Watch the video of this presentation: https://youtu.be/Qc9T5mj3oDc?t=1s
Data mining is a multi-industry trend that looks certain to grow in both scope and application.
It offers a hugely powerful means of identifying aggregates and trends at all levels, which is why we’ve worked extensively on deepening our analytics APIs over the last year.
This session will walk you through the latest advancements to our analytics and show you how we can make your data more valuable and how we handle the heavy lifting to make it easier for you to create complex reports at individual, class, school, or district level.
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Educate 2017: Mining for Gold: Using advanced analytics to get more value from your data
1. Mining for Gold:
Using reporting and analytics to get
more value from your data
2:20 – 3:00pm
Michael & Denis
2. Michael Sharman
Director of Product & Engineering
michael.sharman@learnosity.com
Denis Hoctor
Director of Product & Business Intelligence
denis.hoctor@learnosity.com
Presenters
3. 1. What sort of data we collect
2. Reporting
○ For students
○ For teachers
3. Extending reports
4. Analysis
○ Aggregate reports
Outline
4. ● Make your data more valuable for you
● Make complex reporting easy
● Provide analysis tools
● Handle the heavy lifting
Goals
7. Data collection
Responses
● Question data
● Responses
● Attempted
Session
● No personally identifiable
information
● Number of questions / attempted
● Status (completed or not)
● Date started / completed
● Activity id
● Session id
● User id
8. Data collection
Metadata
● Time per item
● Student flagged
● User agent
● Bank / pool source
● Custom
Scores
● Session, question and item scores
● Auto scored data
● Manually scored data
● Subscore data
9. Data collection → reporting
Data warehouse Reporting
Sessions
Responses
Scores
Metadata
10. ● Series of widgets customers can combine in any way
○ Student
○ Teacher
○ District administrators
● Configurable
● Extendable
Reports API
29. Data collection → reporting
Data warehouse Reporting
Sessions
Responses
Scores
Metadata
30. Data collection → analysis → reporting
Data warehouse ReportingAnalysis Engine
31. Use cases
● Policy makers, district administrators analysing education data
● Principals or teachers looking to understand class performance
● Anyone authorized to see statistical analysis across a cohort
Aggregate reports
32. Aggregate reports
● Visually summarize, explore and compare the assessment
results for large cohorts of students (up to 200,000)
● Compare mean, median and other statistical measures
● Precomputed, point-in-time snapshot of scores
● Arbitrary groupings of users that you define
● Browse and navigate through the group hierarchy
35. Northern District
Springfield High
School B
School C
Class B
Class C
Schools
Classes
District C
Schools
Classes
District B
Aggregate Report
(group hierarchy)
Ms Hoover
40. Aggregate reports
● State
● District
● School
● Class
● Cultural factors
● Rural suburban urban
● Socio economic
● Attendance
● Dyslexic
● School type
● Special needs program
● Family factors
Example groups / hierarchies
42. Aggregate reports - Summary
● Completely customizable
● Access to all the raw data
● Processed asynchronously (precomputed)
● Preserves your privacy and security
● Extensible in powerful ways
45. Analytics
Item bank analysis
● Break down of banks
○ Question types
○ Configurations (single vs multi select MC)
○ Items by tag
■ Eg ELA vs Math
■ Standards
■ DOK
46. Analytics
Item score analysis
● Cohort / time based classical item analysis
● Help check item reliability and validity
○ Relationship of item scores to test scores
■ P-Value
■ Point biserial
47. Analytics - Item bank
Items with bad
validation
Lack of easy
items in this bank