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Steps in outcome harvesting

Steps in outcome harvesting. Identify outcomes Describe the outcomes and how AAS contributed (i.e., the ToC) Verify Draw implications across the harvest Within hub Across hubs Use results. Who and how?. Baselines. Conclusions : Could be a monster

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Steps in outcome harvesting

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  1. Steps in outcome harvesting • Identify outcomes • Describe the outcomes and how AAS contributed (i.e., the ToC) • Verify • Draw implications across the harvest • Within hub • Across hubs • Use results Who and how?

  2. Baselines • Conclusions: • Could be a monster • Baselines have more of a research value for AAS than an impact assessment one • Because our main form of impact evaluation is building and testing ToC) • Need to know what we already have and are about to do: perhaps this is sufficient. • Need sharper thinking about what they will be used for • Need help with this - requires specialist expertise. Who can we draw on? • Next steps • Penang to provide instructions on how to do this, after taking some expert advice. Who can help? • Hub teams to pull together existing data

  3. Outcome harvesting • Conclusions • Makes sense, resonates, need to do it soon • Use of outcome harvesting is broader than evidence for next proposal • Should be underpinned by good research method • Will likely require external support - credibility, specialist expertise • Steps • Identify outcomes for harvesting • Processes and institutions in place to do this • Include bilaterals • Describe ToC for the outcomes • Will need external help • Verify • External oversight • Implications / next steps • Develop method guide – first iteration could be a PowerPoint • Identify external assistance • Plan how to do it in the hubs

  4. Scaling Pathways • Conclusions • Clearer, useful • Fuzzy, but that's OK • Most early outcomes are pathway 2, surprising • M&E harder for pathway 2 than 1 • Implications • Rework chapter • Socialize with hubs teams • Develop communication materials (?) including more examples, cartoons ... • Guidance / capacity (enabler)

  5. M&E strategy • Conclusions • Strategy is ok • M&E for Learning is new piece • Graphics were clarifying • Tension between linear and complex mental models • Implications • ???

  6. IDOs • Conclusions • Varying levels of comfort with the targets and process for agreeing them • IDO targets need revisiting • Implications • CPLs to send responses to 3 questions • Use to propose a process for agreeing targets this year to be discussed by PLT

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