revised essays were then reviewed by the quarterly’s editors, who made the final decision to include them in the printed journal, due out Sept. 17.
http://www.my-efolio.com/
New Media Affordances
Evidence Centered Design
http://www.nytimes.com/2010/08/24/arts/24peer.html?
...where complexity analysis is
going to be helpful in finding coherent resolutions among the layered & overlapping frames of reference
I fed in an 8 page conference paper
and got several terms...
Structure-behavior-function
Emergent properties
Control/feedback
Processes
Boundaries
Subsystems
Interactions
Multiple variables
Trade-offs
Requirements
Resources
Physical Laws
Social constraints
Cultural norms
Side effects
http://www.alchemyapi.com/api/demo.html
http://cogsci.uwaterloo.ca/Index.html#software
http://semanticproxy.com/
Machines will learn to make their own topic maps by observing performances and artifacts - and will be able to compare their topic maps to those in order to make an assessment.
http://cogsci.uwaterloo.ca/JavaECHO/echoApplet.html
http://www.wandora.org/wandora/wiki/index.php?title=Topic_Maps
Automated assessment
with topic maps will include pattern
recognition & judgment
assistance for humans
and computer agents
Bayesian Essay Test Scoring sYstem
http://echo.edres.org:8080/betsy/
Knowledge
In this example, the
computer recognizes similarities between
two visual examples (e.g. "same color" & "same cone-like shape")
See Paul Thagard's work
Learner
Assessment & Digital Media Learning
New possibilities for assessment stem from