iReflectiReflectReflection in Web2.0 Style

Green TalkGreen Talk

Martin HomikMartin Homik

MotivationMotivation

Different (Meta-) cognitive prompting schemas:Different (Meta-) cognitive prompting schemas: Renkl, Schwonke; B. WoodwardRenkl, Schwonke; B. Woodward No common schema; no semantic model???No common schema; no semantic model???

Learning Diaries used in closed environmentsLearning Diaries used in closed environments Open up!!! Use anytime and anywhere! Open up!!! Use anytime and anywhere! Get independentGet independent Get a larger audience! Get more data!Get a larger audience! Get more data!

This is how many Web2.0 applications workThis is how many Web2.0 applications work Focus on and offer specific functions/servicesFocus on and offer specific functions/services Flickr; YouTube; ClipMarks; SlideShare; Google; DeliciousFlickr; YouTube; ClipMarks; SlideShare; Google; Delicious

Cognitive PromptsCognitive Prompts

Organisation.Organisation. What is the story line of the talk? What is the story line of the talk? Describe the motivation, the goals, and the path Describe the motivation, the goals, and the path to the goals.to the goals.

Elaboration. Elaboration. Make up own examples, counter Make up own examples, counter examples or illustrations. Did you come across examples or illustrations. Did you come across the presented techniques in a different context? the presented techniques in a different context? If yes, where?If yes, where?

Critical Reflection.Critical Reflection. What did you find What did you find interesting, useful, convincing, inspiring? Is there interesting, useful, convincing, inspiring? Is there anything you criticise?anything you criticise?

Metacognitive PromptsMetacognitive Prompts

Monitoring.Monitoring. What did you not understand about What did you not understand about the talk?the talk?

Self-diagnosis.Self-diagnosis. What is the likely reason? What is the likely reason? Self-regulation.Self-regulation. How would you overcome your How would you overcome your

deficiency?deficiency?

A Structure/ModelA Structure/ModelPrompt

Organi-sation

CognitiveMeta-

Cognitive

ElaborationCritical

ReflectionRegulationMonitoring Diagnosis

QQ Q QQQ QQ Q

QQQ QQ Q

Problems:1. How to distinguish prompts?2. Can’t use all prompts at once3. More categories …

A Structure/ModelA Structure/ModelPrompt

Organi-sation

CognitiveMeta-

Cognitive

ElaborationCritical

ReflectionRegulationMonitoring Diagnosis

QQ Q QQQ

QQ QQQ

Q QQ Q

Problems:1. How to distinguish prompts?2. Can’t use all prompts at once3. More categories …

MMM

A Structure/ModelA Structure/ModelPrompt

Organi-sation

CognitiveMeta-

Cognitive

ElaborationCritical

ReflectionRegulationMonitoring Diagnosis

QQ Q QQQ

QQ QQQ

Q QQ Q

Problems:1. How to distinguish prompts?2. Can’t use all prompts at once3. More categories …

MMM

S

MMM

Web2.0 Design PatternsWeb2.0 Design Patterns

Article: Tim O’Reilly: Article: Tim O’Reilly: http://www.oreilly.com/lpt/a/6228http://www.oreilly.com/lpt/a/6228

1.1. The Long TailThe Long Tail

2.2. Data is the Next Intel InsideData is the Next Intel Inside

3.3. Users Add ValueUsers Add Value

4.4. Network Effects by DefaultNetwork Effects by Default

5.5. Some Rights Reserved. Some Rights Reserved.

6.6. The Perpetual BetaThe Perpetual Beta

7.7. Cooperate, Don't ControlCooperate, Don't Control

8.8. Software Above the Level of a Single DeviceSoftware Above the Level of a Single Device

ScenarioScenario

PromptsDB

Plattform

Let users contribute! • add prompts• create sets• annotate

ServiceLet users use! • press reflect button• store in database• share / RSS• send to blog• send via mail … • integrate (seamless; add context)• choose/assign prompt set

ReflectDB

Where is AI? Where is AI?

Semantic Knowledge Representation (Model)Semantic Knowledge Representation (Model) Data MiningData Mining

Analyse (set of) prompts Analyse (set of) prompts Preferences with respect to Metadata?Preferences with respect to Metadata? With respect to usage statisticsWith respect to usage statistics

Expert System for R.-Set suggestionsExpert System for R.-Set suggestions Based on Data Mining and KRBased on Data Mining and KR

NLPNLP

Comments are welcome!Comments are welcome!

DFG ProposalDFG Proposal

Publications on Learning DiariesPublications on Learning Diaries Publication on e-PortfolioPublication on e-Portfolio E-Portfolio StudyE-Portfolio Study ActiveMath (Loads of Publications)ActiveMath (Loads of Publications) Can add Schwonke, Renkl Can add Schwonke, Renkl

Research QuestionsResearch Questions

Model? What kind of Metadata;Model? What kind of Metadata; Context information and capturing;Context information and capturing; Enhance by Data Mining and AIEnhance by Data Mining and AI How to make reflection independent of a How to make reflection independent of a

particular environment and yet acquire and use particular environment and yet acquire and use all information …all information …

How to facilitate reuse and seamless How to facilitate reuse and seamless integration? Possibly as WebService.integration? Possibly as WebService.