Intro
Autodidactism
DataTimeline
Knowledge Economy Roles: Producer/Consumer
[Streamgraph of yearly knowledge graph channels]
How many days in a year?
Bookmarks
Growth Metrics
Tools and Data
Pushing for Cooler Calculations
Aquariums & Cave Diving
Undergrad STEM
GOALS
HISTORY
Challenges
One Million More STEM Trained
Simplest Approach to Augmenting Learning
Collaboration: Resources: Sharing Data Resources
Usability: Collaboration: Device Diversity
Standards: Standards Implementation
Usability: Interface Complexity: Scrolling through pages
Collaboration: Search & Peer Reviewed Learning
Collaboration: Indexing Things
Linking: Web Video
Value: Privacy
Value: Security
Collaboration: Versioning Things
Resources: Resource Constraints
Value: Employer Acceptance
Value: Verification
Value: Incentivization
Linking: Learning Assessments
Opportunities
"where can I add value?"
Web Video on the Radio
Learning STEM Theory, Process, and Knowledge
Value: Direct & Indirect Returns
Tools: Through Applied Data Science
Resources: Linking Things Together
Collaboration: Maximizing Collaborative Value: Network Effects
Collaboration: Feedback & Collaboration
Collaboration: Six Patterns of Collaboration
Collbaoration: Information Access Optimizations: TOC, Index, Search
Collaboration: Creative Process / Goal Attainment Paradigm / DMAIC
Collaboration: Healthy Online Communities: Python
Collaboration: Web Standards / Devices
Linking: Linked Data Workflows
Linking: Scheduling Learning Objects
Linking: Interface Flexibility Improvements / Standards
Linking: Augmenting Power of Search / Ctrl-F
Collaboration: Indexing Things
Collaboration: Wikipedia Notability / Local Resources
Strategies
Linking Process Components and Resources of a Learning System w/ Feedback
And Learning Environments
"Two Hard Problems in Computer Science"
Collaboration: Where do I put my slides?
Collaboration: Feature Decision Consensus
Collaboration: Knowledge Graph
Collaboration: Channels
Docs, Sheets, Slides // Word, Excel, Powerpoint
Video
Q&A
Chat
Resources: Bookmarks
Resources: Creating & Updating Resources
Resources: Labeling Things: Namespaces, URIs
Resources: Linking to Things with Metadata
Resources: Smart Tagging/Labels
Resources: Email Attachments & Document Sharing
Resources: Document Capturing / Process Artifacts
Resources: Versioning Things
Resources: Course Lifecycle
Linking: Generating Curricula Graphs and Traversal Sequences
Linking: Degr, Career, Resource Requirements as Constraints
Linking: DFS Traversal
Linking: Describing Learning Momentum
Linking: Reviewing & Improving Curriculum Sequences
Optimization: ROC, Cost, Complexity Value
Optimization: Machine Learning
Optimization: Activity Metrics
Optimization: Max Flow
Implementations
Learning Dashboard
Linking: Organizing 8.5x11
Standards: IEEE Learning Objects
Resources: Linking to Things with Metadata
Linking: Sequencing Objects in Practice
Collaboration: Managing Feedback
Linking: Mnemosyne
Linking: Grade Measuring Criteria
Linking: OCW, Coursera, EDX
Linking: Online University Courses
Collaboration: Comparison Scheme for Collaborative Technology
Collaboration: Killer Features
Authoring Tools
Standards: HTML, SCORM, REST, PRDF, SLIDES
Linking: The Simplicity of MOOCS
Q&A: Tutoring: You want to answer questions?
Q&A: Tutoring: But they are sharing the answers!
? Build Servers as Course Automation
Usability: ZIP of MP4 and SRT files
Usability: iCal of Course Calendar
Project: ReStructuredText metadata/microdata
Project: S5 Slideshow Content / Timing Guidelines
Project: JS Quiz Widget
Software R&D and Learning
Project Based Learning
To Compile a Course
Lean Production (*)
Processes, Resources, and Learning
Resources: README , TODO , Changelog .
Resources: Version Control
Documentation: Lightweight Markup Languages -> ReST
Documentation: Sphinx Documentation
Documentation: Bibtex
Documentation: Extending a Documentation Grammar Parser
Testing: Continuous Regression Testing as Learning
Testing: Links, Constraints, and Metrics
Testing: Test Cases for Comprehension
Testing: Code Review Software
STEM Laboratory Courses
Theory, Objectives, Questions, Process, Data, and Tools
Data Science Laboratory: Modeling Processes and Sequences
Tools: Python for STEM: [Python(x,y) mindmap]
Labs: STEM Labs Processes
Tools: OpenStack
Q&A: Preprocessing out Question Answers
Standards: Web Hooks / Repository Events
Q&A: JS Q&A Widget
Labs: Request / Response :: Push / Pull
Tools: Portability/Packaging: Egg, Wheel, Python Guides
Project: HTML5 JS Math Game Design
Project: If a Student were an API
Project: Build a Bookstore API
Project: CodeCademy
Project: Finding Tools Gaps
Challenges
Opportunities
Strategies
Value*+
Collaboration*
Resources*
Standards*
Tools*
Usability*
Sequencing* (Authoring)
Documentation*
Q&A*
Testing*
Labs* : Integrating Processes and APIs
Project* : where there are Gaps and Opportunities
Optimization*
Theory
Process
Knowledge
Objectives
Questions
Tools
Linking
Systems
Processes
Components
Resources
Learning System
Feedback
Learning Environment
Data
Gaps
Opportunities
Sequencing / Authoring / Linking
Topology
Tagging
Ontology
Folksonomy
Graph
Node
Edge
Vertex