1. Alexandra Cristea Toshio Okamoto and Safia Belkada
Concept mapping for Subject Linking in a WWW Authoring Tool: MyEnglishTeacher: TeachersSite ANNIE 2000
Alexandra Cristea
Toshio Okamoto
and Safia Belkada
2019/4/7
AI Lab., Japan

2. Main research goals
free, adaptive, WWW, agent-based, long-distance teaching environment for academic English, for non-native English-speaking academician
=> 2 environments:
student learning environment+
teacher’s courseware design environment.
2019/4/7
AI Lab., Japan

3. Main system modules Story Editor Environment +display Teacher user
Expression DB
Link DB
- Graphics DB
- Video DB
- Story DB
- Audio DB
GlA
- general
student DB PA
- private
student DBs
...
Story Editor
Environment
+display
Teacher user
Learning
Environment
+display
Student user
2019/4/7
AI Lab., Japan

4. Hypotheses: authoring
many course authors, representing different teaching strategies, with different amounts of time to spend in designing the course, different attention to details
ultimate goal is to find the optimal learning path in this heterogeneous net course
system helps teaching in adding semantics
2019/4/7
AI Lab., Japan

5. Goals of authoring system
Low overhead
Great flexibility
To allow teachers to input as little or as much material as they want, within some reasonable limits
2019/4/7
AI Lab., Japan

6. Main solutions for course authoring
For easy re-usage => course building bricks
For adding flexibility & semantics =>
manual & automatic concept mapping
2019/4/7
AI Lab., Japan

7. course building bricks
2019/4/7
AI Lab., Japan

8. Texts smallest building block;
can have corresponding video/audio attached (of dialog, etc.)
attributes:
main text, a short title, keywords, explanation, patterns to learn, conclusion, and exercises
2019/4/7
AI Lab., Japan

9. Lessons One or more texts build a LESSON attributes (similar to text):
title, keywords, explanation, conclusion, combined exercises
2019/4/7
AI Lab., Japan

10. Exercises attributes:
title, keywords, patterns to test, explanation, conclusion
This structure allows connecting exercises to rsp. texts and lessons automatically, via relatedness computations
2019/4/7
AI Lab., Japan

11. Test Points
The teacher should mark TEST POINTS: a text/ lesson where it is necessary to pass a test in order to proceed (~ game theory).
if student wants to jump subjects => 1 test　= combination of tests from current level
if student fails => another test generated
2019/4/7
AI Lab., Japan

12. Course graph
2019/4/7
AI Lab., Japan

13. Priority and Relatedness Connections
Lesson
Text 1
Text 2
...
Text i
Text n
Lesson
Text 1
Text 2
...
Text i
Text n
Lesson
Text 1
Text 2
...
Text i
Text n 1
Priority
connections
Relatedness
connections w
Test point
Lesson
Text 1
Text 2
...
Text i
Text n
New Lesson
Text 1
Text 2
...
Text i
Text n 2
2019/4/7
AI Lab., Japan

14. Manual concept mapping
2019/4/7
AI Lab., Japan

15. Method1: Input of transversal links
Current concept ?
Keyword List:
concept 1, concept2, ….
Title List: title 1;
title 2;
- - -
2019/4/7
AI Lab., Japan

16. Concept mapping application
Linear courseware
as opposed to
Transversal courseware
2019/4/7
AI Lab., Japan

17. Method2: labeling links
subcategory:
Simple words
Listening to
words
Listening practice
more
focus
Change
focus
Listening to
sentences
Audio
material
2019/4/7
AI Lab., Japan

18. Student advice for ex. You can go from here to:
Listening practice
Listening to
words
subcategory:
Simple words
You can go from here to:
· Subcategory: simple words “listening to words”, or to
· “Audio material”, etc.
Audio
material
2019/4/7
AI Lab., Japan

19. Courseware Processing views
for easy overview + gradual processing in labeling+linking
=> partial views of whole graph, (bird)
1 concept + its “star”-links (all concepts currently linked to it). (fish)
non-linked concepts: “floating”-concepts
2019/4/7
AI Lab., Japan

20. Teacher’s responsibilities
only responsible to link own course to existing courses (priority links)
cannot link other teacher’s lessons
is free to link and label whatever subjects desired (relatedness links)
no compulsion to link all texts in the system
2019/4/7
AI Lab., Japan

21. Automatic concept mapping
2019/4/7
AI Lab., Japan

22. Subject relatedness weight computation
wA,B0= 1: teacher’s selection;
0.5: system’s generation;
0: rest;
} (1)
where:
wA,B>0: weight between subjects A and B;
if wA,B = 0, the relatedness connection disappears
2019/4/7
AI Lab., Japan

23. wA,B t+tconst =  wA,B t + f1(no. of times connection A,B activated) +
+ f2(no. of times connection A,B was accepted, when
proposed in relation to unknown subject)
+ f3(no. of times connection A,B was accepted, when
proposed in relation to query) +
+ f4(no. of times tests related to connection A,B were
solved satisfactorily or not) (2)
where:
(0,1): forgetting rate; f1~f4: linear functions;
t: time; tconst: period for weight updated
F1: activated by the user or by other users, depending if it is a weight in the global model or the personal one;
F4: can be positive or negative
tconst exists because: the weights are not updated at every move, otherwise computation becomes too time-consuming
2019/4/7
AI Lab., Japan

24. Conclusions
This paper presents a way of using concept mapping techniques (manual & automatic) and breaking of contents into highly structured, information rich pieces of low granularity, in order to support teachers in creating English language teaching
material
The application field of these techniques is larger, could be used not only for other language teaching materials, but also for other subjects (restricted only by the presentation power of the current system
version)
This research is just a part of a larger project for academic English teaching
2019/4/7
AI Lab., Japan

25. Other features of authoring env.
at 1st system entry, teacher user must register (next fig.)
for confidentiality, teacher user (like student user) must choose
pseudonym (username) +
password
( to access own profile + courses)
2019/4/7
AI Lab., Japan

26. 2019/4/7
AI Lab., Japan

27. 2019/4/7
AI Lab., Japan

28. 2019/4/7
AI Lab., Japan

29. The teachers can change the lesson input as many times as they desire.
next : selection menu for extra lesson formatting, correction, and viewing.
The teachers can change the lesson input as many times as they desire.
2019/4/7
AI Lab., Japan

30. 2019/4/7
AI Lab., Japan

31. All teachers can view each of the course items
All teachers can view each of the course items. However, modification is only allowed for the teacher who is the designer of that specific item.
2019/4/7
AI Lab., Japan

32. 2019/4/7
AI Lab., Japan

33. Teacher/student users and their private screens
2019/4/7
AI Lab., Japan