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Data analysis: WHAT and WHY

Learn the importance of aligning data collection with project goals and how to define key indicators to measure success. Understand the process of selecting relevant data and building a theoretical model. Examples provided for clarity.

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Data analysis: WHAT and WHY

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  1. Data analysis: WHAT and WHY Part 2

  2. WHAT and WHY • Data collected/indicators need to reflect project/policy goals or objectives! 1. What is it that we wish to know? • list objectives or questions 2. What information can provide the answers we seek?

  3. Example • What do we want to assess? → e.g. quality in VET • How do we define the concept/what are its objectives? → e.g. quality VET as training and education assuring employability of graduates • What are the aspects/criteria of such objectives? → e.g. competences and attitudes achieved (basic, social, technical-profession specific, ICT); completion of education and training; transition to employment; quality of employment (income, work stability etc.)

  4. Example • Consider external and internal coherence of indicators ↓ build a theoretical model reflecting the objectives, process and the results of an action) PROCESS INPUT OUTPUT OUTCOME CONTEXT

  5. Example • Decide on indicators/data needed: → How to measure indicators chosen? → Against what to measure? (derived from objectives set) → What details needed? → What kind of (qualitative/quantitative) data needed? → From which sources can they be obtained?

  6. Example Example: Investment in training of teachers/trainers How to measure (definition of an indicator)? Share of teachers/trainers participating in accredited training programmes out of the total number of registered teachers/trainers What kind of data needed? no. of teachers/trainers participating in accredited training programmes no. of total registered teachers/trainers From which sources can data be obtained? administrative sources

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