Examen
DVA2601Assessment 6
- Grado
- Institución
Exam of 2 pages for the course dAV34 at dAV34 (DVA2601Assessment 6)
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1. Conventional M&E:Definition: Conventional M&E is a top-down approach where external experts or agencies define
project indicators, collect data, and evaluate progress without active involvement from project
beneficiaries.
Advantages:
a. Objectivity: Conventional M&E is often perceived as more objective since external experts are less
likely to be influenced by personal biases or vested interests.
b. Expertise: It leverages the expertise of professionals in data collection and analysis, ensuring
rigorous and standardized methods.
c. Comparability: Conventional M&E allows for comparability across projects and sectors since
standardized indicators and methodologies are often applied.
Limitations:
a. Limited Local Context: Conventional M&E may overlook local nuances, leading to a lack of
understanding of the project's real impact on communities.
b. Top-down Approach: It can perpetuate power imbalances, as beneficiaries have limited say in the
design and evaluation of projects.
c. Inflexibility: Conventional M&E may struggle to adapt to rapidly changing contexts or evolving
project goals.
2. Participatory M&E:
Definition: Participatory M&E involves active engagement of project beneficiaries and stakeholders
in defining indicators, collecting and analyzing data, and making decisions about the project's course.
Advantages:
a. Local Empowerment: Participatory M&E empowers local communities and stakeholders, giving
them a voice in decision-making processes.
b. Contextual Relevance: It leads to the development of context-specific indicators and evaluation
methods, ensuring that the project addresses local needs.
c. Ownership: When beneficiaries actively participate, they take ownership of the project's success
or failure, increasing their commitment to its goals.
Limitations:
a. Resource Intensive: Participatory M&E can be resource-intensive in terms of time, capacity-
building, and coordination.
b. Subjectivity: There is a risk of subjectivity in data collection and analysis, as beneficiaries may
have varying perspectives and interests.
c. Lack of Expertise: In some cases, beneficiaries may lack the technical expertise required for
rigorous data collection and analysis.
Supporting Arguments with Scholarly Sources:
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