School Performance Monitoring and Evaluation Training Course

Participants can frame a performance problem using evidence, stakeholder perspectives and measurable priorities.

• Problem tree analysis identifies immediate causes, root causes and effects
• Reviewing school improvement plans for measurable priorities and realistic assumptions
• Stakeholder mapping identifies information needs, influence and accountability interests
• Equity analysis examines barriers affecting marginalised learners and underserved groups
• Prioritisation matrix ranks performance problems by severity, urgency and controllability
• Framing management questions before selecting indicators, data sources or methods

Participants can build a theory of change linking school interventions to intended outcomes.

• Theory of Change maps causal pathways from interventions to learner outcomes
• Results chains sequence inputs, activities, outputs, outcomes and long-term impact
• Assumptions identify conditions required for planned results to occur
• Risks register records threats, likelihood, consequences and mitigation actions
• Testing causal logic against evidence from school improvement research
• Drafting measurable outcome statements with population, change and timeframe

Participants can create an indicator framework that measures implementation, service quality and outcomes.

• Indicator selection criteria assess relevance, feasibility, validity and decision usefulness
• Leading indicators signal implementation progress before outcome measures change
• Outcome indicators measure changes in learning, attendance, retention and transition
• SMART indicator statements specify measure, population, direction and timeframe
• Indicator reference sheets define numerator, denominator, unit and disaggregation
• Avoiding perverse incentives, double counting and indicators without management purpose

Participants can select fit-for-purpose data sources and document collection responsibilities.

• Education management information system data: enrolment, staffing and infrastructure records
• School registers capture attendance, lateness, dropout and learner transfers
• Assessment records provide learner achievement, progression and remediation evidence
• Classroom observation tools document teaching practices and instructional time
• Parent, learner and teacher surveys measure experience and perceived barriers
• Data flow mapping assigns collection, validation, aggregation and approval responsibilities

Participants can establish baselines and set credible targets for school performance indicators.

• Baseline studies establish starting values before improvement actions begin
• Historical trend analysis separates normal variation from meaningful performance change
• Target-setting methods use trends, benchmarks, capacity and resource constraints
• Annual milestones translate multi-year outcome targets into manageable checkpoints
• Performance standards define acceptable, concerning and critical indicator thresholds
• Documenting target assumptions prevents unsupported commitments and misleading comparisons

Participants can interpret learner-level data to identify progress gaps and participation risks.

• Cohort tracking follows learner enrolment, attendance, progression and completion
• Early warning indicators combine absence, behaviour, achievement and transition risks
• Assessment item analysis identifies misconceptions, difficult items and curriculum gaps
• Disaggregating results by grade, gender, disability, language and location
• Attendance rate calculations distinguish enrolment records from daily participation
• Learner progress profiles support targeted remediation and parent engagement

Participants can measure instructional quality and leadership actions using structured observation evidence.

• Classroom observation rubrics rate lesson structure, questioning and learner participation
• Inter-rater reliability improves consistency among observers using shared scoring criteria
• Time-on-task observation measures instructional time, transitions and learner engagement
• Teacher professional development logs connect training attendance with follow-up support
• Leadership monitoring tracks lesson observation, coaching and improvement plan follow-through
• Feedback protocols separate observed evidence, interpretation, action and review dates

Participants can integrate equity and safeguarding measures into school performance monitoring.

• Equity-focused indicators reveal participation and outcome gaps between learner groups
• Washington Group Child Functioning Module supports disability-disaggregated data collection
• Gender analysis identifies participation barriers, safety concerns and learning disparities
• Safeguarding reporting protocols protect confidentiality, referral pathways and case records
• Intersectional analysis examines overlapping disadvantages affecting learner participation
• Data minimisation limits collection of sensitive personal information without purpose

Participants can assess data quality and apply ethical controls to school monitoring data.

• Routine Data Quality Assessment examines accuracy, completeness, timeliness and integrity
• Verification factor compares reported totals with source documents and registers
• Data validation rules flag impossible values, duplicates and missing records
• Spot checks test register entries, assessment records and observation forms
• Consent, confidentiality and secure storage protect learners and school personnel
• Corrective action logs assign data quality issues, owners and deadlines

Participants can analyse school data using descriptive methods and interpret findings cautiously.

• Descriptive statistics summarise central tendency, spread, proportions and rates
• Cross-tabulation compares results across grades, groups, schools and time periods
• Run charts display performance trends against targets and intervention dates
• Funnel plots distinguish expected variation from unusual school-level performance
• Triangulation compares administrative records, observations, assessments and stakeholder feedback
• Interpreting correlation avoids unsupported claims about cause and effect

Participants can produce audience-specific reporting products that prompt timely management action.

• Balanced Scorecard perspectives organise learning, operations, people and stakeholder measures
• Dashboard design prioritises exceptions, trends, targets and required management actions
• Traffic-light ratings require explicit thresholds and documented escalation rules
• One-page school performance reports combine key findings, causes and decisions
• Data storytelling links visual evidence with implications, limitations and recommendations
• Performance review agendas assign actions, owners, deadlines and follow-up evidence

Participants can prepare a proportionate evaluation plan for a school improvement intervention.

• OECD DAC criteria frame relevance, coherence, effectiveness, efficiency, impact and sustainability
• Evaluation questions specify intended users, decisions and evidence requirements
• Process evaluation examines implementation fidelity, reach, adaptations and contextual factors
• Outcome evaluation assesses changes plausibly associated with school interventions
• Mixed-methods designs combine quantitative patterns with qualitative explanatory evidence
• Sampling strategies balance representativeness, feasibility, precision and available resources

Participants can select data collection methods and synthesise findings against evaluation questions.

• Survey questionnaire design uses clear wording, response scales and skip logic
• Semi-structured interviews explore implementation experiences, barriers and unintended effects
• Focus group protocols manage participation, confidentiality and dominant voices
• Document review matrices assess plans, records, reports and supporting evidence
• Thematic coding organises qualitative evidence into patterns and explanatory themes
• Evidence matrices connect findings, sources, confidence levels and recommendations

Participants can monitor improvement actions and use findings to adjust implementation decisions.

• Workplan monitoring tracks deliverables, milestones, dependencies and responsible owners
• Implementation fidelity measures whether planned activities reached intended quality standards
• PDSA cycles test small changes, review results and standardise improvements
• Issue logs distinguish operational problems, decisions needed and escalation routes
• Learning reviews examine what worked, what failed and why
• Change control procedures document approved adjustments to targets, activities and budgets

Participants can establish governance and resourcing arrangements for a sustainable school M&E system.

• RACI matrices clarify monitoring responsibilities, approvals, consultation and information flows
• M&E plans schedule indicators, methods, frequency, owners and reporting products
• Costed data collection plans estimate staff time, tools and travel
• Standard operating procedures document collection, checking, storage and reporting steps
• Capacity assessment identifies skills gaps among school and district staff
• Data governance arrangements define access rights, retention periods and accountability

Participants can build, review and present a complete school performance monitoring and evaluation package.

• Define a priority school performance problem using available evidence
• Construct a results chain with assumptions, risks and intended outcomes
• Complete an indicator framework with definitions, disaggregation and targets
• Prepare data collection, quality assurance and reporting procedures
• Design a dashboard and performance review process for decision-makers
• Present the package, receive peer review and revise implementation priorities