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.
Keeping out that bad data like a pro.
In short, errors are inevitable. So how can you deal with them?
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. programme 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 testings
Specific Training Outcomes
At the end of this course, participants will understand theories of and approaches to Data Centric Monitoring and Evaluation
Understand the systemic data linkages of M&E circles and the people behind each dataset.
Able to create a circle of data tag, data track and data trace system within a selected technology set.
- Engage M&E systems more confidently and support stakeholders in the course of M&E data collection.
- Build an DC-M&E plan, projects and implement it.
- Build a DC-M&E community locally or internationally.
- Understand the technologies behind the community.
- Learn advocacy to enhance technology adoption in policy-based circles.