Transcript
Page 1: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Agent-Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Punyanuch Borwarnginn5 August 2013

Page 2: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Outline•Virtual Learning Environments•Problems•Baseline capturing (Survey results)• Proposed solution• Intelligent Learning Environment•Evaluation•Plan

Page 3: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Virtual Learning Environments▫Web-based learning environments▫Support classroom learning▫Self-learning

•Examples▫Blackboard WebCT▫Moodle

Page 4: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

ProblemsVLEs usually• lack of assistive feedbacks.• lack of providing personalisation and

adaptivity. • lack of supporting collaborative tasks.• itself is not an automated system.

How do we improve VLEs to support these issues?

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Baseline CapturingSurvey Results

Page 6: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Purposes•To understand a students' behaviour and a

classroom style. •To capture current uses of an online learning

environments that students use in their learning.

•To evaluate the satisfaction of the current use in an online learning environments.

•To be able to use these data as orientation data for establishing issues and requirements of the project.

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Data collection•Questionnaire •Faculty of Information and Communication

Technology, Mahidol University, Thailand▫11 Lecturers (44%)▫283 1st-3rd Undergraduates

valid answers : 277 (40.67%)

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What kind of learning could best describe the students’ learning behavior?

50%49%

1%

Individual LearningCollaborative LearningMixed

18%

64%

18%

Students LecturersN= 272 ,No answer = 5

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Which style of classroom could describe your class? 9%

18%

73%

51%45%

4%

Student-centeredTeacher-centeredMixed

Students Lecturers

N= 274 ,No answer = 3

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Have you experienced any issues or problems according to this learning behavior and classroom styles?

0102030405060708090

53.68

32.35

54.78 59.93

1.84

72.73

45.45

81.82

27.27

54.55

StudentsLecturers%

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More detailsLecturers 'views• Not all students were interested in the activities.• Students pay no attention.Students’ views• The attention span of students is in general quite short• Sometimes students want to know why we should learn this

subject and If we study well in this subject what can we use benefit (useful) from this.

• Students did not participate with teacher as it should be.• Lack of resources for teaching.• Some subjects have many lessons and very board then we

want some activities for making we active to learn. • Some subjects are difficult to explain in lectures. Other

learning activities could make them easier.• Students have different backgrounds, profiles, learning

styles and knowledge about their subjects.

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Have you ever used learning management systems (LMS), virtual learning environments (VLE), e-learning systems or course websites?•Lectures▫100% Yes

•Students▫89% Yes (247)▫11% No (30)

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Frequency of use in different features (Students)

Downlo

ad cou

rse m

ateria

ls

Check

cours

e ann

ounce

ment

Submit a

ssign

ment

Take q

uiz

Discuss

ion Fo

rum

Chat

room Wiki

Questi

onnai

re0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

43.0328.28

49.59

18.413.78 4.55

14.888.33

43.03

36.48

25

13.81

9.24 6.2

15.719.58

1.64

4.92

9.02

20.92

18.4915.29

9.525.42

11.89

27.4612.3

23.01

26.89

9.5

23.97

28.33

0.41 2.87 4.1

23.85

41.6

64.46

35.95

18.33

NeverSeldomOccasionallyFrequentlyAlways

Page 14: Agent - Based Architecture for Intelligence and Collaboration in Virtual Learning Environments

Frequency of use in different features (Lecturers)

Upload course mate-

rials

Create course announce-ment

Setup as-signments

Setup quizzes Discussion Forum

Chat room Wiki Ques-tionnaire

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

90.91

18.18

36.36

0 0 0 0 0

9.09

27.270

0 0 0 0 0

0

27.2736.36

36.3627.27

09.09

27.27

0

18.18 18.18

0

0

0

0

18.18

09.09 9.09

63.6472.73

10090.91

54.55

NeverSeldomOcca-sionallyFrequentlyAlways

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Features RankingLectures1. Upload course materials2. Setup assignment 3. Create course

announcement 4. Questionnaire5. Setup quizzes 6. Discussion Forum7. Wiki 8. Chat room

Students1. Download course

materials2. Submit assignment 3. Check course

announcement 4. Questionnaire 5. Take quiz 6. Wiki 7. Discussion Forum 8. Chat room

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I am satisfied with the current system that I am using.

Agree Neutral Disagree0

10

20

30

40

50

60

70

80

36.67

60.42

2.920

72.73

27.27

StudentsLecturers%

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Suggested ImprovementsLecturers’ views• Interactive lesson that allows teachers to

incorporate formative assessments into course materials.

• Dynamic web modules for observing student assignments, performances, and easing up grading processes.

• More interactive features • Better User Interface • Pool of videos (may be imported from Youtube)

categorized by its subjects with a search 'feature' • Multiple templates of Quiz and Scoring systems

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Suggested ImprovementsStudents’ views• More functions for supporting collaborative

tasks such as group projects. • Video Lectures • More social network integrations • Search engine • More contents and activities in Wiki and Forum

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Proposed SolutionHypothesisIntegrating well-designed agent-based systems can enrich the intelligence responses (adaptivity, personalisation and task monitoring) during the learning process in the virtual learning environment that lead to the better learning experience.

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Proposed SolutionOutcomeAgent-Based Architecture for Intelligence and Collaboration in Virtual Learning Environments called “Intelligent Learning Environment” (I-LE)

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Intelligent Learning Environment

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Objective•To introduce an agent-based system into a

Virtual Learning Environment •To personalise and adapt learning

materials and activities based on students’ profiles and preferences.

•To observe students’ assignments, group progresses and their performances.

•To assist teachers when it needs their attention.

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Intelligent Learning Environment

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Aims

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Agents• Profile Agent▫ Collect and Update student data ▫ IMS Learner Information Package

• Student Agent▫ Recommend a student to perform activities ▫ Suggest students to learning resources

• Activity Monitor Agent▫ Monitor student activities by using state changes

Student A has created a report B hasCreated(StudentA, ReportB) Report B is reviewed by student C isReviewed(ReportB, StudentC)

• Teacher Agent▫ Notify teachers about students progress▫ Notify teachers when to review and mark assignment

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Overview of I-LE

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Experimental Design •Phase I: Baseline capturing •Phase II: Pre-experiment •Phase III: Post-experiment

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Evaluation•Deploy in a real learning environment▫Comparing their learning experience with

the current virtual learning environment▫Undergraduates in Thailand ▫Interview and survey

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Plan

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Thank you

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Questions•How to deal with evaluation using a real

environment?•Are there any suggestions on a student

model?


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