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Mi bug grcc analytics presentation 2013
- 1. Getting Started with Blackboard Analytics for Learn Eric Kunnen Director, Distance Learning & Instructional Technologies
- 2. Big Picture & Big Data • “Analytics is the use of data, statistical and quantitative methods, and explanatory and predicative models to allow organizations and individuals to gain insights into and act on complex issues.” Retrieved from: http://www.educause.edu/ero/article/lets-talk-analytics Analytics & Big DataAnalytics & Big Data Business Intelligence / Academic Analytics Business Intelligence / Academic Analytics Learning AnalyticsLearning Analytics
- 3. 2013 Horizon Report – Big Data and Learning Analytics • Time-to-Adoption Horizon: Two to Three Years • “…learning analytics leverages student-related data to build better pedagogies, target at-risk student populations, and to assess whether programs designed to improve retention have been effective…” Retrieved from: http://www.nmc.org/publications/2013-horizon-report-higher-ed
- 7. Analytics Needs at GRCC Key Areas of Strategic Importance: •Access to Data!!! •Data Warehouse Initiative •Title III – College Success Program •Student Success and Completion Agenda •Early Alert, Student Risk Identification & Intervention, and Predictive Analysis •Professional Development & Course Quality •Measure Trends with SIS Demographics •Link Outcomes to Grades •Overall ROI
- 8. Analytics Implementation at GRCC Key Highlights: •Strategic Planning •Infrastructure Planning •Data Warehouse Architect Hired •Project Coordination •Installation •On Campus Implementation Team Training, Business Process, Validation, etc.
- 9. Analytics for Learn - Sample Student Reports
- 12. Analytics for Learn - Instructor Reports
- 17. Analytics for Learn Reports
- 21. Next Steps… • Dedicating Time (Learning the meaning of data, validating the data, generating dashboards, and asking the right questions.) • Building Capacity (Who can lead? Who needs what? What training is needed.) • Engaging the Culture (Asking good questions, building an understanding of the value of data, and how data could be misleading. Communicating around the “big brother” notion.) • Emerging Directions (Linking and using data in campus initiatives such as program review, accreditation, early alert, advising, etc.)
- 22. Additional Analytics Resources Learning Analytics 101 Infographic: http://www.opencolleges.edu.au/informed/learning-analytics-infographic/ EDUCAUSE resources: •Index: http://www.educause.edu/library/analytics •Sprint Resources http://tinyurl.com/learnanalytics •Building Organizational Capacity for Analytics: http://www.educause.edu/library/resources/building- organizational-capacity-analytics •Infographic: http://net.educause.edu/ir/library/pdf/ERS1207/eig1207.pdf Learning Analytics - Definitions, Processes and Potential: http://learninganalytics.net/LearningAnalyticsDefinitionsProcessesPotential.pdf
- 23. Thank You!
Hinweis der Redaktion
- Focus on 3 areas: About Analytics, Analytics @ GRCC, Next Steps
- So what is this session about? Analytics is the gathering and use of data to gain insight… “Big Data” is around massive use of data. Administrative functions and operational focus is where BI and AA come in. And finally the focus of this presentation will be on the information collected about students and faculty around their use of the course management system and the SIS around teaching and learning. Learning analytics as “the measurement , collection , analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.
- Why is Learning Analytics important? New Media Consortium and the EDUCAUSE Learning Initiative (3D printing, game-based learning, tablet computing, MOOCs…)
- Big data = the use of massive amounts of information – some call this “Retail Analytics”
- Our retail customers are students - Typically this is SIS systems, Purdue – Signals / Sherpa – South Orange CC / MOOCs – Stanford and Coursera, Starfish
- Focusing more on students and learning - SIS is typically the “data warehouse” for an institution with a missing piece of a large amount of data – within the lms. A4L brings this data and the SIS together.
- “ Uncollected data can’t be analyzed” -- 2007 Project ASTRO - Tool use, content use, course activity (instructors and students), find innovative instructors, report on requirements , make realtime decisions for what is happen ing rather than what happen ed …
- October Bb Analytics and March 2013 A4L
- Some sample reports…
- Retention Center (replace the early warning system - course centric with a student view coming) – last login is like going to class, activity is like being engaged, grades, due dates.
- Bb Analytics for Learn (campus wide with deep dive drill down, longitudinal trends (historical), slice and dice, SIS)