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Assessment & Digital Media

Created for the un-panel start to an un-conference at Duke, with thanks to HASTAC and the MacArthur Foundation, this Prezi was edited for the DML conference in March 2011, adding new research on network analysis of learner physical, emotional and cognitiv
by

David Gibson

on 17 August 2011

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Transcript of Assessment & Digital Media

Learner
Knowledge
Community
Assessment
Peer-to-Peer Pedagogy
ePortfolios
Project & Challenge Based
Learning
Learning Theory
Evidence Centered Design
“Network-Based”

Online data gathering +
Distributed interoperating web services
Decisions & Dilemmas
New Media Affordances
Your unique
solution suite of
tools & practices
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...
Ownership
Media
Focus
New possibilities for assessment stem from
evidence centered design theory,
traditional decisions and dilemmas of performance assessment, and
the affordances of immersive digital media learning environments.

Assessment & Digital Media Learning
Cognitivism
Behaviorism
Contructivism
Digital Media Assessment Theory
"Assessment"

Measures and feedback for improvement of performance and evaluating learners, that are “multidimensional, integrated, and revealed in performance over time” (Walvoord & Anderson, 1998)
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.
Emerging capabilities in metadata generation offer the potential for identifying the problem-solving strategies of learners.
The interactive potential of network-based assessment opens up new possibilities for fostering and determining metacognitive skills of the learner.
http://www.equityallianceatasu.org/ea/equity-matters
http://www.niusileadscape.org/mp/City/N1709930?year=2005
Automated assessment
with topic maps will include pattern
recognition & judgment
assistance for humans
and computer agents
In this example, the
computer recognizes similarities between
two visual examples (e.g. "same color" & "same cone-like shape")
http://www.my-efolio.com/
Thank you!
Self-Directed,
Personalized Learning
Learner
Knowledge
Assessment
Community
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.
Network-based assessments can include statistical analysis and displays of information to assist learners and teachers in making inferences about performance.
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.nytimes.com/2010/08/24/arts/24peer.html?
Author
Experts
Crowd
Editors
Intersectionality
Automated Tagging & Text Mining
http://www.wandora.org/wandora/wiki/index.php?title=Topic_Maps
http://www.alchemyapi.com/api/demo.html
http://semanticproxy.com/
Feed in some documents or web pages, then...
...which leads to topic maps and other forms of semantically organized information
I fed in an 8 page conference paper
and got several terms...
...where complexity analysis is
going to be helpful in finding coherent resolutions among the layered & overlapping frames of reference
Primary proposition:
GIS Mapping of Social Characteristics
Equity Alliance & Leadscape @ ASU
An Example of Peer-to-Peer Assessment
Illustrates the need to understand...
An example of metadata generation
david.c.gibson@asu.edu
Structural modeling can now start with drawings and qualitative understandings...

...& be mathematically rigorous.
A design for any
digital media learning experience...with computational representations of assessment functions
Imagine teaching an online course and mapping the distribution of grades on the last assignment.
Decisions & Dilemmas of Assessment
Evidence Centered Design
New Media Affordances
Imagine these as performance levels in the skills to be acquired...
An example of metadata generation is coming next
Intersection of MIRROR, PUBLIC, MEDIA
Intersection of MAP, TRUSTED OTHER, ARTIFACT
Intersection of SONNET, PUBLIC, FOCUS
Needs human shaping...called "supervised learning" of the artificial intelligence
How do student grades relate to where they live?
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.
BETSY
http://echo.edres.org:8080/betsy/
Bayesian Essay Test Scoring sYstem
Automated Essay Scoring
http://cogsci.uwaterloo.ca/Index.html#software
Software from the Computational Epistemology Laboratory
http://cogsci.uwaterloo.ca/JavaECHO/echoApplet.html
Analytics
Prediction
Adaptive Digital Media
Personalization
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
Next stops on the path are examples of "semantic data" generation
See Paul Thagard's work
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
Optimization
Systems
Engineering Concepts
Sensors capture 128 records per second during digital media performance and learning
The sensors provide simultaneous multi-channel data
Data is transformed to represent time slices of interest via adjacency matrices
Adjacency matrices are used to create network maps of brain states
http://stackoverflow.com/badges
Full transcript