KS5: Getting Started Checklist (Admin)

The aim of this article is to guide you through all the necessary steps to complete the set up of Sisra Analytics for KS5 cohorts. Click the links to the full articles for more information on each step (which opens them in a separate tab) if needed, as well as additional optional features that you can set up to get even more functionality from Analytics.

We have also included an interactive PDF checklist at the very end of this article, which you can click to download. This can be handy to tick off each step as you work through.

Step 1 / Student Data Profile

To start, you will need to plan with your SLT which custom student data filters you want to be able to use in your reports to filter your data by (e.g. Disadvantaged, Registration Group, etc.). You will then need to set these up and add them to your Student Data Profile, which is where you define which filters should be included in student data files that you import into Analytics.

• Create and Define Student Filters - You can create these additional filters via CONFIG. > Student Data > Filter Management, and then add these to your Student Data Profile ready for importing your student data. 

Step 2 / Grade Methods

Next you need to plan and set up your grade methods. These are used to tell Analytics what type of grades are going to be uploaded for each qualification, as well as the points and entries each grade is worth, to be used in the calculations within the reports. 

• Identify and Create Grade Methods - You can create grade methods for GCE A Level, AS Level, EPQ etc. via CONFIG. > Grade Methods > KS5 Methods > click Create KS5 Grade Method.

Step 3 / Student Data

Now it's time to prepare and import your student data files. These are used to import all student details for an individual cohort, including information such as student IDs, names, classes and additional filter values such as Gender, Ethnicity, etc. as defined in your Student Data Profile. This information can be extracted from your MIS, formatted using the Sisra Analytics Excel Add-In and then imported into Analytics. 

• Download Excel Add-In - This a free tool to help you prepare your student and grades data for importing and uploading to Analytics. You can download the Add-In via this page.
• Extract and Prepare Student Data - Once you extract the necessary data from your MIS, this will need to be prepared for import using the Add-In so it's in the correct format for importing into Analytics. Note: If you’re working with Current Y13 or a Leavers cohort then we recommend extracting two student data files. One containing their historical student data from when they were in Y12 (from the time of the October census), and one containing their Y13 current student data.
• Import Student Data - Once you have prepared your data, you can import this via DATA > select Keystage 5 and cohort > STUDENTS > Import. Select the year the file relates to, then locate the file to be imported and click Import.
• Key Filter Mapping - Map your school's Disadvantaged, Gender and SEN filters to the relevant Sisra Filter Values if your school is part of a Multi Academy Trust which uses the Juniper Insights MAT Dashboard (This page does not need to be completed if this is not the case). STUDENTS > Key Filter Mapping.

Step 4 / KS4 Core Baselines

Once your student data has been imported, the next step is to obtain and import the KS4 Core Baselines for your students. Core Baselines are the official points, or challenge points, students have achieved at the end of Y11. These must be imported and set up accurately within Analytics to ensure headline figures are calculated in line with the DfE within the reports, such as L3VA and L2 Progress. The articles linked below will help with all of the steps here.

• Find your students core baselines - These should include Overall APS and GCSE APS for L3VA, and the Maths and English points for L2 Progress and L3 Maths measures.
• Prepare and Import Core Baselines - Once your file of core baselines has been prepared (and saved as CSV (MS DOS) format) you can import this via KS4/EAP > Core Baselines > Import Core Baselines. During the import, pair the baselines by selecting the relevant option from the SISRA Baseline dropdown.

Step 5 / EAPs and EAP Baselines

Next you need to set up your EAPs. An EAP (Expected Attainment Pathway) serves two main functions. The first is to set the grade method used for each qualification (as created in step 2), therefore EAPs must be created. The second function is optional and is used to define the grades students are expected to achieve each term. These are used to populate whether students are on, above or below track in the reports.

• Plan your EAPs - Decide whether you'll be wanting to use the On Track functionality, and if so, decide what type of grades to use as students' starting points (for example, you could use targets).
• Prepare and Upload your EAP Baselines - Once you have decided on the EAP Baselines you want to use (e.g. target grades), you can prepare these using the Excel Add-In and upload them via KS4 / EAP > EAP / Baselines > Uploads. 
• Set Up EAP Baselines - Once your baselines have been uploaded, you will need to set these up via KS4 / EAP > EAP / Baselines > Baseline Management > Edit, ensuring to select the appropriate grade type and grade method, where necessary.
• Create your EAPs - Once you have set up your baselines, you can create your EAPs via KS4 / EAP > EAP / Baselines > EAP, and enter the expected grades in each one if you're wanting to make use of the On Track functionality. Once you have created and defined at least one EAP in your cohort, you will then have the option to copy this to create up to 10 additional EAPs simultaneously, using the same setup This process can be repeated as many times as needed and also allows you to copy EAPs across cohorts.

Step 6 / Grades Data

Now that you have created your EAPs, it's time to upload your grades data (such as Targets, Mocks, latest Assessments). Grades data files are used to upload all student grades for the qualifications they are taking. This should include student IDs, student names, qualification names and grades.

This information can be extracted from your MIS, ran through the Excel Add-In and then uploaded into Analytics. Analytics uses the student ID within student and grades files to link the appropriate students with the correct grades. Therefore, you must be consistent with the student ID used within all files for a cohort.

• Extract and Prepare your Grades Data - Once you extract your grades data you can prepare this for uploading using the Excel Add-In.
• Upload Standalone Grades (e.g. Targets, Mocks, Exams etc.) - You can upload standalone grades in GRADES > Uploads, then select the appropriate data set (Exams, Targets, Mocks, Data Set 3 to 5). Select the appropriate 'term' the data relates to or was collected within and also the relevant 'Grade Type', then upload your grades file.
• Upload Assessments - You can also upload assessments (data you would like to track over time, such as current working at grades). Assessment cycles in school can be replicated by creating 'collections' in Analytics, within GRADES > Uploads > Assessments.

Step 7 / Assign Qualifications to Classes

You must then assign each qualification to the relevant set of classes for Analytics to pull these through for relevant grades. If a qualification is not assigned to classes, all students with grades in that qualification will appear as ‘Not in Class’, preventing class analysis in reports. A set of classes is a group of individual classes taught in a particular subject area. For example, the individual classes 13En1, 13En2, etc. could sit within the ‘English’ set of classes, taken from the 'Subject' column of the student data files imported for a cohort.

• Assign Qualifications to the appropriate sets of classes - In STUDENTS > Classes > Assign Quals. Sets of classes will be displayed down the left and unassigned qualifications (taken from the Qualification column in the grades files uploaded) will be shown at the bottom of the page. To assign a qualification to a set of classes, click the + icon next to a set of classes, place a tick next to the relevant qualification/s and click ‘Save’.

Step 8 / Matching

The next step is to complete the Matching process. The Matching process tells Analytics important information about each qualification, such as whether a qualification should be included in the reports, which EAP should be used, to determine the grade method and expected grades for each term (if entered). In KS5, you can enter the QN codes for each qualification which allows Analytics to check the setup, ensuring they will count accurately towards the reports. 

• Complete the Matching process - This must be completed for all qualifications you wish to include in the reports via GRADES > Matching > Edit. All included qualifications must be matched successfully to continue, therefore any rows highlighted amber or red MUST be resolved, as this will prevent you from publishing the reports. 

Step 9 / Grades Management

Grades Management provides an overview of qualifications with grades uploaded into each data set / assessment, allows you to manage your grades data and performs several setup checks to highlight potential issues which could affect the accuracy of your reports. It’s important to check Grades Management and clear any warning icons shown before publishing the reports.

• Address warning icons - If any are flagged in GRADES > Grades Management > Select Dataset / Assessment.

Step 10 / National Data - Value Added

The next step is to complete the Value Added National Data page to allow Analytics to calculate L3VA in the reports. Value Added is a KS5 performance measure that calculates progress from KS4 to KS5. This uses each student’s KS4 prior attainment and national average data provided by the DfE to calculate L3VA scores for school, performance cohorts, qualifications, classes, and students. Value Added is calculated for GCE, Academic, and Applied General qualifications.

• Select the Value Added data to use - Navigate to GRADES > National Data and click Edit VA Data to select the desired 'Value Added Year'. This should reflect the year the cohort is reported on, if available. Otherwise you can use the most recent available until this is released by the DfE. Analytics will then attempt to automatically select the VA subject for each qualification, if available, based on the QN/Qual Name selected on your Matching page.

Step 11 / Publish Reports

Once you have finished setting up a cohort in Analytics, you will need to complete the publishing process to populate the reports. Each menu (STUDENTS, KS4 / EAP, and GRADES) has a separate publish section, and when you’re publishing the reports for a cohort for the first time, you will need to publish each of these areas in order, to populate the reports. However, this also means that next time you make changes to data in a specific tab, you should only need to publish the respective area. For more information on the publishing process overall, please see the following article: What does publishing mean?

• Publish STUDENTS - Via STUDENTS > Publish Students > Publish.
• Publish KS4/EAP - Via KS4/EAP > Publish KS4/EAP > Publish.
• Publish GRADES - Via GRADES > Publish Grades > Click 'Publish' next to relevant dataset/assessment. If issues are flagged in the 'Health' tab while publishing grades, we recommend resolving these - Resolve Health Check Issues.

Step 12 / Create Users

Now that the reports are published, you can create user accounts for your members of staff. This will provide them with access to Analytics so that they can log in and view the reports. Once an account is created for a user, they will be emailed a Username and Password to their registered email address.

• Create Custom Authority Groups (if required) - Authority groups are used within Analytics to determine the access levels that each staff member has. 'Admin' (access to all areas, including uploading and managing data and users & embargoed exam reports) and 'User' (access to all reports) are available by default. However, you can create additional groups if required with custom access, for example, you may have user groups for SLT, Governors, etc. via USERS > Groups.
• Create User Accounts - You can either manually create your users via USERS > User List > Create User, or prepare and import CSV file via USERS > Upload Users to create them in bulk.

Next Steps

And that's it, you've completed the setup! Well done! Below we've provided links to useful articles for further reading, which will expand on other aspects of Analytics such as accessing the reports.

As a Sisra Admin however, if you ever have any questions, the Support team are here to help. You can reach us in Analytics by clicking the 'Support' button to start a chat in real time with one of the team. This is available Monday to Friday, 9am - 5pm (UK time). Outside of these hours, you can click to leave us a message, and one of the team will get back to you as soon as possible. For more information on contacting the Support team, see our article - How to Contact Customer Support.

Useful Resources:

• Getting Started for Users - A useful article to share with staff, containing a downloadable PDF handout to guide them through Analytics and the reports from a users' perspective.
• Analysing KS5 Reports - A dedicated area of help, with a variety of articles from accessing the reports, to key functionality and FAQs!

Optional Extra Setup & Features for Admins

Below we've outlined some advanced optional extra features you can set up at anytime, to enhance the analysis available in the reports! You may want to book mark these to return to.

• Student Filter Aliases and Tags - You can create aliases for student filter values you import (e.g. 'Female' instead of F') to make the reports more user friendly, as well as 'tag' key groups of students in the reports, allowing them to standout easily in analysis (e.g. Disadvantaged students). 
• Attitude to Learning / Pastoral data - You can import 3 categories worth of additional data into Analytics, such as Homework, Behaviour, Attitude etc. that your school focus on.

Thanks for reading!