Virtual environments, MOOs and Virtual agents

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Virtual environments, MOOs and Virtual agents
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Virtual Environments

• Readings for this week
• Peterson 1998 (VLE)
• Peterson 2004 MOO
• Morton and Jack 2005 Virtual agents
• Development of technology

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Virtual environments

• Learning environment (Peterson 1998)
• Very familiar one these days
• Does not now seem novel

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Construction of the learning environment

• Select a learning theory
• Cognitive processing model (Bialystock)
• Identify learner needs
• Needs analysis (questionnaire) (??)
• Choose website design tools
• Netscape Navigator Gold
• Browser/editor
• Hand-coding
• Dreamweaver etc.

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Construction of the learning environment

• Instructional design/HCI (human-computer
  interface) issues
• Choice of number of links, font type and size,
  use of colour, arrangement of the page
• Links -- page 1
• Cutting edge CALL Resources
• SchMOOze University
• Online English Grammar
• ESL Café

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Construction of the learning environment

• Links -- page 2 Technical Writing Page
• Bilingual English-Japanese Online dictionary
• Online Writing Lab
• Online Thesaurus
• The Elements of Style etc.
• Links -- page 3 Presentation Resources
• The Virtual Presentation Assistant
• Briefing Notes on Giving Short Talks
• Giving a Scientific Talk

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Virtual Learning Environment

• Site Evaluation
• Student feedback
• Lost in space -- Frames-based site
• More interactive materials needed
• More visual metaphors for navigation
• Online feedback link (email)
• Wider range of sites
• Site redesign

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Many VLEs available

• Individual sites, like Petersons
• CMS sites (Course Management System) Moodle, Web
  CT
• Intuto.com -- local online learning company

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Virtual Learning Environment

• Too static ??
• Should be possible to create an individualised
  VLE
• Student types in requirements
• Web-page is generated based on those requirements

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MOO

• MOOs and MUDs
• MOO -- multi-user object-oriented domain
• MOOs are virtual environments designed to
  facilitate synchronous text-based communication
  among users
• More permanent than chat rooms

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SchMOOze University

• http//schmooze.hunter.cuny.edu/
• Users log on (to a virtual domain such as a
  university)
• Create a nickname (and adopt an online persona
  ??)
• Users then interact, navigate and manipulate
  virtual objects
• Series of virtual rooms and objects

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Advantages of MOOs

• Increased communication
• Reduced stress
• Anonymous user
• New persona
• Easy to make a contribution

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Chatbots

• Original program -- Eliza
• Conversation with a psychiatrist (Rogerian type
  psychiatry)
• Designed to show that dumb programs could appear
  to be intelligent
• Eliza and chatbots
• http//www.cmr.fu-berlin.de/mck/courses/lv00ss/Pe
  KMan/team7/eliza.html

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Chatbots

• Turing test -- a test to see if a computer is
  intelligent.
• Loebner prize -- annual competition for chatbots

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Chatbot plus voice

• http//www.daden.co.uk/chatbots/pages/000067.html
• http//www.alicebot.org/

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Visual agents

• Morton Jack reading
• Avatars -- virtual beings -- extensions of humans
  in the virtual world. An avatar may be an virtual
  you
• Visual agents -- other beings in a virtual world

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Spoken Electronic Language Learning

• SPELL -- Morton Jack
• Includes speech recognition
• How good is speech recognition?
• How good is it with language learners
• Goal in this system is not to improve
  pronunciation, but to understand what the student
  says

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Semantic representations

• My guess is that the system uses representations
  of meaning based on verbs and their arguments
• Eat (I, hamburger)
• Want (I, (Eat (I, hamburger))
• Want (I, (Eat (I, ??))
• See (I, You)

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Semantic representations

• Dialogue
• Question What do you want to eat?
• Learner Id like a pizza
• Speech recognition has to decode the speech well
  enough to recognise hamburger or pizza etc. and
  create the meaning representation
• Want (I, (Eat (I, pizza))
• This can then be used to continue with the
  dialogue -- what kind of pizza would you like
• Is the goal to have a dialogue or give feedback??

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Desirable characteristics of speech interactive
CALL

• Wachowicz and Scott 1999
• Adopted by SPELL

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Interactions in SPELL

• Learner and computer interact -- no learner
  input, no dialogue
• Constrained environment -- so that the learner
  contribution can be understood
• Scenarios
• Observational scenario
• One-to-one scenario
• Interactive scenario

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Observational scenario
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Observational scenario

• Clear situation
• Students listen to the interaction
• Subtitles available
• Stop/start/replay the dialogue
• Access to other materials

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One-to-one
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One-to-one

• Virtual tutor agent asks the learner some
  questions
• About themselves
• About the dialogue
• What foods did the virtual people like?
• What foods does the learner like?
• Agents use pre-recorded audio files

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Interactive scenario
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Interactive scenario

• Learner enters the scene
• If he orders water, the waitress will bring
  water.
• Constrained environment limits what the learner
  is likely to say
• Recognition grammar -- range of utterances that
  the customer might use

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Interactive scenario

• Recognition grammar developed for each stage of
  the dialogue
• Possible learner errors are added to the
  recognition grammar
• The grammar is loaded into the program for each
  stage

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Interactive scenario

• For each stage, there are assumed to be four
  types of response

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Recasts
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Recognition Grammar
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Help for the learner -- reformulation
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Error analysis

• Errors for each learner are logged

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Prototype system

• Technical developments -- speech recognition of
  pronunciation
• Students want more affective behaviour from the
  visual agents
• (Eliza effect)

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Virtual Reality

• MOOs are VR environments
• Text-based
• Active Worlds -- http//www.activeworlds.com/
• Education programs

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Active Worlds
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MOOs, Avatars,CMC

• Where is the learning?
• Issues?