Posts tagged Evaluation Methods
New Template: Telephone Survey Introduction

The Telephone Survey Introduction Template is a comprehensive script designed to guide surveyors when initiating contact with participants for telephone surveys. It provides a structured framework for addressing various scenarios and ensures a professional and respectful approach to data collection.

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A picture is worth a thousand words: Photovoice

While traditional data collection methods like surveys, interviews, focus groups, and document reviews are well-known in evaluation, there are also innovative approaches like participatory and arts-based methods. One such method is Photovoice. While it might be daunting to embrace new techniques, it's important to recognize the value of methods like Photovoice in expanding our toolkit and enhancing evaluation practices.

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New Template: Logic Model template using Canva Whiteboard

This Logic Model template is for anyone who wants to make Logic Models that look professional and visually interesting. This Canva design template can be customized to create your own Logic Model, suited to your evaluation needs. The professional design of this template makes it easy to create a visually interesting Logic Model to present to clients, share on a website, or submit in a report.

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What’s the Difference: Bias versus Confounding?

In every research and evaluation project, it is important to identify and address sources of error that may impact the accuracy of your findings and the relevance of your recommendations. Here, we will look at what bias and confounding are (and are not), the differences between them, and important considerations to take to prepare for and address both in your next evaluation project.

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New Tip Sheet: Tips for Conducting Interviews

Eval Academy just released a new tip sheet for Conducting Interviews. If you will be conducting interviews in your evaluation, then this tip sheet is for you! Whether you’re new to the process or have conducted interviews before, this tip sheet provides a good overview and refresher to make your next interview experience a great one.

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New Infographic: Qualitative Data Saturation

Eval Academy just released a new infographic about qualitative data saturation. This infographic is for those who collect or who will be collecting qualitative data and are looking to support the validity of their results. It’s a helpful resource for those who are both new and experienced in evaluation!

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What you need to know about member checking

While member checking is commonly used in qualitative research, it’s less commonly used in evaluation and we think that should change! In this article, we’ll review what member checking is and why, when, and how you should use it.

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New Template: Canva design templates for creating your own Logic Model!

Eval Academy just released two new Canva design templates for creating your own Logic Model! Whether you’re new to evaluation or if evaluation is your main role, these Canva design templates are for anyone who wants to design a Logic Model to be more visually appealing.

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Sampling and Recruitment 101

You’ve got your evaluation plan; you’ve developed your data collection tools and you’re ready to go live with collecting the data you need to answer your evaluation questions. Step 1: Identify your sample. Step 2. Recruitment. But how do you get participants to take part in the data collection process?

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New Template: Interview Tracking Log

Eval Academy just released a new template, “Interview Tracking Log.” This template is available as a Word document as well as an Excel file! This Interview Tracking Log can be used by anyone who will be completing interviews to collect qualitative data.

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Common Evaluation FAQs

In this article, we provide the answers to some of your FAQs about evaluation including: Why do people conduct evaluations? Where can I find an evaluator? What makes a good evaluator? How can I get training in evaluation? What is the difference between research and evaluation? How much does an evaluation cost?

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Sampling bias: identifying and avoiding bias in data collection

Bias in evaluation is inevitable. Reflection helps us to identify our bias and when we do, it is necessary to identify sources of bias in our processes, eliminate which bias we can, and acknowledge which bias we cannot.

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