Introduction
In the Implementation Phase of an evaluation you put into action the evaluation plan that you developed previously. This phase covers everything from setting up for implementation through data collection and analysis.
Before beginning the Implementation Phase, you need to have a completed Evaluation Plan. Although the Evaluation Plan is a document that is always subject to revision as circumstances change and adaptations are needed, you should have a complete version that you are comfortable using as you enter upon implement of your evaluation. As part of the evaluation planning process, you should have also created a logic and pathway model. All of these products will be important tools to help guide your work through implementation and utilization.
Each evaluation is a unique experience undertaken in a unique context. While the steps in this protocol will help you anticipate many of the challenges you will face, no protocol can ever anticipate the unique circumstances in every situation. Be prepared to identify your evaluation’s unique challenges and address them while going through this phase of the protocol.
STAGE 1 – IMPLEMENTATION PREPARATION (Rough Draft, Subject to Revisions)
The Preparation stage of the Implementation Phase includes steps that need to be taken before data can be collected, that are typically not included in the formal evaluation plan. As in other phases these steps do not necessarily have to be concluded in the order presented here, but all of the steps should be addressed as part of the implementation process.
1. Reconsider alignment, context appropriateness.
2. Address ethics for human participants.
3. Set up for data collection
4. Set up for data management.
5. Conduct pilot tests.
6. Train data entry and analysis staff.
7. Train data collectors.
STAGE 2 – DATA COLLECTION AND MANAGEMENT
The second stage of the implementation phase is data collection. This includes accessing, collecting, and entering data as described in the following steps:
1. Access data sources.
2. Collect, enter and secure data.
3. Review and Clean Data.
4. Create Codebook and Code or Categorize Data.
5. Explore and Summarize Data.
6. Transform Data.
STAGE 3 – DATA ANALYSIS
The analysis stage includes tasks necessary to convert raw data into interpreted results. These include:
1. Conduct Statistical Tests.
2. Synthesize and interpret data.