DiscoveringCollaborative Patterns

in eLearning fromMeta-code Subsequence

Name: Yip Chi KinDate: 15-01-2005

Motivation

․Collaborative eLearning․Machine Learning Assess․Temporal Data Mining․Generalization Usage

eLearning․Learning Style & Model․Collaborative activity․Courseware․Technology․Assessment

Temporal Data

․Asynchronousness․Irregularity․Huge Volume․Streaming Data․Distributed analysis․Heterogeneous data types

SynchronousDataset

Temporal MiningThreshold selection Frequency Analysis Anomaly Detection

Prediction Correlation Regression BenchmarkingCausality Analysis Periodic Pattern MiningSequential Event PatternsTemporal Association FindingClustering and Classification

Bioinformaticsapproach

Tracking Techniques․Full Screen HyperCard

․Click tracking of user․Timeout timestamp․Referrer timestamp․Full-loaded timestamp․Machine hanging․Diminish / Enlarge Platform Window․Delay capture session code

Temporal Timestamp

Event ID User ID Timestamp From Referrer

22345 101 20030620160000 S21 t12

22346 66 20030620160008 PLI ipi

22347 101 20030620160010 T12 cmi

S21, t12, … are HTML page codesipi, cmi, … are communicative sessions

Temporal Grouping

ID User ID Timestamp Group_id

223 101 20030620160000 21

224 66 20030620160008 35

225 101 20030620160010 42

Members could be join to another groupAnytime in the eLearning Platform

Data Cleaning

․Hacking Problem․Graphics Learning․Session Errors․Double Clicks

s = Number of students, where 1 s 163 t = Timestamp c = Pagecode

Duration(Page)= Starting Timestamp(Page) Ending Timestamp(Page) = St Et = Dt = Duration of each page

․Fuzzy rule:

Duration

Browse weight Bc = s ( c Dt )

if Dt 1 second then Dt = 0

s = Number of students, where 1 s 163 t = Timestamp c = Pagecode

Ps = Frequency(Page) of each student

fc = s Ps = Total frequence of page

․Fuzzy rule:if Dt 3 seconds then fc = fc + 1

Frequency

where

Weighting

Bc is Duration of Page Code

fc is Frequency of Page Codec is Linguistic variable of each Events

where

Navigation of Page

c

ccc f

BαX

Navigation Pages Statistics

Raw Browsing data After Logarithm

Normalization

․Unique Interval

Normalization of Page Code ( 0 wn 1 )

where xn is source value and wn is weight value

maxx macima and minx minima for all data

xx

xnn

xw

minmax

min)log(

Events CodingA = ConceptsB = IndividualC = CollaborationD = TechniqueE = eLearningX = Idle Time

Theory, Courseware

Video, Skill

Information Granules

․Linguistic variables․Fuzzy Reasoning․Interval Valued․Super Subsequence

Meta-Code

Code about code

MetaCodeInformation Granulation

Events Code

Interval Valued

Linguistic variables

Fuzzy Rules

Tri-event pattern

Discretization

Timestamp

Time Partitioning

TemporalDatabase Fuzzy Rules

Code Sequence

Temporal Reasoning

Granular Computing

Event Weight

Frequency & Time

Fuzzy Rules

…BC D C B A A C

Linguistic Variables

Contiguous Sequence

Collaborative Window

Communication Window

AD D D A A A AAB B A A A A X AX X X X A A A

BA D B B A D DAD C A A B B B AB D D A A C C

AA A A A A A ACA A A A X A A DA A A D D D D

BC D D D B B BBD D A A A A B AB B A A C C C

DC C D D C C CXC B A A X X A BA A C C B B B ……………

Group Size

Mutual event window size

Individual Personalization Profile

Member #4

Member #2

Member #3

Collaborative LinkIncreasing weights from collaborative links

n is Numbers of LinksW is weight of events

Sc = ncWc

Synchronous Communication

where

Member #1

Member #5

Synchronous Communication

Syne = Sc

e is eventsc is member of group

where

Synchronous Weight

Asynchronous Communication

Asyne = Ac

c

ccc n

WWA

Communication

W is weight of eventsn is Numbers of Asynchronous Communications

where

Asynchronous Weight

Capture Windows

One day period 86400 sec

Effective communications100000 to 1400000 sec

Study period subsequence 6480000 sec

Minimum weighting&

Maximum weighting

Capture direction

Points of Weight = (Asyne + Syne)

Minimum Windowing

0

2

4

6

8

10

12

14

16

18

20

100000 300000 500000 700000 900000 1100000 1300000

G roup 1

G roup 2

G roup 3

G roup 4

Maximum Windowing

0

2

4

6

8

10

12

14

16

18

20

100000 300000 500000 700000 900000 1100000 1300000

G ro u p 1G ro u p 2G ro u p 3G ro u p 4

Result Applications

Coursework (#5) studying period should be more than 6 days

Range of Collaboration benchmark is 77920 to 176497 points of weight

Necessary communication period is 4 days

• Curriculum Planning

• Collaborative Assessment

• Effective Communication

Project Enhancement․Huge Volume Implementation

(Apply special algorithms)

․Rewrite C++ Programs (Generalization Usage)

․Data Organization (One day Members = 86400 163) Vis․ualization of Patterns

MetaCode ModelingTime interval = 1 second , weblog duration = 75 days , Code length of Personalization Profile = n = 75246060 = 6480000

n

… BA A A B D D DBA A B B D C A CA A A C C C A

… A B DCA B D A C A

MetaCode Events SubSequence

MetaCode SubSequence

Tri-event PatternMutual relationships of tri-event pattern in sub-sequence

․Comparison of good/bad tri-event patterns․Frequent sequential pattern finding (tri-event)․Longest common subsequence․Super Subsequence․Sequential events prediction․Sequence reconstruction․Viterbi algorithm (hamming distance + Transformational grammar )

Super Subsequenceset of tri-event: {000, 001, 010, 011, 100, 101, 110, 111}

concatenationSuper Subsequence

: 000 001 010 011 100 101 110 111

Super Subsequence 0001110100

011000

001111 101

110010

100

Further Research

․Automata and Computability․Implementing Algorithms․Fuzzy Linguistic Associative Rules․Fuzzy Reasoning Partitioning․Subsequence Matching․MetaCode Grammar

Conclusions

․Assess Collaboration․Granular Modeling․Generalization Usage