Skip to main content

Using data to inform decision-making within the Student Support Team

LAC Case Study: International School of Phnom Penh

(This post is by Jonathan Smedes, Director of Learning, Teaching, Innovation and Impact at ISPP)

THE SCHOOL
The International School of Phnom Penh (ISPP) is an internationally accredited day school located in the capital city of Cambodia, Phnom Penh. The school hosts students from approximately 50 different nationalities and has a current enrollment of approximately 920 students from Early Years to Grade 12. Established in 1989, the school has grown from a small community school, servicing a few expatriate families, to a beacon school in the region, attracting students from all over Asia and beyond who make Phnom Penh home. It is the only parent-governed, not for profit, internationally accredited (CIS/WASC) school in Cambodia. ISPP is fully authorized to run the PYP, MYP and DP and is a member of host of other international organizations. 

 

THE CHALLENGE

In the Secondary School (Grades 6 to 12), the Support Services Team (SST) meets regularly to make decisions about the services provided to individual students based on their unique needs. These needs could be related to English language placement, a learning support need, or even a counselling or health related response. As every student’s context and needs are different, the team relies heavily on qualitative (teacher feedback, observations, referrals, etc.) and quantitative (assessment achievement, standardized tests, etc.) data to make appropriate decisions about differing levels of support that can be provided to each student. 

 

Over the years, the team has struggled to compile and synthesize all of the data needed which will be used to inform their decision making. The sheer amount of data and the non-uniform way in which the data was housed meant that this task was time-consuming and caused a delay in decision making. It meant that students were not receiving appropriate responses or interventions to their needs in a timely manner and teachers became frustrated at a perceived lack of inaction. Furthermore, because the data was housed in a variety of different forms and locations, key pieces of information were sometimes missed, causing potential inappropriate responses to the original concern. 

 

THE SOLUTION 

ISPP became interested in Learning Analytics Collaborative at an early stage, primarily as a way to house important school-wide assessment data. It was originally felt that the benefit of the LAC would be to provide bigger picture information about school-wide achievement both over the course of a semester or year, and longitudinally. As years of data became available in this one-stop-shop approach, it quickly became clear that in the Secondary School, the greatest use for teachers was being able to drill down and receive information about individual student achievement. 

 

The SST was also naturally drawn to the individual student data dashboards as a way to create a quick snapshot of student performance over time in order to help inform individualized responses to student concerns. Where once, the team may have leapt to a conclusion about a particular student based on current teacher feedback, they were now able to provide much more context with more specific sets of longitudinal data that inform more appropriate responses and interventions. 

 

THE OUTCOME 

Nowadays, when discussing student concerns or achievement, the LAC is our first port of call. We have been able to work with the team at the LAC to make the data work for our context. We have developed whole school protocols for how teachers look at and make information decisions and there is now a culture that data can be used as a powerful tool to inform our practices and responses.


Popular posts from this blog

The End of Year Data Handover

“And then she went to the porridge of the Little Wee Bear, and tasted it, and that was neither too hot nor too cold, but just right, and she liked it so well that she ate it all up, every bit!” — Goldilocks and the Three Bears    For many of us, the sun is shining and we are in the mad dash of wrapping things up before escaping for a well deserved summer. I suspect it would be an easy task if wrapping up was all we had to do, but of course it’s never that simple in a school. We don’t just pack up our class, we need to hand them over to next year’s division and teachers, and get ready to receive our next batch. The data handover is enormous, and figuring out the what and how requires a “Goldilocks” attitude - we’ve got to get it just right. Quantity: Sharing enough to inform, but not so much that it will overwhelm next year’s teachers.  Ingredients: Not sharing just numbers, but also anecdotal records and holistic data that will help teachers know students better and so...

Which comes first? The process or the culture?

  “Should we meet with primary and secondary leadership teams separately or together?” This question came up during a recent chat with Joe Barder, IT Director at AIS Lagos, when we were figuring out a strategy for building their data culture. A simple question, but it got me thinking a lot about the difference between organizational culture and organizational practices, and how we need to consider both when fostering change. At AIS Lagos, everyone is eager to dive in and start analysing data. However I also sensed some hesitation from Joe about jumping in without first establishing norms and shared practices. The question of whether to have data discussions at a whole school or division level is really about whether we want to start with targeted, relevant, and actionable sessions tailored for each group, or if we take the time to develop a whole-school shared understanding of what it means to be data-informed. In other words, do we focus on the culture or the practice?  On on...

Growing Data Champions

In my work with schools, I’m always on the look out for a school’s data champions: the early adopters of a culture where data is valued and is used to improve schools and student outcomes. Data champions help colleagues understand how to find, interpret, and use data effectively. They are also translators, able to turn complex findings into clear and actionable insights.  Image by  Mohamed Hassan  form  PxHere  - CC0 Public Domain We often go looking for data champions in the IT office, or failing that, in the math department, but the truth is that data champions are hiding in plain sight everywhere; anyone who believes in using data to inform choices, and who can convince others of the value of data, has the potential to become a champion.  So how do we find and grow these “sleeping champions”? Jim Collins share strategies for building “enduring greatness by cultivating a talent pipeline”. In a data context, this could include: Modeling data-driven d...