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New Topologies for Learning. Tim O’Shea & Eileen Scanlon. Peter Drucker in Forbes ‘97. IT Progress will mean the end of the residential university by 2030 AD; replaced by personalized technologies for learning. Talk Structure. Ideal Next Generation Providers

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new topologies for learning

New Topologies for Learning

Tim O’Shea

&

Eileen Scanlon

peter drucker in forbes 97

Peter Drucker in Forbes ‘97

IT Progress will mean the end of the residential university by 2030 AD;

replaced by personalized technologies for learning.

talk structure
Talk Structure
  • Ideal Next Generation Providers
  • Actual Next Generation Providers
  • History of eLearning
  • Recent Technological Innovations
  • Nice Exemplars
  • Themes & Issues
  • Reasons for Optimism
the ideal
The Ideal
  • Comprehensive Online Curriculum
  • Personalised Support
  • Peer Learning Cohorts
  • Integrated Admin & Learning
  • Mobile & Blended Modes
  • High Integrity
  • Respected Degrees
major universities
Major Universities
  • Research Led Learning
  • Digitising Intellectual Assets
  • Extending Curatorial Role
  • Weak on Integrated Admin
  • Weak for Remote Students
  • Struggling with Assessment
  • History of Awarding Degrees
other providers
Other Providers
  • More Responsive & Flexible
  • Closer to New Tech
  • Cross Borders more Easily
  • Integrated Solutions
  • No Researchers or Curators
  • Very Limited Assets
  • Value of new ‘Awards’?
taxonomy of models
Taxonomy of models
  • Using psychological models of learning to classify different approaches to e-Learning, technology enhanced learning, computer assisted learning …
models
Models
  • Reinforcement
  • Association
  • Feedback
  • Programming
  • Developmental
  • Symbolic
  • Collaborative
  • Environmental
slide9
One can predict that in a few more years millions of schoolchildren will have access to what Philip of Macedon’s son Alexander had enjoyed as a royal prerogative - a tutor as well-informed and responsive as Aristotle.
  • Pat Suppes 1966
enhancements to learning
Enhancements to Learning

Special properties computers can contribute to enhance quality of learning

enhancements
Visualisation

Diagnosis

Remediation

Reflection

Memory Prostheses

Tackling the Hypothetical

Time Travel

Autonomy

Pacing

Motivation

Redundancy

Group Working

Scaffolding

Access

Knowledge Integration

Enhancements
slide13
People are driven by a will to mastery (challenge), to seek optimally informative environments (curiosity) which they assimilate, in part, using schemes from other contexts (fantasy)
  • Malone/Piaget
technology drives
Technology Drives
  • Moore’s Law
  • World Wide Web
  • RFID & Portable OOPS
  • VoIP
  • VLEs
  • Constant Connectivity
  • 3D Virtual Realities
recent events
Recent Events
  • 1Bn Internet Users
  • 25% read Blogs
  • 10 Bn Google uses/day
  • Wikipedia v Brittanica
  • YouTube (videos)
  • MySpace (egos)
  • SunSPOT & Specks
edinburgh exemplars
Edinburgh Exemplars
  • Range of Contexts
  • Digimap/EDINA/JISC
  • eScience (with Glasgow)
  • High Performance (CCLRC)
  • Digital Curation Centre (G&B)
  • Divinity – using key assets
  • Midgealert – models & maps
scott mcneally 04

Scott McNeally ‘04

‘Book are so last Millenium’

slide26

The Library has a new ‘federated search service’ which provides a Google-like search of Library indexes and full-text databases – both commercial services taken on subscription, and databases we have built ourselves

slide27

We can select a subject cluster, as here, a ‘Quicksearch’, or to search against all (currently 300) databases, using a keyword or keywords

slide28

Results take only a few seconds, even for searches against a large numberof databases. Here we have only searched locally-created databases

slide32

Digitised Library treasures are made available in undergraduate and postgraduate courses

slide33

S

Search for Resources

The federated search service can be ‘pasted in’ to useful otherenvironments, such as a course website, in the form of a ‘Googlesearch box’, with the subset of databases chosen by academic staff

objectives aims
Objectives/Aims
  • LeActiveMath aims at advancing e-learning technology by developing innovative technology and by integrating advanced tools and components in one open, service-based system. The progress is evaluated in realistic learning settings1.
  • The benefits for students using LeActiveMath include:
    • Learning material tailored to the students' needs and interests. The personalization is pedagogically/cognitively justified.
    • Students can work interactively with tools, take the initiative and self-regulate learning, e.g. in interactive exercises, in tutorial dialogues, in choosing learning settings and include learning objects, and searching for learning objects and interactive exercises. 
    • Students can inspect their learner model and negotiate modifications. These meta-cognitive activities will support acceptance and self-monitoring. Since the learner model includes beliefs not only about the student's competencies but also about motivational variables, the system can adapt the feedback, dialogues and the user interface to the learner's motivation.
    • Students can communicate in their own words in the dialogue.
slide37

Table of Contents

Definition

A Book

A Chapter

Example

A Page

Note

tutorial dialogue

Student types a statement

Tutorial Dialogue

Adds math formulae

Sends statement

Statement is added to dialogue and the system responds.

Response explains concepts and sets further exercises.

slide39

Mastery colours represent the user’s knowledge for the content of each page.

If the user hovers the mouse over these mastery colours a percentage knowledge value is displayed.

LeAM estimates user knowledge based on their performance on exercises.

These beliefs are based on mathematical concepts not just content. As these concepts are shared by different pages the mastery colours propagate to pages that the user hasn’t even viewed yet.

This allows the user to see what the already know and what they still have to learn.

navigation support

Navigation Support

Where am I in this information space?

Is it really a 2D space, tree, network lattice?

Who is also active in the space?

How can I plan next week’s route?

How can I travel between spaces?

How can I travel in parallel?

virtuality
Virtuality
  • Value – reduces memory load, structures experience, easier to use and retrieve use
  • Key metaphor – ‘Direct manipulation’
  • Virtual Microscope
  • Virtual Summer School
  • Virtual University
  • Virtual Reality
  • Virtual Library
themes
Themes
  • Technology Push
  • Globalisation Pull
  • Blended Learning
  • Intellectual Asset Management
  • Personalisation & Podcasting
  • Assessment & Authentication
  • New Learning Topologies
issues
Issues
  • Security & Identity Management
  • Object Economy (di Sessa ILE 2004)
  • No Significant Difference (Kim on 3D)
  • Digital Divide/Disconnect
  • Interoperability
  • ‘Open’Standards
  • Robust Assessment Models
grounds for optimism
Grounds for Optimism
  • Past Predictions – Turing, Bush, Moore, Kay
  • Robust Sector – WorldCOM, WebCT, ICL
  • Students using Google
  • University of Highlands & Islands
  • RCA Annual show – multiple modalities
  • Earth Lab
  • JISC & JANET
  • Actual Practice – Edinburgh/Stanford/MIT
acknowledgements
Acknowledgements
  • Jeff Heywood
  • David Dewhurst
  • Rachel Ellaway
  • Sian Bayne
  • Sheila Cannell
  • Jane McCloskey
  • Simon Jennings
  • Many Others @ UoE