Impact Evaluation: Masterclass

Advanced Techniques for Measuring Impact in Projects and Programs

What you'll learn

Understand the core principles and methods of impact evaluation.

Identify and apply appropriate evaluation designs and methods

Design rigorous impact evaluations using experimental and quasi-experimental approaches.

Effectively communicate evaluation findings to diverse stakeholders

Requirements

Basic Knowledge of monitoring and Evaluation is an added advantage

Description

Go beyond implementation and truly understand your impact. In today's results-driven world, proving effectiveness is essential. This course, "Impact Evaluation : Masterclass," equips you with the practical skills and theoretical knowledge to rigorously evaluate the impact of projects and programs across diverse sectors. Whether you're in government, an NGO, education, or a student, this course will empower you to become a confident and capable impact evaluator.Imagine confidently answering, Are our initiatives truly making a difference?This course provides the tools and techniques to answer these critical questions with rigor.Here's what you'll learn:Fundamentals: Core principles, key concepts, and the crucial role of impact evaluation.Methodological Toolkit: Experimental and quasi-experimental methods, their strengths, limitations, and application.Randomized Controlled Trials (RCTs): Design, implementation, and ethical considerations – the gold standard.Quasi-Experimental Designs: Robust alternatives like Difference-in-Differences, Propensity Score Matching, and Regression Discontinuity Design for real-world evaluation.Threats to Validity: Identifying and mitigating biases and confounding factors.Sample Size Calculation: Practical skills for A/B testing designs.Qualitative Integration: Complementing quantitative data for deeper insights and context.Why Choose This Course?Practical & Applied: Real-world examples and case studies across various sectors.Expert Instruction: Learn from an experienced tutor in impact evaluation.Accessible to All: Engaging and informative for beginners and those seeking deeper expertise.Empower Decision-Making: Generate credible evidence for strategic choices and maximizing positive change.By the end of this course, you will be able to:Design and implement rigorous impact evaluations.Critically analyze findings and identify key takeaways.Communicate results effectively to stakeholders.Contribute to evidence-based decision-making

Overview

Section 1: Introduction to Impact Evaluation

Lecture 1 Introduction to Impact evaluation

Lecture 2 Brief overview of counterfactual concept

Lecture 3 How Impact Evaluation differs from other M&E Components

Lecture 4 Do we conduct Impact evaluation for the entire program?

Lecture 5 When to conduct Impact Evaluation

Lecture 6 Importance of Impact Evaluation

Lecture 7 Choosing the right evaluation Approach

Section 2: Impact Evaluation Methods

Lecture 8 Impact Evaluation Methods

Lecture 9 Key terms to master

Section 3: Randomized Controlled Trials (RCT)

Lecture 10 Introduction to the Randomized Controlled Trials (RCT)

Lecture 11 How Randomization works

Lecture 12 Randomization methods

Lecture 13 Lottery Method

Lecture 14 Phase-in-method

Lecture 15 Randomization Encouragement Method

Lecture 16 Units of Randomization

Lecture 17 How does RCT work-PROCESS

Lecture 18 Key Facts about RCTs

Lecture 19 RCT Assumptions for valid Impact Evaluation

Lecture 20 Internal Vs External Validity

Lecture 21 When you can`t apply RCT method

Lecture 22 RCT practical Example

Section 4: Difference-in-Differences (DID)

Lecture 23 Introduction to Difference-in-Differences(DID)

Lecture 24 The Parallel Trend Assumption

Lecture 25 Basic Difference-in-Differences Setup Concept

Lecture 26 Difference-in-Differences Example

Lecture 27 Difference-in-Differences(DID) Assumptions

Lecture 28 DID Working Example

Section 5: Propensity Score Matching (PSM)

Lecture 29 Introduction to Propensity Score Matching (PSM)

Lecture 30 Matching Process Concept

Lecture 31 Propensity Score

Lecture 32 Matching Algorithms

Lecture 33 Establishing Impact for the PSM Approach

Lecture 34 PSM data requirements

Lecture 35 Key Assumptions of the PSM Method

Lecture 36 Limitations of PSM Method

Lecture 37 Supplementing PSM with DID

Lecture 38 PSM Process Summary

Section 6: Regression Discontinuity Design (RDD)

Lecture 39 Introduction to Regression Discontinuity Design(RDD)

Lecture 40 Constructing Counterfactuals in RDD

Lecture 41 RDD Assumptions

Lecture 42 RDD data requirements

Lecture 43 Limitations of RDD method

Section 7: Threats to validity in Impact Evaluation

Lecture 44 Introduction to threats to Validity

Lecture 45 Common Threats to Validity

Lecture 46 Attrition

Lecture 47 Non-compliance

Lecture 48 SpillOver

Lecture 49 External Interference

Lecture 50 Strategies for the effective Impact Evaluation

Section 8: Sample Size Calculation In Impact Evaluation

Lecture 51 Why sample size Matters

Lecture 52 Key parameters for the Sample Size Calculation

Lecture 53 Sample size Formula-Continous Outcome

Lecture 54 Sample Size formula-Proportion Outcome

Lecture 55 Adjusting sample size for the Cluster Design Effect

Lecture 56 Adjusting sample size for the attrition or non-response

Lecture 57 Example sample size calculation

Section 9: Qualitative Approach in Impact Evaluation

Lecture 58 Introduction to Qualitative Impact Evaluation

Lecture 59 Qualitative Impact Evaluation Methods

Lecture 60 Most Significant Change (MSC)

Lecture 61 Outcome Mapping

Lecture 62 Outcome Harvesting

Lecture 63 Appreciative Inquiry

Lecture 64 Making Decision on which Qualitative evaluation method to use

Government officials, NGO workers, educators, students, aspiring evaluators.