Virtual environments, MOOs and Virtual agents

1. Virtual environments, MOOs and Virtual agents

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

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

4. 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.

5. 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

6. 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

7. 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

8. Many VLEs available • Individual sites, like Peterson’s • CMS sites (Course Management System) Moodle, Web CT • Intuto.com -- local online learning company

9. 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

10. 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

11. 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

14. Advantages of MOOs • Increased communication • Reduced stress • Anonymous user • New persona • Easy to make a contribution

16. 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/PeKMan/team7/eliza.html

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

18. Chatbot plus voice • http://www.daden.co.uk/chatbots/pages/000067.html • http://www.alicebot.org/

19. 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

21. 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

22. 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)

23. Semantic representations • Dialogue • Question: What do you want to eat? • Learner: I’d 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??

24. Desirable characteristics of speech interactive CALL • Wachowicz and Scott 1999 • Adopted by SPELL

25. 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

26. Observational scenario

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

28. One-to-one

29. 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

30. Interactive scenario

31. 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

32. 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

33. Interactive scenario • For each stage, there are assumed to be four types of response

34. Recasts

35. Recognition Grammar

36. Help for the learner -- reformulation

37. Error analysis • Errors for each learner are logged

38. Prototype system • Technical developments -- speech recognition of pronunciation • Students want more “affective” behaviour from the visual agents • (Eliza effect)

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

40. Active Worlds

41. MOOs, Avatars,CMC • Where is the learning? • Issues?