The distance between a working prototype of student performance analytics and a system the business can depend on is where most budgets disappear. Boards are asking for measurable returns from this strand of digital and data-driven work, not demonstrations. It is written for people who have to make the digital and data-driven work capability work with the resources they already have. They leave able to brief senior management on student performance analytics in terms that support a decision. Moving this part of digital and data-driven work from written policy into daily practice is not achieved by a single decision. Mature organisations treat the wider digital and data-driven work agenda as a standing capability rather than a project that finishes. The teaching approach is deliberately practical: participants build a delivery roadmap for student performance analytics as they go. The programme takes participants through this aspect of digital and data-driven work end to end, from framing the problem to closing it out. Work concludes with a self-assessment of the practice within digital and data-driven work that participants can repeat annually.
Expected Learning Outcomes
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Diagnose whether a problem in student performance analytics is one of design, resourcing or discipline.
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Build a security and access model for student performance analytics appropriate to the sensitivity of the data involved.
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Recognise early indicators that student performance analytics is drifting away from its intended design.
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Adapt recognised practice on student performance analytics to local constraints without hollowing it out.
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Design the pilot for student performance analytics so its result is decisive rather than merely encouraging.
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Agree the retirement plan for the legacy process student performance analytics replaces.
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Establish version control and rollback for every component of student performance analytics that reaches production.
Who Should Attend
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Compliance and governance staff whose remit includes student performance analytics.
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Business analysts translating requirements for student performance analytics.
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Chief information officers accountable for the investment in student performance analytics.
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Staff seconded into improvement work on student performance analytics.
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Product owners prioritising the roadmap for student performance analytics.
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Information security officers reviewing the exposure created by student performance analytics.
Course Modules
Open any module to see its sessions and topics.
01
Student performance analytics: governance, ethics and explainability
2 sessions · 8 points
Session 1Choosing a supplier for student performance analytics without being captured
Classify the data in student performance analytics and apply access controls that match the classification.
Define the exit route from the supplier supporting student performance analytics.
Set the metrics that will show whether student performance analytics is drifting from its intended behaviour.
Estimate compute and licensing cost for student performance analytics at expected and at peak load.
Session 2Building the method for student performance analytics step by step
Set out the decisions in student performance analytics that require sign-off and by whom.
Map the handovers in student performance analytics between functions and secure them.
Verify that student performance analytics still performs when input volume doubles unexpectedly.
Check that records of student performance analytics answer the questions likely to be asked.
02
Student performance analytics: people, skills and the change that follows
2 sessions · 8 points
Session 1Where student performance analytics touches systems nobody wants to change
Design the pilot for student performance analytics so that a negative result is still useful.
Name a single owner for each element of student performance analytics.
Agree who is on call for student performance analytics outside working hours.
Reduce the variation in how student performance analytics is carried out between teams.
Session 2Making student performance analytics secure without making it unusable
Check that student performance analytics still works when volumes rise unexpectedly.
Record the rationale for each significant choice made about student performance analytics.
Specify the fallback path when student performance analytics is unavailable.
Confirm that contractual obligations around student performance analytics are understood.
03
Student performance analytics: architecture, integration and the existing estate
2 sessions · 8 points
Session 1Testing student performance analytics before relying on it
List the data sources student performance analytics consumes and confirm each has a named owner.
Set the review interval for student performance analytics and who attends.
Decide which legacy process student performance analytics retires, and set the date.
Identify every system student performance analytics must read from or write to.
Session 2The cost of student performance analytics and how to present it
Measure the current quality of the data feeding student performance analytics before assuming it is usable.
Review whether student performance analytics is aligned with the objectives of the transformation programme.
Confirm that reporting on student performance analytics reaches the people who can act.
Test student performance analytics against edge cases drawn from real historical records.
04
Student performance analytics: measuring benefit and retiring what it replaces
2 sessions · 8 points
Session 1The data question everyone skips at the start of student performance analytics
Confirm the retention and deletion rules applied to data inside student performance analytics.
Arrange the handover of student performance analytics so capability survives staff changes.
Benchmark the organisation's student performance analytics against comparable operations.
Confirm that those complying with student performance analytics understand why it exists.
Session 2Explaining student performance analytics to people whose jobs it changes
Agree the indicators that will show whether student performance analytics is improving.
Identify the skills the team lacks to operate student performance analytics independently.
Plan how student performance analytics is versioned and how a bad release is rolled back.
Draft the minimum viable delivery roadmap for student performance analytics.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
Workshop or Program Participation
Airport Transfers
Customized Badge
Expert Mentorship (Private Sessions)
Supervision & Secretarial Services
Accredited Certificate of Participation
Complete Training Kit
Coffee Break
Closing Ceremony
Gold Package
At least 3 people
USD1,850
5-night stay in a 5-star hotel
Workshop or Program Participation
Airport Transfers
Customized Badge
Expert Mentorship (Private Sessions)
Supervision & Secretarial Services
Accredited Certificate of Participation
Complete Training Kit
Coffee Break
Closing Ceremony
Complete your registration
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