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Desire2Learn Advanced Learning Analytics Ronald Mol Desire2Learn

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Presentation on theme: "Desire2Learn Advanced Learning Analytics Ronald Mol Desire2Learn"— Presentation transcript:

1 Desire2Learn Advanced Learning Analytics Ronald Mol Desire2Learn

2 Learning Analytics

3 What is it?

4 Why is it important?

5 Demonstration

6 a holistic, analytical view of student academic progress, including risk Student Success System

7 a “flight plan” for navigating and selecting courses in a program Degree Compass

8 Advanced Learning Analytics D2L Differentiator Big Data Data Mining Algorithms Advanced Visualizations “Less Data, More Insights”

9 Why Learning Analytics?

10 Sir Kenneth Robinson Author, Educator, and Advisor

11

12 The aim of Learning Analytics is to personalize learning and, therefore, to transform teaching and learning.

13 Three Types of Analytics

14 Learning Analytics focus is the individual student or learner

15 Academic Analytics focus is the institution, program, department, and course

16 Enterprise Analytics focus is the entire enterprise and includes all systems and data with IBM

17 Less Data, More Insights Product Overview

18 R3 Reporting S3 Next-Generation Learning Analytics D3 Enterprise Data Warehouse + + = Analytics Reporting = Student Success System

19 Big Data “Only education analytics solution built on an top of a scalable, enterprise-class data warehouse” D3 Enterprise Data Warehouse one-stop shop repository for all assessment & learning data comprehensive data-domains for tracking all aspects of learning massively scalable to billions of records data pledge ”all your data is yours forever”

20 Deep Learning Insights “Recipient of Brandon Hall Group’s Gold Medal for technology innovation.” R3 Analytics Advanced Reporting hierarchical views for viewing data dynamically at multiple levels historical data for trend and comparative analysis advanced statistics for going beyond data to insights access controls for sharing data based on role authorization

21 Next-Generation Learning Analytics open architecture S3 Student Success System customized predictive models for early intervention advanced visualizations for diagnosis and deep insights case management for personalized referrals and 360 student view for flexible enterprise integration

22 Predictive Modeling Engine Predictive Modeling Engine Packaged Analytics Applications Visualization Layer Packaged Analytics Data Services Custom Analytics Applications Custom Analytics Applications WebWeb MobileMobile Database API Access Layer Data Domain Layer Statistics Layer Extraction, Transformation & Loading (ETL) Transactional Data Sources D2L Analytics Data Warehouse EnrollmentEnrollment Course Access Content Access Tool Access AssessmentsAssessments Learning Outcomes RubricsRubrics Internet Usage Curriculum Mapping CompetenciesCompetencies D2L Analytics High-Level Architecture Devices

23 Three Levels of Analytics (Maturity)

24 insight information value what happened? past predicted future what will happen? desired future how i want things to be Analytics Maturity Levels present what is happening now?

25 current state desired future optimal path

26 Analytics is finding an optimal to a desired future

27 Demonstration

28 a holistic, analytical view of student academic progress, including risk Student Success System

29 a “flight plan” for navigating and selecting courses in a program Degree Compass

30 Which courses in my program are optimal? Which program(s) or major is optimal? Which career(s) is optimal? (in development) Navigation

31

32 Global centrality Major centrality Grade prediction What ingredients go into the ratings?

33

34 Thank You


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