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ERIC Number: ED560880
Record Type: Non-Journal
Publication Date: 2015-Jun
Pages: 4
Abstractor: As Provided
Learning Analytics Platform, towards an Open Scalable Streaming Solution for Education
Lewkow, Nicholas; Zimmerman, Neil; Riedesel, Mark; Essa, Alfred
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)
Next generation digital learning environments require delivering "just-in-time feedback" to learners and those who support them. Unlike traditional business intelligence environments, streaming data requires resilient infrastructure that can move data at scale from heterogeneous data sources, process the data quickly for use across several data pipelines, and serve the data to a variety of applications. As a solution to this problem, we have designed and deployed into production the Learning Analytics Platform (LAP), which can ingest data from different education systems using standardized IMS Caliper events. The education events are triggered by student and instructor activity within Caliper instrumented learning systems. Once sent to the LAP, events are transformed and stored in a data store where they can be used for student, educator, and administrator visualizations as well as education driven analytics research. Two McGraw-Hill Education platforms, Connect, used for higher education, and Engrade, for K-12, are currently instrumented to send the LAP event data which in turn feeds visualizations for educational insight. Future plans for the LAP include collection of education event data from a wide variety of proprietary and open source education platforms, computational engines for predictive analytics, and an open API for third-party analytics using LAP data. [For complete proceedings, see ED560503.]
International Educational Data Mining Society. e-mail:; Web site:
Publication Type: Speeches/Meeting Papers; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education; Elementary Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: International Educational Data Mining Society