Introduction to the course
No matter the size and level of data collection, a common problem with the exercise is error. Some of the errors are minor but others are large enough to disregard the purpose of collecting the data in the first instance.
What are the major causes of errors in data collection?
Surveyors may be poorly trained, or well-trained ones may misunderstand a question’s responses or units. They may mistype a respondent’s answer or enter fake data to save time. Respondents may lie to save face, or they may answer randomly if they don’t understand questions. And anyone involved may get confused or distracted, even during short surveys.
In short, errors are inevitable. So how can you deal with them?
This course will put the tools you need to keep out bad data practices in your hands. After the course you can turn your data collection from a minefield of errors to zero errors exercise.
Who attends this course?
Heads of Ministries, Departments and Agencies (MDAs), Donor whose staff and partners are working on development projects locally and/or globally. programs managers, Career Individuals, Monitoring and evaluation specialists; project coordinators; Evaluators specialists; ; Non-For Profit (NFP) organizations, Funders and students.
- Welcoming and getting to know participants and their M&E environments
- Gloose through your technical and managerial knowledge of M&E
- Introduction to DC-Results-based management theories and other related topics such as monitoring, evaluation, methodologies, tools, techniques, reporting and control, risk management etc.
- The 3 Technologies for M&E, Tag, Track and Trace. And how participants see themselves in this world.
- Practical testing's
Specific Training Outcomes
At the end of this course, participants will understand the step-by-step procedures of collecting error free data in their unique settings. After the course you can turn your data collection from a minefield of errors to zero errors exercise by using various technology tools. This will include:
- Types of data validations?
- Setting the right questions and making mandatory options
- Question choices and dynamic limits
- Use of logic and randomize options.
- Numerical and open-ended questions or choices
- User requirements and customized survey
- Managing submissions
- Move to policy-based analysis.
- Engage data collection systems more confidently and support stakeholders in simple data collection technologies.
- Build an error free data collection plan and implement it.
- Build an intelligent database community locally or internationally.
- Understand the data technologies behind public sector and NFP Result Based Management (RBM).
- Learn advocacy to enhance technology adoption in policy-based circles.