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Computer, Internet, and English Learning

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Title: Computer, Internet, and English Learning


1
Computer, Internet, and English Learning
  • Howard Hao-Jan Chen
  • Dept of English, NTNU
  • ???
  • hjchen_at_ntnu.edu.tw

2
Listening
  • International Web sites
  • Domestic web sites
  • Streaming Technologies
  • Real media
  • Windows media
  • QuickTime

3
Randal Davis ESL Cyber Listening Lab
4
CNN
5
VOA Special English
6
How to download VOA
  • The VOA files can be downloaded and put on the
    Moodle
  • Scripts available

7
Synchronized Audio and Texts at Taiwan Normal
University
8
Regular VOA
9
Pod cast CNN
10
NTNU Moodle Listening Courses
11
Audio/Video Files Available
  • Podcasts
  • CNN
  • VOA
  • PBS
  • ABC
  • Other kinds of Audio and Video via Podcast
  • How to use Juice? Or iTune

12
Listening Comprehension Test
  • Moodle offer options.
  • Or you can use Hotpotato
  • Upload and make link to the files

13
Tracking Learner Performance
14
Speaking Skills
  • Speech recognition programs (ASR)
  • From Europe
  • From US
  • From Microsoft
  • Computer mediated communication
  • Various formats---
  • Text. Voice. Video

15
An Conversation with TeLLmeMore pro
16
A.L.I.C.E. (Artificial Linguistic Internet
Computer Entity) by Dr. Richard Wallace
17
The log of conversation with ALICE
18
Talking bots AIML and TTS
19
http//140.122.73.1508080/candle/candle1.html
  • CANDLE Project FAQ

20
JoinNet Conferencing Server
21
The total scores assigned by MyET program
22
NTNU speech recognition System
23
NTNU Dept of English ASR Technologies
24
Listen and Repeat the Sentences
25
Conversation (Role Play)
26
Choose the Right Answer
27
Write and Say (exercises on demand)
28
Flash and Speech Recognition
29
Personal Learning Records
30
Checking Students Performances Demo of various
activities
31
Reading
  • Web Sites and Tools

32
Reading Web Sites
  • Online dictionaries
  • Self-access reading center at NTNU
  • Various News Web Site CNN, BBC, ABC, NBC, CBS,
    VOA, Taipeitimes, and many many others.

33
Click and Show Dictionary
  • Google toolbar
  • Dr. Eye online
  • Yahoo minipen
  • Moodle and reading management
  • And assign readings to students.

34
Online Reading/Vocabulary learning Center
  • Moodle can be used again.
  • Moodle in reading course and extensive reading
    and what they can do?

35
Text-to-Speech( speech synthesis)
  • THE TTS server at national Taiwan Normal
    University and how do students feel about this?

36
Writing Web Sites
  • The Numerous online handouts for writing
  • The various tools for second language writing
  • Concordancer
  • Bilingual Concordancers
  • Collocation tools in Taiwan
  • E-rater

37
Writing Sites and Tools
38
Hong-Kong University Online Handouts
39
Purdue University Writing Lab
40
Tools PC Concordancer and Web Concordancer (????)
41
Collocation Retrieval Tools
42
Outcomes
43
NTNU Collocation Tool
44
Outcomes for task
45
Perform the tasks
46
More Writing tools
  • The BNC system
  • The Gutenberg system
  • The Wikipedia

47
NTHU Bilingual Concordancer developed by Jason
Chang

48
NTNU bilingual search engines
49
Hong Kong news and Scripts
50
Automatic Scoring and E-raters
  • ETS Criterion
  • MyAccess

51
Automatic Feedback on Learners Writing- ETS
Criterion
52
Poor grammar Feedback
  • NTNU has developed good tool here and it can help
    students.
  • Rule-based
  • Statistic-based

53
The Needs to Providing Feedback on Second
Language Writing
  • Many ESL students want to improve their writing
    abilities.
  • SLA Researchers would suggest that learners would
    need more practices and corrective feedback.
  • However, who can provide them useful feedback on
    meaning and forms?

54
The Existing Grammar Checkers
  • Teachers are the best feedback providers.
  • However, so many essays to correct.
  • Microsoft grammar checker
  • How useful is this tool? How does it deal with
    various ESL errors?
  • General impressions from ESL/EFL learners it is
    NOT very useful.
  • The two new commercial packages Vantage MyAccess
    and ETS Criterion

55
Errors Marked by Criterion and Human Instructors
(Means)
  • Error Type Criterion Human Instructors
  • Verbs 0.47 0.84
  • Nouns 0.00 0.94
  • Articles 0.07 2.00
  • Word Choice
  • 0.11 2.32
  • Sentence Structure
  • 0.32 6.31

56
Rather Disappointing Results
  • The results revealed that Criterion experienced
    difficulties in detecting errors in all of the
    five categories.
  • Another program MyAccess has similar problems,
    though the general impression from review reports
    was that they can detect more errors.

57
Whats the Ngram (statistical) Checker?
  • The computer helps to calculate all the possible
    combinations of word strings (2-word and 3-word)
    in a very large native corpus. Language models
    building.
  • All these saved to a large database.
  • Then when students write and submit an essay to
    the ngram checker, the system can quickly detect
    the word strings that do not exist in the native
    corpus.

58
Ngram-based Checker advantages
  • The key idea is simple but powerful
  • No need to write rule
  • More robust in detecting errors.
  • Large and suitable corpus might make this very
    useful. (EST,30-million news)

59
The Procedure of Developing an Ngram Checker
(corpora and tools)
  • 1. Find suitable and large corpus (e.g BNC
    wikipedia, and Google)
  • 2. Extract the ngrams (NLP tools SRI tool )
  • 3. Build a large ngram database
  • 4. Develop and test different highlighting
    methods
  • 5. Highlight the possibly problematic ngrams in
    learners writing

60
Grammar Checker Online
  • The links
  • http//140.122.83.2504000/main (BNC)
  • http//140.122.83.250/search.php (Google)
  • http//140.122.83.245/ngram-check/ (BNC)
  • http//140.122.83.227/ngram-count/ (BNC)
  • The rule-based checker
  • http//140.122.83.1898080/wgrammar/default.asp

61
The Web Interface of Ngram Checker
62
A Simple Example
63
Evaluate the Checker Performances Any Standard
Way of Evaluating Checkers?
  • What kind of errors should be used to test the
    grammar checker?
  • Fair assessment- same set of sentences.
  • How many sentences?
  • Many different categories and errors
  • Lexical factors.
  • NLP researchers F-measure and precision and
    recall

64
Test with CLEC Corpus from China
  • The size of the Chinese learners of English
    Corpus.
  • 1 million error-tagged learner corpus.
  • With about 60 error types.
  • We decided to single out some sentences (10
    sentences) from the learner corpus and then throw
    them into our ngram checkers.

65
The Strengths and Limitations of NTNU Ngram
Checkers
  • Ngram is good at detecting errors in the local
    or adjacent domains. It can indeed find many
    errors in CLEC.
  • Spellings
  • Word forms
  • Verb phrases
  • Noun phrases
  • Adj phrases
  • Collocations

66
The Weakness of Ngram Checkers
  • It failed to catch the followings effectively
  • Tense errors
  • Conjuncts errors
  • Fragments
  • Pronoun errors
  • Preposition errors
  • The run on sentences
  • The missing words

67
How about comparing NTNU Checkers with Criterion
and Myaccess?
  • We would like to compare with Criterion and
    MyAccess. But this was difficult to get the
    outcomes from these packages.
  • The checkers were embedded in a large program.
  • The topics are assigned by the system
  • But we will do this later on when we have access
    to more data from these two tools.

68
Pre-service English Teachers Feedback
  • Microsoft Word is widely available for teachers
    and learners.
  • How about comparing with Microsoft Word?
  • 22 pre-service teachers prepared their own
    sentences (errors).
  • Results NTNU checkers do work better than
    Microsoft Word (21/22). It can detect more
    errors, but the ngram systems still highlight
    some strings incorrectly.

69
A Simple Example
70
How to provide effective feedback?
  • The function words and content words
  • Function words limited
  • We might be able to provide some rule-based
    generalizations
  • Some word choice problems.
  • Increase their life, receive their apology.
  • Content word Search Just the word

71
ESL Portals
  • CANDLE- NTHU
  • ESL Café
  • Hong-Kong Polyu
  • NTNU
  • NCNU
  • Others.

72
NTHU CANDLE
73
Powerful Tools Available
74
More Portals for ESL/EFL
  • ?? ?????????????
  • http//llrc.eng.ntnu.edu.tw
  • ?????? ???????
  • http//english.csie.ncnu.edu.tw/index.php
  • Hong Kong Polytechnic University
  • http//vlc.polyu.edu.hk
  • HKUST Self Access Centre
  • http//lc.ust.hk/sac/advice/V1.htm

75
2004 version of The Developments in the Future
  • More audio and video on demand with
    subtitles/speed control/summary
  • Interacting with a virtual partner or a real
    person via The Internet (speech recognition and
    CMC)
  • Reading Intelligent agent summarizing the main
    ideas for us
  • Writing better tools and corrective feedback on
    demand
  • Testing automatic generation of questions, and
    computer adaptive tests
  • Virtual Reality 3D

76
Moodle the most popular CMS
77
ICT4LT (information and communication
technologies for language teachers) Web Site
78
Fun Internet Movie Database
79
Movie Trailers and others
80
Games and The 3D Virtual Worlds
  • Talking about the LLT. Sims ????- about using the
    German version of Sims to learn German.
  • A new trend is that many universities and
    colleges moved their classrooms and campus to the
    virtual world.
  • The new world- Second life????.

81
Second Life
  • Show them some video files there.
  • Quite a few
  • Downloadable from Youtube
  • Several books and web sites for tutorials
  • http//www.associatedcontent.com/article/215721/to
    p_10_second_life_tutorial_videos.html

82
Texas State in Second Life
83
Texas State University
84
Meeting People on Second Life
85
Interactions with Other People
86
Virtual Classrooms
87
The Potentials of Second Life
  • 1. Use the existing resources
  • English village language lab
  • 2. Build new learning environment for specific
    learning needs _ How challenging is this?
  • 3. Build and design with a team.
  • How many teachers and developers should be
    involved?

88
The Potentials of Learning/Education Games
  • Traditionally, we think games are useless and
    irrelevant for learning
  • Playing games wasting precious time.
  • Perhaps the new generation might not believe
    that.
  • How we can make the Learning Process more
    Interesting and engaging

89
Hardware
  • Wireless tech WiMax
  • EEEPC
  • Smaller NB
  • Mobile device

90
More New Applications
  • The use of Google video
  • Youtube
  • Skype
  • More communicative tools-CMC
  • Face to face video calls
  • High quality TTS and ASR
  • Faster reading speed
  • Web-based Content-based English learning

91
Recommendations
  • Self-Access learning
  • Better English ability
  • Moodle as the major tool
  • Infuse various contents and tools
  • Are you ready?
  • Collect and Use good tools and good sites

92
Hands-on Sessions
  • Moodle accounts
  • How to download video and audio
  • How to use podcast?
  • speech recognition- log in
  • collocation tools- search tips
  • grammar checkers- allow learners to use
  • second life at home- virtual classrooms
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