학습분석을 위한 참조모델과...

학습 분석을 위한 참조모델과 시스템 요구사항 정의

한국교육학술정보원조용상 , Ph.D

[email protected]: /zzosang Twitter: @zzosang

2016 년 한국교육정보학회 동계 학술대회(2016. 1. 14)

DataCollection

Data Storing & Processing

Visualization Analyzing

PrivacyPolicy

• lecture (MOOCs, OER)• material (reading etc)• learning tool• quiz/assessment• discussion forum• message• social network• homework• prior credit• achievement• system log ……

personalization,intervention andprediction, etc

Input data items for learning analytics

Outcomes from learning analytics

Data processing and analysis

secured data exchange

Learning & Teaching Activity

•Reading•Lectures •Quiz•Projects•Homework•Media•Tutoring•Research•Assessment•Collaboration•Annotation•Gaming•Social Network•Messaging•Scheduling•Discussion

참조 모델 Reference Architecture

<source: ISO/IEC 20748-1 Learning analytics interoperability – Part 1: Reference model>

데이터 수집 Data Collection

• lecture (MOOCs, OER)• material (reading etc)• learning tool• quiz/assessment• discussion forum• message• social network• homework• prior credit• achievement• system log ……

learning & teachingactivity

III-02. PersonalData Control

III-05.Identification

IV-01. Accessibility Preferences

III-01. Data Flow and Exchange(i.e. xAPI and IMS Caliper)

Data C

ollection API

Temporary Data Store(Event Store)

Data C

ollection Instance secured data transmission

III-04. Data Utilization

conformance testing

I-01. Learning ActivityI-04. Social NetworksII-01 & II-02 Assessment


데이터 저장 및 처리 Data Storing & Processing

Temporary Data Store(Event Store)

Analytics Data Store(Micro Data)

Data Translator and Filter

Data Q

uery

Unified Data Translator

(i.e. to LOD)

Data Filter

Filtering Conditions

TranslationRules

NaturalLanguage

Processing

Data M

igration I-05. Discourse Analytics

III-01. Data Flow and Exchange(i.e. xAPI and IMS Caliper)

III-05. Identity Protection & Identification


데이터 분석 Data Analysis

Analytics Data Store(Micro Data)

Analytics Data Store(Analyzed Data)

Data M

anipulation Data Analysis

Analysis Interface

(i.e. R)

Analysis Algorithm

Analysis Processing

Output Generation

Statistic Analysis

Topic Analysis

Network Analysis

Pattern Analysis

Dynamic Modeling

Association Analysis

Constant Information(Curricula, Learning Resources,

Preferences)

Privacy Masking

Dashboard Integration

Content Recommendation

Learning Path Recommendation(Curriculum Support)Social Analysis

III-05. Identity Protection & Identification

I-01 to I-05. Log, Predictive, Adaptive, Social and Discourse AnalyticsII-01 & II-02. Assessment using ICTIII-03. ePortfolioIV-01 to IV-03. Accessibility Matching

I-02. Predictive AnalyticsI-03. Adaptive AnalyticsI-05. Discourse AnalyticsII-01. Assessment using ICT


시각화 Visualization

Analytics Data Store(Analyzed Data)

Data Q

uery

Dashboard and Reporting System

DO

M Interface

Data Interpretation to Visualization

personalization,intervention andprediction, etc

DashboardInformation ePortfolio Learning Path

& Resources

IV-01 to IV-03. Accessibility MatchingI-01. Dashboard ServiceI-02. Predictive AnalyticsI-04. Social Analytics

III-03. ePortfolio

I-03. Adaptive AnalyticsII-01 & II-02. Assessment using ICT


1. Session Event – 로그인 (Readium JS 뷰어 ) - JSON Data- Figure

1

2. Navigation Event – 페이지 내비게이션 - JSON Data

- Actions

- Figure

Readium Viewer 다음 페이지 이동

1

3. Annotation Event – 하이라이트 ( 사용자 주석 )텍스트 드래그하여 하이라이트 버튼으로 마킹

1

2

( 참고 ) 전송되는 Annotation Event 데이터 캡쳐 화면 (J-SON)

4. Annotation Event – 북마크 ( 사용자 주석 )북마크 할 위치의 텍스트를 드래그한 후 북마크 버튼 클릭

2

3 1

( 참고 ) 전송되는 Annotation Event 데이터 캡쳐 화면 (J-SON)

5. Session Event – 로그 아웃 (Readium JS 뷰어 )- JSON Data

LMS 사용자 로그아웃1

6. 실시간 분석 결과 – 대시보드 ( 분석 플랫폼 )

감사합니다 !!!Thanks you !!!

Korea Education & Research Information ServiceYong-Sang CHO, [email protected]: /zzosang Twitter: @zzosang

학습분석을 위한 참조모델과...

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