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The Learning Analytics Collaborative
Monthly Newsletter
October 2020
Dear LAC Members,

Welcome to our October LAC Newsletter! We have had a very busy month behind us - new initiatives launched, new schools joining the LAC, and all schools starting a new academic year. A big Thank You for engaging with our LAC family; we are receiving a number of enquiries about the SEL engine, Class Placement engine, as well as great feedback that will help us pave the way for future enhancements. While we are working hard to implement the changes already underway such as new interface and legends for our engines, the new initiatives are helping us expand our LAC ecosystem and stay relevant in the ever-changing educational landscape. We look forward to sharing more information about these initiatives in future newsletters. 

I was very pleased with our second Virtual Meetup on September 26th. We had a great turnout with over 30 participants across our 3 sessions. We want to acknowledge again our amazing speakers: Jonathan Semdes from International School of Phnom Penh and Andrew Blair from Zurich International School as well as all participants that have contributed to the event! Many new connections have been made and this is what this Collaborative is all about! More on the event in the section below. 

I am also delighted to welcome the International School of Dongguan and The American International School of Vilnius to the LAC family. The schools have just joined us and are beginning their journey to implement the platform at their schools.

All the best and stay safe!

Piotr Olczak
Director of Learning Analytics
Consilience Education Foundation
2nd Virtual Meetup
The event has not only given us the opportunity to showcase best use cases from our LAC family but has allowed LAC members to connect with and learn from each other. The next event will take place in January 2021. All resources from the Virtual Meetups including the recordings can be accessed via the LAC Online Learning Center. The three sessions on the 2nd Virtual Meetup featured: 
  • Leveraging High Quality Data Visualization for Better Insights - Student Data Explorer (LAC)
  • Functionality and use cases of the Student Data Explorer engine, how to sort, compare and cluster student achievement data
  • Finding correlations between student data points and drilling down to individual student performance
  • How to access all relevant resources from LAC (LAC Manual and LAC Online Learning Center)
  • Playing with Data - ISSP’s journey with the Learning Analytics Collaborative (ISPP)
  • Embedding a culture of data informed decision making
  • Walking through data to uncover questions
  • Establishing protocols for Analysing Data 
  • Lessons learned and way forward
  • Establishing Foundations for the Improved Use of Student Data (ZIS)
  • The importance of maintaining data integrity and data governance 
  • The challenges of building robust data sources and creating impactful visualisations
  • Creating case studies and use cases to promote data literacy and consumption 
MAP Screener - Name change. Welcome MAP Scanner!
In response to feedback from our members, we are changing the name of one of the most popular engines - the MAP Screener. This engine provides analysis of growth and achievement of students in a cohort based on core MAP data that schools receive from NWEA. The name, however, has been a source of some confusion suggesting it is only used to analyse MAP screener data (short version of MAP test often used for admission purposes). In order to address this confusion, we will change the name to MAP Scanner. We will include the old name in parenthesis for a while, to allow for a smooth transition. The functionality and features of the engine remain unchanged.
Engine of the Month - ACER ISA
This month we are showcasing the family of 3 engines developed to analyse ACER International Student Assessment (ISA) data:
  • ACER ISA Data Explorer visualises key student level and question level metrics for all candidates across grade levels and strands for one testing period.
  • ACER ISA Longitudinal data looks at grade level aggregate trends for year-on-year results
  • ACER ISA Cohorts and Comparisons focuses on tracking cohort level performance over time, allowing schools to view key statistics for selected groups of students and benchmark them against other schools.
If you would like to find out more about this engine you can watch the video about the ISA engine in the LAC Online Learning Center. If you would like to implement it in your school’s LAC site, please contact Piotr.
SEL Engine/Dashboard
Last month we announced we are working on an SEL Engine that would allow schools to monitor students' social-emotional learning specifically around measuring students’ relationships and networks. A working prototype will be ready soon. We are looking forward to hosting a webinar to showcase the functionality and potential use cases of this engine. We are also planning to build a family of SEL engines and an SEL Dashboard that will host all these engines. We are looking forward to working with those schools that may be interested in measuring SEL. If you are interested in a conversation about the first engine that will be rolled out soon, please email [email protected]
Parents and Access to their Child's Learning Data
The Data Quality Campaign (DQC) conducted an online survey in the US in 2015 among 1,093 parents of child(ren) aged 5–17. These were some of the findings that were shared in this summary report - http://bit.ly/DCQparentsurvey

  • Parents use a variety of data for various purposes, including to determine school quality. While most parents receive information from their child’s school about academic progress (93 percent) and when they need extra help (78 percent), the kind of data parents want varies based on what level of information they already receive. 
  • Parents are also interested in different types of data — Over 90% of the parents were at least somewhat interested in receiving information about their child’s social-emotional learning and and more than half (55 percent) are very interested.
  • Parents say they need data, like grades and test scores, to understand their child’s progress so they can help them do their best.
  • 93 percent of parents who receive information from their child’s teachers think it is at least somewhat easy to understand.

“When information about students is provided in a timely, useful manner, every adult working with a child—especially parents—is able to support that student’s learning more effectively. Understanding parent attitudes around data use is the first step... (that schools) can take to ensure that their efforts really meet parents’ needs.”

If you are interested in a conversation to explore the possibility of providing parents access to their child’s visualized learning data, please complete this form.

Data Literacy - Building a Culture of Data Use

By adding Angela Duckworth's 12-item grit scale to the standard assessments, one school is investigating the possibility of measuring and teaching its students grit.

Schools already use a lot of data - from ERB scores and PSAT, ACT, and SAT information to AP exam results - to help shape and focus instruction each year. However, this data provides a glimpse into a few facets of students who are complex young men and women.
Useful Links
Consilience is a non-profit, global education innovation company that supports institutions and educators to transform teaching and learning. We provide leadership training and professional development in the areas of Innovation Leadership, Technology Integration, Maker Learning, Online Learning and Learning Analytics. For more information about our work, please visit our website: www.consiliencelearning.org 
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