Foundations & planning
Lessons 01–03L · 01
Foundations of Program Planning and EvaluationThe lesson defines evaluation as the judgement of a program's merit, worth and significance, compares the main approaches on the evaluation theory tree, and introduces Canadian evaluation policy, ethics screening and the CDC evaluation framework.
L · 02
Needs Assessment and Planning ModelsStudents assess need with Bradshaw's taxonomy, local data and asset mapping, set priorities with weighted criteria and a health equity impact assessment, compare planning frameworks, and write SMART objectives.
L · 03
Program Theory: Logic Models and Theories of ChangeThe lesson distinguishes change and action models, builds logic models and a theory of change by backward mapping, and introduces contribution analysis and realist context-mechanism-outcome configurations.
Engagement & measurement
Lessons 04–05L · 04
Interest Holder Engagement and Evaluation QuestionsStudents map the interest holders in an evaluation, plan engagement on the IAP2 spectrum with attention to equity and Indigenous evaluation, and draft and prioritize evaluation questions with primary intended users.
L · 05
Indicators, Process Evaluation and Mixed MethodsThe lesson specifies indicators in full, plans a process evaluation of reach, dose and fidelity, integrates evidence in mixed methods designs, and builds a data collection plan and a simple dashboard.
Evaluation designs
Lessons 06–08L · 06
Randomized Designs for Health Services InterventionsStudents learn why randomization supports causal claims, place trials on the PRECIS-2 continuum, size a cluster randomized trial and interpret its analysis, and weigh stepped-wedge designs and the ethics of randomizing access.
L · 07
Quasi-Experimental Designs I: Comparison Groups, Difference-in-Differences and MatchingThe lesson identifies threats to internal validity in non-randomized evaluations and estimates program effects with difference-in-differences, propensity score matching and synthetic control, with worked examples based on simulated data.
L · 08
Quasi-Experimental Designs II: Time Series, Discontinuities and Natural ExperimentsStudents interpret segmented regressions for interrupted time series, estimate sharp and fuzzy regression discontinuity effects, interpret natural experiments and instrumental variables, and compare these designs with quality improvement methods.
Implementation, economics & use
Lessons 09–10L · 09
Implementation ScienceThe lesson distinguishes efficacy, effectiveness and implementation research and applies implementation outcomes, CFIR 2.0, RE-AIM, the ERIC strategies and hybrid effectiveness-implementation designs to a program rollout.
L · 10
Economic Evaluation, Reporting and Evaluation UseStudents cost a program, compare the forms of economic evaluation and interpret an incremental cost-effectiveness ratio, synthesize mixed evidence into an evaluative judgement, and plan reports that decision-makers will use.