1. Using Instant Messaging to Provide an Intelligent Learning Environment
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Using Instant Messaging to Provide an Intelligent Learning Environment
Chun-Hung Lu, Guey-Fa Chiou, Min-Yuh Day, Chorng-Shyong Ong, and Wen-Lian Hsu

2. Because I be required a endodontic yesterday.
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Because I be required a endodontic yesterday.
If my presentation is not clear, please let me know, or you can ask my colleague and co-author Day Min Yuh.

3. 140502LNZXD910GRPW-X1
Our Purpose
We provides students with on-line coaching in a total English learning environment by using AIML & Natural Language Processing technique.

4. teacher cannot interact with students anytime, anywhere.
140502LNZXD910GRPW-X1
teacher cannot interact with students anytime, anywhere.
Tutorbot
Teacher
Student A
Student B
Student C
Tutorbot like a learning companion of students

5. Psychological Reasons
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Psychological Reasons
People work harder to understand material when they feel they are in a conversation with a partner, rather than simply receiving information. An agent with learning capacity can grow with the student.
Pedagogical agents are onscreen characters that help guide the learning process during an e-learning episode.
Skill development and expertise are strongly related to the time and efficiency of deliberate practice. An “Instant Messaging” based agent can provide practice anytime, anywhere.
On-line learning is a collaborative endeavor in which participants learn by collaboration.

6. Ready reference material
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Architecture
TutorBot
Ready reference material
Dictionary
(Wordnet,
M-W online)
Course Dialog
(Business)
Idioms
archive Module
Regular Conversation
ClassifyBot
AIMLBot
Spell Check
Engine
Language Analysis
OpenNLP
Chunker
Similarity

7. User Input TutorBot RRMBot ClassifyBot AIMLBot Conversation UI Yes Yes
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User Input
TutorBot
Spell Check
English Environment
RRMBot
Check Right
Ready
reference materials
Yes
Conversation UI
Classify
Conversation
Yes
ClassifyBot
AIMLBot
AIML
Conversation
Yes

8. Ready Reference Materials
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Ready Reference Materials
Thanks to Overseas Radio & Television Inc. ( ) who provide us “Let’s Talk in English”, “Studio Classroom”, and “Advanced”.

9. RRMBot User Login Searching exist profile
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RRMBot
User Login
Searching exist profile
Ready reference materials Repository
Loading section content
Send text & link (voice) to user
Tutorbot’s response

10. ClassifyBot User Key-in sentence NP Chunker/ OpenNLP
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ClassifyBot
User Key-in sentence
NP Chunker/ OpenNLP
Computed RRM Similarity by using Wordnet
Get Top 5 candidates
Conversation achieve repository
Computed similarity of context
Tutorbot’s response

11. 140502LNZXD910GRPW-X1
ClassifyBot
Backend which provides corpus-based concordance analysis and grammar analysis.

12. Disneyland was very crowded.
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ClassifyBot
User Input
Oh, yes! Hong Kong
Disneyland was very crowded.
OpenNLP
chunk result: “[NP Hong/NNP Kong/NNP Disneyland/NNP ] [VP was/VBD very/RB crowded/VBN ] ./.”
NER
<location>Hong Kong</location> Disneyland
Using those information to find related topic

13. 140502LNZXD910GRPW-X1
AIMLBot
Why AIML?
Derivative of XML.
Adopted by the AI Foundation.
Does not incorporate dependencies upon any other language.
Small learning curve.
Simple yet extremely powerful for describing natural language conversation.
Using AIMLbot from
Adding 2 feature
Adding a spelling check engine
Making AIMLBot can process <li> tag

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ALICE System
ALICE: the Artificial Linguistic Internet Computer Entity; a software robot that you can chat with using natural language.
ALICE is composed of two parts:
Chatbot Engine
The language model
ALICE language model is stored in AIML files.
AIML: The Artificial Intelligence Mark up Language.

15. The AIML Format < aiml version=”1.0” >
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The AIML Format
< aiml version=”1.0” >
< topic name=” the topic” >
<category>
<pattern>Input</pattern>
<template>Output</template>
</category> ..
</topic>
</aiml>

16. AIMLBot AIMLBot User typing response Achieve All conversations
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AIMLBot
User side
User typing
response
Spelling Check Engine
Achieve All conversations
AIMLBot
AIML repository
User log file
NPAnalysis

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Backend
Login Screen
Backend Achieve System

18. User Case Scenario Student Login
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User Case Scenario
Student Login
Tutorbot need to dialogize student about 10 minute
Tutorbot give a suggested label to this student
RRM
beginner
intermediate
advanced

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Conclusion
TutorBot plays the role of “assistant instructor” to provide service anytime, anywhere.
Our contribution in this paper is that we use NLP Tool and AIML to integrate several language learning components (words, sentences, sounds, and meanings) in context with an instant messaging-based Chatbot for English as a Second Language programs.